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MACRO POLICIES TARGETING LOW INFLATION:
REVISITING THE CONVENTIONAL WISDOM IN SELECTED
DEVELOPING COUNTRIES OF ASIA
A thesis submitted in fulfilment for the degree of Doctor of Philosophy
Ahmed Taneem Muzaffar
School of Business
2013
DEDICATION
To Ishrat and Talal
ii
Acknowledgements
All praise be to All Mighty for His infinite generosity without which I could not
accomplish this task. Faith in Him sustained me when I was in doubt and guided me
when I felt lost.
My profound gratitude is to my supervisors – Professor P. N. (Raja) Junankar,
Professor Anis Chowdhury, and Professor Ronald A. Ratti – for providing me with
important academic support. Both Raja Junankar and Anis Chowdhury were
instrumental in encouraging me to think about broader developmental issues rather
than focussing on a narrow technical work. Their intellectual support instilled
confidence in me, which helped me think outside the box and to provide a sharp
critique of some of the conventional ideas of mainstream economics. Three of them
continuously pressed me to improve the clarity of my writings. This helped me
understand the aspects of theoretical and applied economics that were most difficult
to master. They also provided me moral and psychological support when I was
struggling at the initial stage. The privilege of receiving guidance from such
intellects shall remain an inspirational experience for my career in the days ahead.
Outside the panel of supervisors, I would like to thank Dr. Girijasankar Mallik,
Senior Lecturer of School of Business for his enthusiastic support, especially when I
needed to understand issues relating to applied econometrics. His door was always
open even though he was not on my supervisory panel. I am, indeed, grateful to him.
I am also extremely grateful to Dr. Zulfan Tadjoeddin for his constant material,
intellectual, and moral supports. Quite often he was the bridge between Professor
Anis Chowdhury and myself since Professor Chowdhury’s move to the United
Nations in October 2008.
My foremost gratitude is to the University of Western Sydney for awarding me with
the International Postgraduate Research Scholarship and UWS International Award.
Without this financial support I could not have embarked upon my PhD study. I also
express my gratitude to Professor Andrew Cheetham, Pro Vice-Chancellor
(Research) for allowing me to submit the thesis with a tuition waiver. I should also
iii
thank the School of Business for approving release of funds to attend conferences at
the University of California at Berkeley, USA and the University of New South
Wales, Australia. The feedback I received from the conference participants was
important in strengthening the arguments of this work.
I am also indebted to Professor John Lodewijks, Head of School of Economics for
his support and giving me an opportunity to teach in a number of units as a tutor.
Besides helping me financially, this has been intellectually very rewarding for me. I
also gained experience in teaching at a higher education institution. My thanks also
go to Craig Berry, Carolyn Love, Bec Campisi, and Barbara Pinning for their support
on administrative issues.
Finally, I should like to thank my family members, my wife, son, parents and
parents-in-law, particularly for their tremendous moral support. My parents shared
their own gruelling experiences of pursuing postgraduate studies and their words
helped me keep going. I am specially indebted to my wife Ishrat Khan who has
sacrificed her own higher studies and potential career in order to help me achieve my
own. Last but not least, I thank my little son Ahmed Talal Muzaffar for his tolerance
of my endless excuses for why I could not play with him.
iv
Statement of Authentication
The work presented in this thesis is, to the best of my knowledge and belief, original
except as acknowledged in the text. I hereby declare that I have not submitted this
material, either in full or in part, for a degree at this or any other institution.
………………………………………………
Ahmed Taneem Muzaffar
University of Western Sydney
v
Table of Contents
Acknowledgements
iii
Statement of Authentication
v
Table of Contents
vi
List of Tables
viii
List of Figures
x
Abstract
xi
Introduction: The Wisdom of Low Inflation in Developing Countries
1
1.1
An Overview
1
1.2
The Policy of Low Inflation in the Developing Countries and the IMF
4
1.3
Growth under Moderate Inflation: Experience from Selected Developing
7
Chapter 1
Countries
1.4
The Nature of Inflation Growth Relationship
11
1.5
The Research Objectives of the Thesis
19
The IMF and the Policy of Low Inflation: A Review of Article IV
21
Chapter 2
Consultation for Selected Developing Countries of Asia
2.1
Introduction
21
2.2
A Review of Related Literature
23
2.3
A Review of the IMF Article IV Staff Consultation Reports in Selected
28
Developing Countries of Asia
2.4
Chapter 3
2.3.1 Bangladesh
29
2.3.2 Bhutan
31
2.3.3 Cambodia
32
2.3.4 China
34
2.3.5 India
35
2.3.6 Indonesia
36
2.3.7 Lao PDR
37
2.3.8 Malaysia
38
2.3.9 Maldives
39
2.3.10 Nepal
40
2.3.11 Pakistan
41
2.3.12 The Philippines
42
Conclusion
44
Cross-Country Evidence on Inflation-Impact on Growth: A Review
46
of Related Literature
3.1
Introduction
46
3.2
Cross-Country Evidence of Growth-Inflation Nexus
46
3.3
Conclusion
55
vi
Chapter 4
An Enquiry into the Relationship between Inflation and Growth in
57
Selected Developing Countries of Asia
4.1
Introduction
57
4.2
Trends in Inflation and Growth in Some Selected Developing Countries
58
of Asia
4.3
The Nature of Relationship between Inflation and Growth
64
4.4
Identifying a Threshold Level of Inflation
76
4.5
Experiences with Policies Targeting Low Inflation
87
4.6
Determinants of Inflation: Demand Driven versus Supply Side
96
4.7
Conclusion
107
A Panel Study on Growth-Inflation in Selected Developing Countries
109
Chapter 5
of Asia
5.1
Introduction
109
5.2
Estimation Methods
111
5.2.1 Selection of variables and summary statistics
113
5.2.2 Empirical model
128
Empirical Results
131
5.3.1 Static panel estimation results
134
5.3.2 Dynamic panel estimation results
139
5.3.3 Summary of the results from static and dynamic panel estimations
145
5.3.4 Robustness checks and comparing the differences in the threshold
147
5.3
levels of inflation
5.4
Chapter 6
Conclusion
152
Appendix to Chapter 5
153
The Relationship between Inflation and Growth: The Bangladesh
156
Experience
6.1
Introduction
156
6.2
An Overview of the Bangladesh Perspective
157
6.3
Trends in Growth and Inflation in Bangladesh
163
6.4
A Time Series Analysis of the Growth-Inflation Relationship
166
6.5
Identifying the Threshold Level of Inflation in Bangladesh
170
6.6
Conclusion
181
Chapter 7
Conclusion
183
References
196
vii
List of Tables
Table 1
Average Annual Real GDP Growth and Inflation Rates 1950-2010
9
Table 2.1
Inflation Targets and IMF Policy, Selected Recent Studies
24
Table 2.2
Inflation Targeting Countries (Emerging and Developing Countries)
25
2011
Table 2.3.1
Average Growth-Inflation Figures in Bangladesh
29
Table 2.3.2
Average Growth-Inflation Figures in Bhutan
31
Table 2.3.3
Average Growth-Inflation Figures in Cambodia
32
Table 2.3.4
Average Growth-Inflation Figures in China
34
Table 2.3.5
Average Growth-Inflation Figures in India
35
Table 2.3.6
Average Growth-Inflation Figures in Indonesia
36
Table 2.3.7
Average Growth-Inflation Figures in Lao PDR
37
Table 2.3.8
Average Growth-Inflation Figures in Malaysia
38
Table 2.3.9
Average Growth-Inflation Figures in Maldives
39
Table 2.3.10
Average Growth-Inflation Figures in Nepal
40
Table 2.3.11
Average Growth-Inflation Figures in Pakistan
41
Table 2.3.12
Average Growth-Inflation Figures in The Philippines
42
Table 2.4
Median CPI Inflation and Growth in Countries in South Asia, Pre and
44
Post 1980
Table 3
Selected Cross-Country Studies on the Relationship between Growth
47
and Inflation
Table 4.1
Summary Statistics of CPI Inflation in 15 Developing Countries of
58
Asia
Table 4.2
Summary Statistics of Real GDP Growth in 15 Developing Countries
59
of Asia
Table 4.3
Studies on Inflation-Growth Causality
65
Table 4.4
Studies on Threshold Level of Inflation
77
Table 4.5
Studies on Low Inflation Targeting
87
Table 4.6
Inflation and Growth Statistics in Indonesia and Thailand, Pre and
94
Post IT Implementation
Table 4.7
Determinants of Inflation
Table 5.1
Summary Statistics of Growth Rates of Selected Variables, 1961-
97
125
2010
Table 5.2
Correlation Matrix of Growth Variables
126
Table 5.3
Impact of Inflation on GDP Growth, OLS Estimations
131
Table 5.4.1
Fixed and Random Effects Panel Regressions (Case 1)
135
Table 5.4.2
Fixed and Random Effects Panel Regressions (Case 2)
137
Table 5.4.3
Fixed and Random Effects Panel Regressions (Case 3)
138
viii
Table 5.5.1
Impact of Inflation on Growth, Dynamic Panel Estimations
140
Table 5.5.2
System GMM Estimations (Case 1)
142
Table 5.5.3
System GMM Estimations (Case 2)
144
Table 5.6.1
Summary of Results from Static and Dynamic Panel Estimations
146
(Case 1)
Table 5.6.2
Summary of Results from Static and Dynamic Panel Estimations
147
(Case 2)
Table 5.7.1
Inflation Turning Points in Different Time Frames
148
Table 5.7.2
Impact of Inflation on Growth, the Regional Effect
149
Table 5.7.3
Averages of Selected Variables in the Sample Countries, 1990-2010
150
Table 5.7.4
The Impact of Inflation on Growth Based on Structural
151
Characteristics of the Economy
Table A.5.1
List of Variables and Their Sources
153
Table 6.1
Key Demographic and Geographic Features of Bangladesh
158
Table 6.2
Conditions of IMF’s US $ 1 billion Loan to Bangladesh, 2010
161
Table 6.3
Decadal Averages of Growth and Inflation in Bangladesh, 1971-2009
164
Table 6.4
Unit Root Tests with Real GDP, CPI, Growth, and Inflation, 1977-
167
2009
Table 6.5
Structural Breakpoint Test for Real GDP Growth in 1992
169
Table 6.6
Cointegration Test Results
170
Table 6.7
Impact of Inflation on Growth, Conditioned upon Other Covariates,
172
1977-2009
ix
List of Figures
Figure 1
Scatter Plot of Inflation and Growth in 150 Emerging and
10
Developing Countries, 1961-2011
Figure 4.1.a
Inflation and Growth in South Asia – Bangladesh, India, Pakistan,
61
and Sri Lanka
Figure 4.1.b
Inflation and Growth in South Asia – Bhutan, Maldives, and Nepal
62
Figure 4.1.c
Inflation and Growth in East Asia – Indonesia, Malaysia,
63
Philippines, and Thailand
Figure 4.1.d
Inflation and Growth in China and East Asia – Cambodia, Lao
64
PDR, and Vietnam
Figure 4.2.a
Scatter Plot and Linear Fitted Line in Four Countries of South Asia
74
Figure 4.2.b
Scatter Plot and Polynomial Kernel Fit Curve in Four Countries of
75
South Asia
Figure 4.2.c
Scatter Plot and Linear Fitted Line in Four Countries of East Asia
75
Figure 4.2.d
Scatter Plot and Polynomial Kernel Fit Curve in Four Countries of
76
East Asia
Figure 4.3
Inflation and Growth in Selected Countries (Long Run Median in
82
per cent)
Figure 4.4
Scatter Plot between Average Real GDP Per Capita and Long Run
83
Inflation
Figure 5.1
Inflation and Growth in Selected Asian Countries, 1961-2010
111
Figure 5.2
Distribution of Real GDP Growth and Real GDP Per Capita
114
Growth in Selected Developing Countries of Asia, 1961-2010
Figure 5.3
Distribution of Inflation in Selected Developing Countries of Asia,
116
1961-2010
Figure 5.4
Relationship between Real GDP Growth and Inflation
117
Figure 5.5
Deviation from Trend of Growth Rates in Oil and Commodity Price
124
Indexes, 1961-2010
Figure 5.6
Mean of Cross-Country Data for East Year, 1960-2010
128
Figure 5.7
Conditional Correlation between Inflation and Growth, 1961-2010
134
Figure 6.1
Real GDP Growth and CPI Inflation in Bangladesh, 1971-2009
164
Figure 6.2
Growth Rate, Actual and Fitted, 1977-2009
177
Figure 6.3
Scatter Plot between Unexplained Growth and Inflation, 1977-2009
177
Figure 6.4
Parameter Stability Test using CUSUM Test
178
Figure 6.5
Parameter Stability Test using CUSUMSQ Test
178
Figure 6.6
Impulse Response Analysis for Growth and Inflation
179
x
Abstract
This thesis questions the validity of macroeconomic policies that emphasise targeting
low inflation rather than economic development. It provides systematic research in
the context of Asian developing countries to raise doubts about this conventional
wisdom of keeping inflation at a low single digit level. In this connection, the study
addresses three questions relating to the growth-inflation nexus. The first question is
whether there exists an inflation threshold at 5 per cent; in other words, whether
inflation becomes harmful to economic growth when it exceeds 5 per cent. This is
because the International Monetary Fund (IMF) advises developing countries to
restrict the inflation rate to not more than 5 per cent per annum. It is regarded as safe
and conducive to long term economic growth. The second question is whether the
threshold level varies according to country-specific circumstances and levels of
development. The purpose is to examine the validity of IMF’s policy advice of
keeping inflation at 5 per cent irrespective of country-specific circumstances. The
final question is on the nature of policy suggestions relating to growth and inflation
in country reports by the IMF. This is to determine whether the advice in the IMF
reports have any reflection of the need for a change suggested by leading economists,
including the Chief Economist of the IMF, in the aftermath of the global economic
crisis of 2008-2009.
The study examines the research questions, broadly, in two ways. First, we resort to a
critical review of existing literature and an in-depth content analysis of the IMF
Article IV country consultation reports. The second method provides an empirical
analysis using panel and time series estimation techniques. For both types of
analyses, our sample includes selected developing countries from Asia. Although a
number of studies in recent years have argued against policies targeting low inflation,
both empirically and analytically, a systematic empirical research on Asian
developing countries is limited. Besides, our interest in Asian economies, particularly
the Asia-Pacific region, is due to their good performance in terms of both growth and
macroeconomic stability. The selection of countries, however, is influenced by the
availability of data on growth, inflation, and other control variables; existence of
literature pertaining to the research issues; and release of country reports by the IMF
xi
during 2009-2010, around the time of the global economic crisis. For instance,
country-specific literature review and content analysis of the IMF country reports
include 15 and 12 South and Southeast Asian countries (including China),
respectively. On the other hand, the cross-country panel study includes 14 countries
covering economies from South Asia, Southeast Asia, Asian countries within the
Commonwealth of Independent States (Asian countries of the former Soviet Union),
and Small Island States (SIDS).
The empirical analysis using panel estimation models uses annual observations
between 1961 and 2010. The data are gathered from standard sources such as World
Bank’s World Development Indicators and the IMF’s International Financial
Statistics and World Economic Outlook. Both static models such as Fixed Effects
and Random Effects models, and dynamic panel estimation model (System
Generalised Method of Moments, SGMM) are used. Our methods have a number of
strengths over the methods used in the existing literature. First is the use of annual
observations instead of five or ten year averages. The relationship between inflation
and growth becomes stronger with greater frequency of observations. Second is the
use of SGMM since the technique is the most advanced so far, in order to take care
of the endogeneity problem. The empirical investigation also includes time series
regression analyses in a country-specific context. We examine the case of
Bangladesh between 1977 and 2009. Bangladesh is selected because the country is
widely regarded as an interesting example in the development discourse.
The findings of the research provide strong empirical evidence that an inflation rate
beyond 5 per cent is not necessarily detrimental to economic growth. The crosscountry panel study shows that the threshold varies between 8 and 15 per cent.
Similarly, results from country-specific study on Bangladesh reveal that the threshold
is around 15 per cent. Empirical evidence also suggests that the threshold level varies
according to the levels of development. Poorer and less developed countries
demonstrate a higher inflation tolerance. Analyses from the IMF country reports
show that policy advice of achieving low inflation at around 5 per cent or less
continues to receive priority in general. There is little evidence that IMF’s policy
prescription reflects the need for a change in the wake of the recent global economic
xii
crisis. Nor is it consistent with country-specific historical experience on inflation and
growth.
The results, in short, help to conclude that the empirical basis for maintaining
inflation at 5 per cent or below in developing countries of Asia is weak. We also
conclude that targeting inflation should be done after a careful consideration of
country-specific circumstances and levels of development. Taking all these into
account, the IMF should rethink its macroeconomic policy advice to developing
countries and policy makers should highlight their country-specific circumstances
during Article IV consultations with the IMF officials or when they negotiate with
the IMF to access its support facilities. Thus the analyses and findings of this thesis
reveal its two important contributions. First, it provides a unique contribution to the
literature pertinent to the growth-inflation nexus. Secondly, it helps rethinking
macroeconomic policy making in the developing countries that still follow a rule of
low inflation targeting policies. Macroeconomic policies require a broader
perspective, creating a balance between the need for stabilisation and development.
The study suggests that the developing countries should give priority to poverty
reduction and employment creation instead of pursuing a restrictive policy of low
inflation.
JEL Classification: E31, O40.
Keywords: Inflation threshold; growth; Asian developing countries; panel
estimation; IMF macroeconomic policies.
xiii
Chapter 1
Introduction: The Wisdom of Low Inflation in Developing
Countries
1.1 An Overview
Attaining price stability by keeping inflation low receives priority in macroeconomic
policies of the developing countries in recent decades. This follows episodes of high
and accelerating inflation accompanied by growth stagnation during the 1970s and
the 1980s, especially in Latin American countries. There seems to be a strongly held
belief by the mainstream economics that targeting low inflation is good for achieving
macroeconomic stability and therefore beneficial for long term economic growth.
The experiences of the “Great Inflation” of the 1970s and the “Great Moderation”
during 1993-2007 have led to a growing consensus on this.1 Founded on this belief,
policies targeting low inflation have been spearheaded by international financial
institutions such as the International Monetary Fund (IMF). The IMF strongly
advocates the developing countries to pursue macroeconomic policies targeted at
keeping inflation rates within 5 per cent. As a result, central to the economic
management of some of these countries, compelled to embrace IMF suggested
economic reforms, has been to restrain inflation at 5 per cent. Typically, these
policies include tight monetary policy and reining in fiscal deficits because of their
supposed link to cause inflationary pressure.2 This policy of fighting inflation first,
keeping it as low as 5 per cent, is suggested even at the expense of immediate
adverse impacts on growth on the ground that this would foster sustained growth in
the future. That is, the argument is couched in terms “short-run pain for long-run
gain”.
1
The 1970s was a period of high inflation, caused mainly by commodity price shocks and the
breakdown of the Bretton Woods system as a result of high US inflation. The Great Moderation was
characterised by an unusually high degree of macroeconomic stability, with steady growth and low
and stable inflation in most of the advanced economies since 1993 until the Great Recession hit in
2008.
2
Chowdhury (2006, p. 407) notes that “[o]ne major component of conditionality [by the IMF] has
been macroeconomic stabilisation…[which is] solely meant to be nominal stabilisation…of a low
inflation (targeted at less than 5 % in the medium term) and a low budget deficit (targeted at near zero
primary deficit).”
1
The IMF strongly believes that inflation above 5 per cent is harmful for sustained
economic growth and long term prospects for the developing countries. The concern
is that inflation might accelerate beyond 5 per cent and runaway inflation may lead to
a crisis. The cost of this stabilisation process, then, may turn out to be painful. This
sense of apprehension appears to have led the IMF to advise the developing countries
to become extremely cautious about inflation. An inflation rate restricted at 5 per
cent is regarded as safe. Macroeconomic policies, irrespective of country specific
circumstances, are therefore aimed at achieving this target. This is clearly not what
IMF’s Article of Agreement states that “each member shall endeavor to direct its
economic and financial policies toward the objective of fostering orderly economic
growth with reasonable price stability, with due regard to its circumstances” (Article
IV, I(i)).3 It seems that now the IMF believes this one policy fits all works the best.
The nature of relationship between inflation and growth has been studied extensively
in the literature, with mixed findings – outlining both reasons for inflation being
beneficial and detrimental to economic growth. The literature also provides reasons
why both low and high inflation may be growth-inhibiting. On the other hand, in the
wake of the crisis that led to the Great Recession of 2008-2009, the efficacy and
implication of IMF policies have also been questioned.4 Although a number of
studies (for example Chowdhury 2006; Epstein & Yeldan 2008) have provided both
empirical and analytical arguments questioning the wisdom of keeping inflation
essentially at 5 per cent or below, no systematic empirical research is available for
developing countries in Asia particularly Asia-Pacific region which have generally
done well in terms of both growth and macroeconomic stability. Incidentally, low
inflation and high growth experience of East and Southeast Asia vis-â-vis Latin
American countries’ hyperinflation and growth stagnation provided a strong rationale
for low inflation macroeconomic policy paradigm. The broad generalisation of East
and Southeast Asian experience, however, ignores the fact that both South Korea and
Indonesia grew rapidly since the mid-1960s until about mid-1980s when inflation
rates ranged between 13 and 17 per cent. Poverty also declined dramatically in both
Indonesia and South Korea during this period of rapid growth.
3
Source: http://www.imf.org/External/Pubs/FT/AA/index.htm#art4
In fact pointing out that economic crisis sometimes bring about enormous changes, Palley et al.
(2012) comment that the “economic crisis that these events have generated, combined with the failure
of the mainstream economics profession, has again put the question of change on the table.”
4
2
Therefore, there is a need for systematic investigation of the Asian developing
countries. This research aims to do that by thoroughly investigating the nature of
inflation-growth relationship in selected developing countries of Asia. The findings
of this thesis raise doubt about the validity of the widely held belief that low inflation
is always beneficial for growth, particularly in the context of developing countries.
The study is unique as it specifically seeks to answer whether inflation beyond 5 per
cent is always harmful for growth in some selected developing countries of Asia
which are pursuing low inflation targeting policies. Such empirical investigation with
particular emphasis on developing countries of Asia is absent to the best of our
knowledge. Thus, the findings of this research will have significant implications for
macroeconomic policy making in these countries. More broadly, it is a significant
contribution to the literature pertaining to growth-inflation nexus. It is also important
because despite the policy application suggested by the IMF based on this
conventional wisdom, economic performance failed to improve and poverty
remained high in many countries, even though inflation fell (see Wilkinson 2000, p.
643). Even the influential people at the Bretton Woods Institutions seem to have
acknowledged it. A former president of the World Bank (WB) admits, “…if we take
a closer look, we see something else – something alarming. In developing countries,
excluding China, at least 100 million more people are living in poverty today than a
decade ago. And the gap between rich and poor yawns wider” (Foreword to Thomas
et al. 2000).
The findings of the thesis reveal that despite suggestions to revise its position by the
leading economists, both inside and outside the IMF, in the aftermath of recent
global crisis, the IMF seems to continue with its policy prescription of achieving low
inflationary environment (usually below 5 per cent) in developing countries. This is
evident from the country consultation reports released by the IMF, still emphasising
strongly on macroeconomic stabilisation by attaining price stability. The policy
advice in the reports shows little reflection of flexibility being suggested even by its
own senior economists. The advice, irrespective of country-specific circumstances,
seems to focus on achieving certain nominal targets, for example inflation within 5
per cent in particular. It is clearly against the mandate of the IMF to fostering
economic growth and attaining reasonable price stability, taking the country specific
3
circumstances into account. This notion of one policy fits all does not find support in
the country-specific studies as well as historical evidence on inflation and growth.
Likewise, cross-country evidence, as well as empirical analysis of this thesis, finds
no justification for claiming that inflation above 5 per cent necessarily deteriorates
growth in the developing countries of Asia. Poorer countries appear to show higher
tolerance for inflation. In other words, whether inflation would cause an adverse
effect on growth depends critically on country-specific circumstances and historical
conditions. In short, evidence from the analysis of this research reveals that the
conventional wisdom of low inflation has some serious flaws and macroeconomic
policies in developing countries should not be concerned only about price stability.
Macroeconomic policies need to balance between the need for stabilisation and
development.
The rest of the chapter is organised as follows. Section 1.2 briefly discusses the
rationale behind the IMF policies geared towards keeping inflation within 5 per cent
benchmark and the problems relating to such policies. Section 1.3 takes a look at the
empirical evidence on growth performance during moderate inflation regimes.
Section 1.4 provides a brief literature review pertinent to the nature of the growthinflation relationship. Section 1.5 sets the research agenda of this study, outlining the
key research questions it attempts to investigate.
1.2 The Policy of Low Inflation in the Developing Countries and the IMF
In response to why inflation should be kept within 5 per cent the IMF notes:
“Inflation is the most pernicious tax on low-income households
that lack the means to protect their salaries and scant savings
against inflation. In addition to the negative impact on the poor,
a large body of empirical evidence has established that when
(annual) inflation passes the 5 per cent mark investment and
economic activity also suffer. It is against this background that
4
the Fund supports policies aimed at achieving or maintaining
low inflation.”5
In line with the mainstream economic view, as mentioned in the previous section, the
IMF does not seem to acknowledge that ensuring price stability by keeping inflation
at 5 per cent may conflict with the objective of fostering economic growth. Antiinflationary policies are believed to ensure both the objectives of low inflation and
long term growth – a divine coincidence as termed by Blanchard and Gali (2007).
One can, however, put forward strong theoretical and empirical evidence against
such a policy stance. Nobel Laureate in Economics, Paul Krugman in his opinion
page of The New York Times in 2011 calls this “the low inflation trap.”6 When
inflation falls it creates a deflationary expectation and thus even if nominal interest
rate is kept at a very low level7 real interest rate continues to rise. This leads to a
higher real cost of borrowing and eventually depresses the economy.8 Therefore,
pursuing a very low single digit inflation rate may create a stabilisation trap, a
situation attributable to low inflation and insufficient growth for poverty reduction
(Chowdhury 2006, p. 409). A couple of decades ago, another influential economist
James Tobin (see Tobin 1987) also pointed out the danger of paying too much
attention to inflation control.
On empirical side, Akerlof and Shiller (2009) bring in the example of Canada to
highlight the danger of placing too much emphasis on attaining a low inflation target
at any cost. In the early 1990s, the Bank of Canada vigorously pursued restrictive
monetary policies to bring down inflation from 4.8 per cent to 1.8 per cent. The
authors note that this had a terrible cost as unemployment reached 11.3 per cent in
1992, a level unprecedented since the Great Depression. Yet the then Governor of the
Central Bank of Canada commented that the costs of lowering inflation were
5
Source: http://www.imf.org/external/np/exr/faq/progfaqs.htm#q4
Paul Krugman, “The Low Inflation Trap (Slightly Wonkish),” The New York Times (23 September
2011); available at http://krugman.blogs.nytimes.com/2011/09/23/the-low-inflation-trap-slightlywonkish/
7
It cannot go below zero.
8
The Japanese economy is a classic example in this regard. This idea is also captured in the
Keynesian Liquidity Trap. There is however an opposing view which considers higher inflation rate to
cause higher cost of borrowing. Rising inflation leads to higher inflation expectation. Fisher’s
equation explains that this would lower the real return for lending and hurt lenders. As a result lenders
tend to charge higher nominal interest rate.
6
5
temporary, but there is a permanent gain in terms of changed expectations on
inflation. However, as the authors note that the recession as a result of this was
“deeper and longer than the Great Depression” (ibid., p. 115).
In the context of developing countries, a classic example of an economy trapped in a
stabilisation trap could be Argentina (see Chowdhury 2006, Note 5, pp. 426-427). In
the 1980s, hyperinflation in the country (average annual inflation rate of around 391
per cent) had led to a crisis and the IMF stabilisation program brought down inflation
to a single digit level, 1.5 per cent annually. However, as Chowdhury (2006, p. 427)
notes that the continuation of the tight macroeconomic policies created a
“deflationary-spiral” and the economy plunged into recession, causing
unemployment rate to rise from 6.5 per cent in 1991 to 17.5 per cent in 1996. This
had dire consequences for the poverty rate (head-count ratio) as well – about 13
percentage point rise in a decade, from 21.8 per cent in 1993 to 34.3 per cent in 2002.
Referring to the experience of Argentina, Chowdhury (2006) alerts that while
inflation needs to be kept under control, too much emphasis on a very low inflation
rate may lead to an inadvertent consequence that exacerbates poverty.
Epstein and Yeldan (2008) also observe the sacrifice made in terms of growth and
employment in developing countries in order to pursue a low inflationary
environment. Besides supply shocks are common in developing countries and
restrictive policies create challenges for them in such circumstances. The authors
note that there are instances where stabilisation policy of price stability, in the hope
of achieving higher growth, has not been materialised (ibid. 2008). Ensuring growth
by only combating inflation first, and by achieving a single digit rate, may not be as
simple as it appears to be. As Rodrik (1999b) explains that growth performance in
developing economies may depend on domestic social conditions and its interaction
with supply shocks. In the event where social divisions are deep and conflict
management is weak, external shocks may magnify the effects and reduce
productivity and growth.
Against the backdrop of the Great Recession of 2008-2009, the issue of revisiting the
traditional macroeconomic tenets has come at the forefront. Even the heads of the
IMF have recognised the need for it. For instance, Strauss-Kahn a former managing
6
director of the IMF felt the need for a “wholesale re-examination of macroeconomic
policy principles” in the face of the crisis.9 The Chief Economist of the IMF Olivier
Blanchard also criticised the one policy one instrument, consensus of the mainstream
economists.10 He comments that “beauty is…not…synonymous with truth…[and]
there are many targets and there are many instruments.”11 In a different paper, raising
doubt about the conventional view of low inflation strategy, Blanchard et al. (2010)
make an important observation that higher average inflation and higher nominal
interest rates to start with, would have helped to lower interest rates more, thereby
most likely reducing the decline in output and deterioration of fiscal positions in the
aftermath of global crisis. This criticism against the low inflation strategy is not just
shared within the IMF. As The Economist notes that “[e]conomists of highly
divergent stripes…[such as] Kenneth Rogoff, Greg Mankiw, Scott Sumner, Paul
Krugman, Brad DeLong – all have indicated that higher inflation would be a boon to
the economy.”12
1.3 Growth under Moderate Inflation: Experiences from Selected Developing
Countries
There is much historical evidence from some of the high growth performing
countries such as Brazil, Israel, South Korea, and Indonesia that both growth and
inflation can move together, during their early phase of development period. For
instance in Brazil, throughout the period between the 1940s and early 1980s high
growth occurred while there were several bouts of high inflation (Armijo 2005, Table
1, p. 2014). Brazil is often cited as a high inflation high growth counter-example to
the common notion that inflation was bad for the economy (Bruno & Easterly 1996).
In fact, Latin America in general had double digit inflation rates in the 1950s and
1960s, but economic growth was respectable (Pazos 1972). Growth in Brazil started
to decline when the country experienced hyperinflation in the early 1980s. In this
9
Remarks by Dominique Strauss-Kahn at the conference “Macro and Growth Policies in the Wake of
the Crisis” at the IMF’s Headquarters in Washington, DC on March 7-8, 2011.
10
The target was inflation and the instrument was policy rate.
11
Source: The speech “Monetary policy in the wake of the crisis” delivered by Blanchard at the IMF
Macro Conference, March, 2011; available at
http://www.imf.org/external/np/seminars/eng/2011/res/pdf/ob2presentation.pdf
12
The Economist (15 February 2010), “Monetary policy: a healthy dose of inflation.” Available at
http://www.economist.com/blogs/freeexchange/2010/02/monetary_policy_1 (this is because of the
problem of the zero bound to nominal interest rate.)
7
connection, Baer (1987) explains how orthodox austerity programmes, for which
growth had to be sacrificed, failed to control inflation because of its inability to
identify the causes of inflation.
Citing some development theories suggesting inflation is a good way to mobilise
resources for capital accumulation, Bruno and Easterly (1996) argue that there was
little in the early experience of developing countries to contradict this view.13 Israel’s
economy, the authors state, grew at around 10 per cent per annum between 1948 and
1973, with inflation rate of around 6 per cent to 7 per cent per annum. Both of these
figures were double compared to the figures for members of the Organisation for
Economic Cooperation and Development (OECD) around the same time. The study
argues that “the higher largely anticipated inflation was a price considered well
worth paying, especially as widespread indexation of wages, exchange rates, and
savings minimised the distortionary costs of inflation” (ibid., p. 139). Bruno and
Easterly (1996, Figure 1, p. 140) also show that the per capita growth rate actually
rose as one went from single to double digit inflation. Only when the annual inflation
rate exceeded 20 per cent did the relationship seem to turn negative.
In the Asian region, a good example is South Korea and Indonesia both of which
grew rapidly amidst high inflation rate. In explaining the policy attitude of South
Korea towards growth and inflation, Chowdhury (1996, p. 150) comments that
during the 1970s “Korea’s inflation rate remained above 20 per cent and it
maintained its growth rate at about 8 per cent, showing that Korea was more
interested in growth than price stability.” South Korea grew by 8 per cent in the
1960s and 1970s when the inflation rates were at double digit levels. The same was
true for Indonesia in the 1970s, when the country grew by 7.7 per cent while the
inflation rate was over 17 per cent (Table 1).
13
It is interesting to note that both Michael Bruno and William Easterly worked for the World Bank in
different capacities. So there is much evidence that policies suggested at country-level reports by the
international financial institutions often have little reflection of what the senior members of these
institutions think.
8
Table 1: Average Annual Real GDP Growth and Inflation Rates 1950-2010
Decade
Republic of Indonesia
Republic of Korea
Growth
Inflation
Growth
Inflation
1950-59
4.1
22.4
4.7
25.6
1960-69
3.5
196.0
7.7
13.5
1970-79
7.7
17.3
8.2
15.0
1980-89
4.8
9.4
7.8
8.3
1990-97
6.9
8.7
7.5
6.0
2000-2010
5.2
8.2
4.5
3.3
Sources: Frank et al. (1975) and Woo et al. (1994, Tables A1 and A2).
Note: Output growth and inflation rates for the Republic of Korea in the 1950s are average annual
rates for 1954-1959, excluding the Korean War period, and are based on real GNP and wholesale
price index respectively.
Contrary, to the widely held views, high inflation did not affect poverty reduction.
For example, the poverty rate declined from over 60 per cent in the early 1970s to
about 11 per cent in Indonesia just before the Asian crisis hit it in 1997. The poverty
rate shot up only after the crisis when inflation rose to 60 per cent and the economy
contracted by close to 14 per cent. As noted in Chowdhury (2006), the impact of
inflation on poverty depends on a number of factors. For example, when inflation
reduces real wages, that should encourage firms to expand employment. Therefore,
the net effect of inflation on poverty would depend on the relative elasticities of real
wage and employment with respect to inflation. One IMF study by Cukierman et al.
(1992) shows that the inflation elasticity of the income (real wage) was only 0.03,
while the output (employment) elasticity was 0.94. These estimates are similar to
those found by Romer and Romer (1999), implying that, moderate inflation may
actually reduce poverty.14 There are also other factors at work. For instance, most of
the poor are net debtors who benefit from inflation as it lowers the real value of debt.
What matters for the poor is not the aggregate price level or overall inflation, but the
prices essential commodities that dominate their consumption basket. Monetary
policy is a blunt tool as cannot deal with sector-specific price rises. It can hurt the
poor if such policy causes job losses. In general, it is the unskilled workers at the
lower end of the labour market who lose their jobs first.
14
There is a caveat here. The argument assumes that real wages decrease with moderate inflation or
wages are partially indexed to inflation.
9
In the light of the above discussion, Figure 1 takes a look at the broad experience
between inflation and growth from all the 150 emerging and developing countries, as
listed by the IMF. The scatter plot between inflation and growth sheds some light on
the nature of relationship between these two variables. First, the relationship is
nonlinear in nature as evident by the quadratic functional relationship. The signs of
the linear and the squared terms of inflation, positive and negative respectively,
confirm an inverted U shaped relationship between the two. What is also evident is
that in the range between 5 and 15 per cent of inflation there does not seem to be any
relationship. Growth does not appear to decline within this range of inflation. This
means, the upper part of the inverted-U is flat, displaying a plateau in the relationship
rather than a sharp cliff edge. Therefore, the fear of accelerating inflation and sliding
down of growth beyond 5 per cent inflation is unfounded. Thus, policy makers can
have a good deal of flexibility in dealing with inflation while pursuing strategies for
sustained growth.
Figure 1: Scatter plot of Inflation and Growth in 150 Emerging and Developing
Countries, 1961-2011
y = -0.0032x2 + 0.0598x + 4.3199
20
Real GDP Growth
15
-15
10
5
0
-10
-5
0
5
10
15
20
25
30
35
40
45
-5
-10
-15
CPI Inflation
Source: Author’s calculations based on the data from World Bank, World Development Indicators.
Notes: Growth is between greater than -10 per cent and less than 15 per cent to avoid the unusual
circumstances. Inflation is less than 40 per cent to avoid any outlier effect.
10
This finding motivates us to take a further look into the existing literature to see what
it states about the nature of the relationship. This review is carried out in the
following section.
1.4 The Nature of Inflation Growth Relationship
Understanding the inflation-growth relationship is perhaps one of the most
extensively studied macroeconomic topics in the literature. In determining how
inflation affects growth, macroeconomic theories offer both conclusions – positive
contribution as well as negative impact of inflation on growth. The positive
contribution of inflation on growth comes mainly from a Keynesian perspective (for
a summary see, for instance, Chowdhury (2002, p. 22)). In the Keynes-Kaldor effect
(see Kaldor 1955-56), inflation raises profits of entrepreneurs and therefore
redistributes income in favour of profit earners who, compared to workers, have a
relatively higher propensity to save.15 The higher profit and savings can be
channelled into investment and thus leading to higher economic growth.
In the Tobin effect, also known as Mundell-Tobin effect, (see Tobin 1965) inflation
helps the economy to become more capital intensive. Higher inflation may raise the
share of savings devoted to capital accumulation rather than to hoarding – the
accumulation of real money balances – since the real rate of return from financial
investment goes down due to inflation (Montiel 2011, p. 300). Thus physical capital
intensity is raised. This helps transformation of the economy from a traditional agrobased to a more modern industrial one. What this therefore implies is that inflation is
an integral part of growth.
The third proposition comes from the Kalecki effect which explains that during
inflation, increased seignorage, in other words inflation tax revenue, leads to forced
savings by people in an attempt to retain the real value of savings.16 This transfer of
resources from households to government allows government to take up necessary
15
The redistribution of income, according to Keynesian perspective, takes place because nominal
wages are assumed to be sticky and do not change quickly in response to changes in prices. A rise in
the price level therefore reduces real wages making entrepreneurs better off and workers worse off.
16
Seignorage is the amount of revenue government raises by printing money. Against the Keynesian
view, Cagan (1956) suggests that attempts to push the collection of seignorage above its maximum
may lead to hyperinflation.
11
investment (see Johnson 1969, Chapter 9 cited in Paul et al. 1997, p. 1388).17 The
writings of Kalecki also suggest that an upsurge of inflation would arise from some
initiating sector(s) which seek to increase their share of national income (Sawyer
1985, p. 286). This will lead to a competition amongst different competing sectors
trying to offset the gains from each other through further price rises. Inflation would
not proceed at a uniform rate either through time or across sectors under such
circumstances (Kalecki cited in Sawyer 1985, p. 286).
In short, the above propositions suggest that inflation is inevitable in a growing
economy and inflation may even be needed to support or induce faster structural
changes in developing countries.
On the other hand, proponents stating inflation having a negative impact on growth
derive their arguments from neoclassical theories. For example, according to the
Pigou effect, which considers real money balances as part of households’ wealth,
rising price level would cause real money balance to fall making consumers feel less
wealthy. This leads to lower consumer spending and ultimately becomes harmful for
economic growth.
Inflation is also believed to be detrimental to investment and, therefore, harmful for
economic growth. Higher inflation may raise the cost of maintaining working capital,
in the form of real money balances. If money and capital are complements – higher
physical capital requires greater need for working capital – then higher inflation
would make capital accumulation more costly. Thus, it would impede investment and
growth. The economists of neoclassical origin also argue that inflation leads to
higher volatility in inflation thus raising uncertainty in terms of potential income
flow and giving misleading signals to the markets. Friedman (1977) argues that
increased uncertainty reduces the information function of price movements and
17
According to Keynesian mode such intervention by government might be essential in the absence of
a developed capital market ensuring a mechanism whereby saving is automatically transforming into
investment. According to Keynes, for example cited in Wilkinson (2000, p. 645), higher income may
lead to higher proportion of it to be saved by the workers and thus this increased propensity to save
may cause a decline in consumption and aggregate demand. This ultimately leads to unemployment as
workers will not be able to find jobs because of shortage of demand for products or services they
could produce and squeezes out excess savings. This proposition is sometimes known as paradox of
thrift and proposed to refute the orthodox view – Say’s Law – supply creates its own demand
(analogously: savings create investment).
12
impedes long term contracting. The differences in sectoral prices, moving at different
rates, create distortions in investment decisions and misallocation of resources. All
this would lead to reducing investment and growth.
In an open economy, inflation causes domestic goods and services becoming
relatively more expensive leading to a fall in exports. That is, inflation may lead to
real appreciation of domestic currency and therefore adversely affecting export and
economic growth.18 Investment and growth can be negatively affected through
another way in an open economy. If the households have a choice between holding
deposits in domestic banks and holding foreign financial assets, a rise in domestic
price level may reduce the real return from domestic deposits. This may cause
capital flight from the domestic economy. Because of the reduced flow of credit to
domestic financial institutions for potential investment, economic growth, ultimately,
is hampered (see Montiel 2011, p. 302).
The above theoretical discussion on whether there is a positive or negative
relationship between inflation and growth also stems from the debate on how steep
the aggregate supply curve is. This is regarded as a key controversial issue in
macroeconomics (Dornbusch et al. 2008, p. 10; Mankiw & Ball 2011, p. 355). The
Keynesian perspective on this is that in the short run and medium run the aggregate
supply curve is flat or upward sloping and therefore inflation is less likely to be
harmful for growth.19 The neoclassical perception is founded on the long run
aggregate supply curve which is believed to be vertical and therefore output does not
depend on the price level.20
18
Real exchange rate, e, is defined as follows:
e = ne × (P/P*); where ne is the nominal exchange rate, P is the domestic price level, P* is
the foreign price level. So an increase in the domestic price level (rising inflation) causes appreciation
of real exchange rate and therefore makes domestic export more expensive (see for instance Mankiw
& Ball 2011, p. 138).
19
In the short run prices are assumed to be fixed and therefore aggregate supply function is horizontal.
Changes in output, therefore, should not have any impact on price level. In the medium run, aggregate
supply is upward sloping. Since wages are assumed to be sticky, increases in prices would cause real
profit to increase and therefore firms would have an incentive to increase output in response to price
increases. Inflation and growth may move together.
20
In the long run prices and wages are flexible and output is determined by real variables of the
economy and stays at natural level. Because of flexible prices and wages changes in prices causes
proportional changes in the wages, making real profit unchanged. Firms therefore have no incentive to
increase output as a result of changes in prices. One distinction between Keynesian and neoclassical
perspectives is that Keynesians assume sticky wages and imperfect markets. Whereas neoclassical
13
Perhaps the issue of aggregate supply and the trade-off between inflation and growth
is widely examined in the Phillips curve relationship, both theoretically and
empirically.21 The original Phillips curve, in reference to the work of Phillips (1958),
depicts a negative relationship between the rate of growth of the nominal wage and
the unemployment rate.22 Phillips’ empirical work was further strengthened by
another empirical work by Samuelson and Solow (1960) and by Lipsey (1960) which
attempted to provide a theoretical framework to this relationship. The relationship
also implied that policy makers trying to control aggregate demand, using monetary
and fiscal policy, faced a usable trade-off, by which lower unemployment rates could
be obtained at the cost of higher inflation rates and vice versa (Tobin 1987, p. 315).23
When expansionary policies shift the aggregate demand curve, the price level rises.
This reduces real wage and hence induces more employment along a downward
sloping labour demand curve as long as there is unemployment. When full
employment is achieved, such policies will cause only inflation. The negative
relationship between inflation and unemployment can also be explained by using
political economy approach in terms of workers’ bargaining power. When
unemployment is low, workers have greater bargaining power to increase nominal
wages (see Blanchard & Sheen 2009, p. 137) and thus it may lead to an inflationary
pressure.24 Therefore, high employment and growth may lead to higher inflation.25
idea rests on the assumption that prices and wages are fully flexible and market clearing forces would
take output to its natural level always.
21
Nobel Laureate economist George Akerlof (cited in Mankiw & Ball 2011, p. 333) considers the
Phillips curve relationship as, perhaps, the single most important macroeconomic relationship.
22
Although Phillips curve traditionally tries to establish a relationship between inflation and
unemployment rate, it can also be reinterpreted to show a relationship between inflation and output by
linking output to unemployment. Modern day Phillips curve can be expressed as price inflation in
terms of expected inflation, output gap (the difference between actual output and potential output),
and supply shock. The inclusion of expectation is due to the works of Nobel Laureates Friedman
(1968) and Phelps (1967) as explained in the text, while the supply shock is incorporated because of
its importance felt during the oil price crises of the 1970s and a failure of traditional Phillips curve to
explain the inflation output trade-off.
23
According to Mankiw (2001) the trade-off does not imply a stable downward sloping Phillips curve
but rather the effects of monetary policy, the fact that changes in monetary policy takes the two
variables in opposite directions.
24
The bargaining power is expected to increase as competition amongst employers is intensified to
attract workers when unemployment is low.
25
It is in this sense a trade-off exists between inflation and growth since in order to achieve high
growth, low inflationary environment may have to be sacrificed.
14
The theoretical foundation of the Phillips curve relationship was challenged by
Friedman (1968) and Phelps (1967), both working independently. They argue that it
is not correct to think that workers observe prices imperfectly and are not capable of
correctly assessing their real wages in the event of inflation. Assuming adaptive
expectations, they argue that real wages should change in line with changes in the
price level. Therefore, according to Friedman (1968) there may be a short run tradeoff, but no long run trade-off between inflation and unemployment (and therefore
growth). This implies that long run Phillips curve is vertical at an unemployment rate
known as natural rate and demand side policies are, therefore, ineffective in the long
run.26
Incorporating rational expectations arguments, replacing Friedman’s adaptive
expectation, Lucas (1972, 1973) and Lucas and Sargent (1978) went on one step
further in claiming no short run trade-off between the two variables. They argue that
when policy makers try to employ demand side policies systematically it fails to have
any real effect as agents have rational expectations and hence incorporate these
inflation expectations in any contract that they complete.27
The Friedman-Phelps-Lucas approach is predicated on rational expectations
formation by economic agents and natural rate hypothesis.28 In essence this
framework does not believe that there is a trade-off between inflation and growth.
There is, therefore, no gain in terms of higher output and employment by causing
higher inflation. This approach, however, has several opposing views. First, on the
grounds of expectations, Tobin (1971a, 1971b) proposed models incorporating
inflation expectations rather than formation of inflation expectations. His model
showed that the long run Phillips curve is negatively sloped and therefore there is a
permanent trade-off between inflation and unemployment (Palley 2012, p. 10).
Second, the natural rate hypothesis is questioned by some economists, for instance
Ball (1997) and Blanchard and Summers (1988). These economists suggest that
26
This is analogous to long run aggregate supply being at the natural level of output.
Real effect, according to the Lucas Critic, may happen in the short run only if there is an
unexpected demand side policy.
28
According to Mankiw and Ball (2011, p. 353) natural rate hypothesis can be summarised as
fluctuations in aggregate demand that affect output and employment only in the short run but in the
long run the economy returns to the level of output, employment, and unemployment described by the
classical model.
27
15
because of the hysteresis effect recessions can raise the natural rate of unemployment
thus having a lasting damaging impact on the economy.29 Policy intervention using
aggregate demand is also believed to affect the output and employment even in the
long run in this case. In another paper Tobin (1972) argued that positive inflation
helps reduce the natural rate of unemployment because it provides a necessary
mechanism for lowering real wages without nominal wage cuts. Later in another
influential study by Akerlof et al. (1996) also reiterated the importance of it.30 Using
the post-Keynesian approach, Arestis and Sawyer (2004, 2005, 2009), Rowthorn
(1995), Sawyer (2001, 2002, 2005) and Storm and Naastepad (2007) also argue that
natural rate of unemployment can change by changes in labour productivity and in
the capital stock. A rise in the employment according to their argument might not be
associated with an increase in the pace of inflation (see Argitis & Dafermos 2011, p.
1016).
In the context of developing economies, the debate on the role of demand side
policies or inflation and employment (or growth) relationship is not new. Back in the
early 1950s, for example, economists debated this issue within the Indian Planning
Commission. Although they did not use the argument of expectation formation, they
came to a very similar conclusion in favour of a vertical relationship based on two
different arguments. Rao (1952) argued that the Keynesian fiscal multiplier works
only in nominal terms in developing countries. That is, expansionary policies only
generate inflation and no increase in output or employment. He based his argument
on price inelasticities of supply, so that any increase in demand will only generate
inflation – as if the economy is operating at full employment. Dasgupta (1954), on
the other hand, believed that the problem was not due to supply rigidity caused by
various structural problems in the commodity market, but due to subsistence real
wage. That is the real wage in developing countries is already too low, and it cannot
be lowered any more for fiscal policy to work for creating more employment. In
other words, every time prices go up due to expansionary policies, nominal wages
need to be raised so that the real wage does not fall below the subsistence level. As a
29
Hysteresis, as stated in Blanchard and Sheen (2009, p. 670), is the proposition that the equilibrium
value of a variable depends on its history. In relation to unemployment what it means is that a
prolonged period of actual unemployment would raise the equilibrium (natural) rate of
unemployment.
30
Poole (1999) provides a rebuttal on this.
16
result, the employment level – determined by the real subsistence wage – remains
unchanged, but at a higher price level.
The empirical literature also provides a mixed result on the issue of causality, that is,
whether there is unidirectional causality running from inflation to growth or from
growth to inflation, or a bi-directional causality. Milton Friedman states, as noted in
Friedman (1973) and Friedman and Schwartz (1963), that historically all possible
combinations have taken place – economic development in the presence as well as in
the absence of inflation. Relatively earlier empirical works such as Tun Wai (1959)
and Bhatia (1960-61) could not show a meaningful relationship between inflation
and growth. Sidrauski (1967) is amongst the first to show, using super-neutrality of
money, that inflation has no effect on growth. Odedokun (1991), on the other hand,
shows that the Lucas hypothesis of no inflation output trade-off can be rejected in the
case of developing country. Paul et al. (1997) captures this mixed findings in terms
of causality. It finds non causal relationship in 40 per cent of the countries studied,
bi-directional causality in about 20 per cent of the countries, and unidirectional
relationship in about one third of the countries.
The issue of which way the causality runs has been part of an influential debate,
generally known as the Structuralist – Monetarist Controversy since the 1950s,
originating against the backdrop of Latin American situation. The structuralist
argument states that causality may run from inflation to growth as well as from
growth to inflation. Based on Keynesian type theoretical propositions outlined above,
they argue that inflation promotes real economic growth (Baer 1967; Felix 1961;
Georgescu-Roegen 1970; Seers 1962; Taylor 1979, 1983). Dorrance (1964) and
Lewis (1964), on the other hand, explain that inflation may be an inevitable
companion to economic growth which is also supported by Harberger (1963) and
Vogel (1974). In a growing economy, because of the structural bottlenecks, supply
may not be able to keep pace with the rising demand. Inflation as a result is
unavoidable in a developing economy. Bruno (1995) suggests that inflation that
results directly from economic expansion does not create any significant barriers to
expansion. In support of this, moderate inflation is found to be helpful for growth by
Mallik and Chowdhury (2001). They however also warn that growth feeds back into
inflation; thus, it may result into an overheating situation.
17
The causality runs from inflation to growth, negatively, is argued by the monetarist
view, primarily based on Friedman’s hypothesis that inflation creates uncertainty. A
number of studies such as Grier and Tullock (1989), Kormendi and Meguire (1985),
and Jung and Marshall (1986) assume that causality runs from inflation to growth.
Grier and Perry (2000) and Tommassi (1994) show that inflation uncertainty has a
negative impact on growth. However, Dotsey and Sarte (2000) support a positive
association in this regard. Stockman (1981), whose work finds empirical support
from Zhang (2000), shows that in an economy with cash in advance constraint on
consumption and investment, expected inflation reduces the demand for real balances
thereby negatively affects growth.
The causality between inflation and growth perhaps is not uniform because of the
non-linear nature of the inflation growth relationship. Fischer (1993) is amongst the
first to examine the possibility of non-linearity in the relationship. In the case of a
non-linear relationship, the interest is to see if there is a threshold level up to which
inflation and growth are positively related, but beyond which the relation switches
sign and becomes negative. In recent years, research interest has paid attention to
finding such a threshold level. Empirical findings of the studies in this respect also
provide different threshold levels for cross country as well as country specific cases.
In the case of cross-country studies, Sarel (1996) and Burdekin et al. (2004) find a
single digit threshold level while other studies such as Khan and Senhadji (2001),
Kremer et al. (2009), Pollin and Zhu (2006), and Sepehri and Moshiri (2004) find the
threshold level between 11 per cent and 18 per cent. In an influential study, Bruno
and Easterly (1998) argue that the case for growth effects of low to moderate rates of
inflation remain very ambiguous. They find that only in the case of discrete high
inflation, beyond 40 per cent, inflation becomes harmful for growth.
In the country-specific cases, studies such as Chowdhury and Ham (2009), Kheir-ElDin and Abou-Ali (2008), Mubarik (2005), Phiri (2010), and Salami and Kelikume
(2010) suggest a threshold level between 8 per cent to 15 per cent. While other
studies such as Ahmed and Mortaza (2005) are more on the conservative side and
suggest a threshold level around 6 per cent.
18
The differences in threshold point for developing countries can be due to a number of
reasons including country-specific circumstances and the stage of development an
economy is in, for instance, initial level of output and growth rate. In this connection,
Drukker et al. (2005) in a panel study shows that if the initial inflation rate is below
19.16 per cent, increases in inflation do not have statistically significant effect on
growth. However when initial inflation is above 19.16 per cent, further increases in
inflation lead to a decrease in long run growth.
1.5 The Research Objectives of the Thesis
In the light of the above discussion the present study is motivated to examine
macroeconomic policies of low inflation in developing countries. The three most
fundamental questions that we come across are as follows
Research question 1: Is there a threshold level of inflation at 5 per cent for the Asian
developing countries beyond which inflation is harmful for economic growth?
Research question 2: Does the threshold level vary depending on the level of
development within the Asian developing countries with poorer countries tend to
have higher threshold?
Research question 3: Is there a consistency between the need for a change in the low
inflation policy suggested by leading economists and country-policy reports by the
IMF?
The investigation is expected to shed some light on a number of important issues
such as in a growing and dynamic economy whether moderate inflation is perhaps
required for efficient reallocation of resources and for faster structural change to take
place. Restrictive policies, overly concerned with keeping inflation at low-single
digits, may stall economic growth and plunge the economies into stagnation and
delay the progress in terms of poverty.
19
The critical review and the empirical investigation of the study take place in five
different chapters. Chapter 2 provides a detailed content analysis of the Article IV
country-specific consultation reports prepared by the IMF which acts as a benchmark
for their policy advice for these countries. This is carried out in the case of selected
developing countries of Asia. We have selected 12 countries from South and
Southeast Asia including China. The countries within this region are of special
interest to us because of their recent economic performance. Besides, there are
enough variations within the selected countries in terms of socioeconomic
development, allowing us to determine whether policy advice on inflation and
growth by the IMF varies according to country-specific circumstances. We are also
interested to find out the nature of policy advice in the aftermath of global crisis
2009. So the selection of counties is also dictated by that availability and release of
country reports by the IMF around the time of 2009-2010. The list of countries for
which the reports are reviewed are Bangladesh, Bhutan, Cambodia, China, India,
Indonesia, Lao PDR, Malaysia, Maldives, Nepal, Pakistan, and The Philippines.
Chapter 3 takes a look at the cross-country evidence based on the existing literature.
It provides a critical review of the major recent works relating to the growth-inflation
nexus. Chapter 4 provides a critical review of the country-specific literature for
Asian developing countries under investigation. Here, again we have paid attention
to 15 countries from South and Southeast Asia. However, the selection depends on
the availability of literature on these countries. The countries are Bangladesh,
Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Maldives, Nepal,
Pakistan, The Philippines, Sri Lanka, Thailand, and Vietnam. Chapter 5 carries out a
cross-country panel study to reveal findings relating to the research questions. A list
of 14 countries has been selected based on the availability of data to perform the
empirical analyses. These countries are Bangladesh, Cambodia, India, Indonesia, Lao
PDR, Malaysia, Pakistan, The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz
Republic, Papua New Guinea, and Tajikistan. Our selection of countries shows
enough variations and a comprehensive picture about the developing countries of
Asia. We have excluded the Arab countries intentionally because we believe their
history and socioeconomic development are quite different from the rest of the Asian
countries. Chapter 6 makes an attempt to empirically investigate the issues in the
context of a particular country, Bangladesh. The purpose of the time series analysis
in a country-specific case is to strengthen the case we examine.
20
Chapter 2
The IMF and the Policy of Low Inflation: A Review of
Article IV Consultations for Selected Developing Countries
of Asia
2.1 Introduction
The discussion of Chapter 1 notes the tendency of macroeconomic policies in
developing countries emphasising strongly on keeping inflation at a low single digit
level. This is primarily spearheaded by the fact that as recipients of the IMF loan,
developing countries are required to focus on attaining macroeconomic stability by
keeping inflation low. As explained in the discussion of Chapter 1, the focus of
policy on reining in inflation is based on the assumption that stabilisation will
ultimately result in long term sustainable economic growth, employment generation,
and poverty alleviation. What is also important, as noted earlier, is that the IMF
seems to assess this macroeconomic stability based on a country’s ability to achieve
and maintain certain nominal targets. In the context of inflation the IMF policy
guideline, explicitly or implicitly, tends to suggest a target of 5 per cent or below
irrespective of country-specific circumstances.31 For instance, an inflation target of 5
per cent or less was suggested to 22 out of 32 programme countries between 1995
and early 2007 (Goldsbrough, Adovor & Elberger 2007, Table 1, p. 5). According to
IMF’s Independent Evaluation Office (IEO 2007) an inflation target of less than 5
per cent was suggested to 29 Sub-Saharan African countries during the 2000s.
Evidence from the cross-country literature, discussed in Chapter 1, shows that the
threshold levels of inflation beyond which inflation negatively affects growth vary
according to the level of development. Generally, poorer countries tend to have a
higher threshold level and the harmful effect of inflation on growth for developing
countries is found to be well above 5 per cent.
31
In addition, as part of the stabilisation programme, nominal targets for fiscal deficits at 5 per cent
(but preferably primary surplus), debt GDP ratio at 40 per cent, and a sustainable current account
balance are suggested. These targets are also expected to be helpful in containing inflation at a low
level.
21
As observed earlier that there has been a rethinking about this stereo-type policy
suggestion in the wake of the global financial crisis of 2007–2008 and the subsequent
Great Recession of 2008–2009 it led to.32 As mentioned in Chapter 1, a former
Managing Director of the IMF argued the need for a “wholesale re-examination of
macroeconomic policy principles” and questioned the pre-crisis advice of “keeping
inflation low and stable was the best way to secure optimal economic
performance”.33 In addition, the current Director of Research at the IMF points out
that the crisis “has exposed flaws in the pre-crisis policy framework”–particularly
about one target, that is low and stable inflation, and one instrument, the policy rate,
to achieve it (Blanchard, Dell'Ariccia & Mauro 2010). In short the orthodox
approach sponsored by the IMF, that has narrowed the goals and tools of
macroeconomic policy, has been questioned by its own key figures within the
organisation.34
Against this backdrop, the key objective of this chapter is to find out whether the
recent shift in the thinking process by the heads and the research staff of the IMF has
any reflection on the policy advice in practice. It provides an in depth examination of
the nature of IMF’s policy advice in selected developing countries of Asia. The
chapter also attempts to seek the rationale behind keeping inflation at a low single
digit level by looking at the historical evidence on country-specific cases. The
methodology we use in this chapter is as follows. In order to investigate the nature of
IMF’s policy advice we provide content analysis of the IMF Article IV staff
consultation reports in the aftermath of the global crisis of 2007-2008. These reports
contain IMF’s recommendations to the individual countries as part of its surveillance
32
There has been in fact a triple crises, energy and food price shocks included, as noted by
Chowdhury and Islam (2010), due to oil price shock of 2007 and international food price hike around
that time. As developing countries are particularly prone to such supply shocks it is important to take
this into consideration as well.
33
See the opening remarks by Dominique Strauss-Kahn, at the IMF conference on ‘Macro and
Growth Policies in the Wake of the Crisis’, Washington D.C., March 7, 2011, available via the
internet at http://www.imf.org/external
34
In fact, raising the concern about the IMF’s international monetarism approach that is not explicitly
concerned about economic growth (see Fischer (1987, p. 165) and Fasano-Filho (1996, p. 135)), is not
new. In the mid-1990s the then Managing Director urged that the IMF should help its member
countries to achieve conditions for high quality growth that brings lasting full employment and
poverty reduction (Fasano-Filho 1996, p. 136). In 1999, the IMF launched the Poverty Reduction and
Growth Facility (PRGF) the objective of which was to make poverty reduction and growth more
central to lending operations in its poorest member countries (Selassie et al. 2006, p. vi). Nevertheless,
the basic assumption that stable and low single digit inflation is both necessary and sufficient
conditions persisted in the IMF’s policy advice.
22
responsibilities. These country reports are released periodically often in a 12 or 24month-cycle. We select the time-frame 2009-2010 to evaluate the policy
prescriptions in the aftermath of the global crisis. Reports of 12 Asian developing
countries released, and therefore available in public around that time, are selected.
These countries are Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Lao
PDR, Malaysia, Maldives, Nepal, Pakistan, and the Philippines. We highlight the
staff appraisal on growth and inflation outlook and analyse the recommendations on
monetary and fiscal policy in view of the country-specific circumstances. The
analysis is aided by the time series data on growth and inflation to reflect the medium
and long term picture as well as forecasts on future trends. The detailed content
analysis with the help of historical data seeks to explain whether the medium and
long-run trends provide a rationale for targeting low single digit inflation irrespective
of country-specific circumstances.
The rest of the chapter is divided into three sections. Section 2.2 attempts to provide
a review of recent related literature. Some of these studies are mostly concerned with
the policy advice of an inflation target of 5 per cent or less in the case of developing
countries. However, majority of these studies cover pre-crisis period as the research
on this topic in the post crisis period is still very limited. Section 2.3 provides an indepth content analysis of the country-specific reports prepared by the IMF staff for
the Article IV consultation in the context of 12 countries selected by this chapter.
The aim is to examine the extent to which the revised position of the IMF research
staff has been translated into policy recommendations in the post crisis era. This is
timely and appropriate since not much research has been done on this topic so far.
Finally, section 2.4 draws conclusions on the IMF’s policy stance on inflation based
on the literature reviewed and historical country-specific experiences presented in the
previous sections. It tries to provide an answer whether the policy advice suggested
in the Article IV consultation reports is consistent with the historical experience and
the findings of the research done by the IMF’s own staff and others.
2.2 A Review of Related Literature
Existing literature providing a post crisis analysis on the IMF policy stance
particularly in respect of inflation in developing countries is inadequate. Table 3.1
23
provides a summary of the studies selected to be reviewed in this section. Perhaps the
only two comprehensive studies in the case of developing countries involving a
content analysis using the Article IV consultation staff reports are Roy and Ramos
(2012) and Anwar and Islam (2011). The study by Roy and Ramos (2012) reviews
the 2010 reports for 26 developing countries to assess whether IMF’s policy
recommendations are based on an understanding of country-specific circumstances
and whether they reflect the shift in the thinking as proposed by the senior members
and the research works carried out by the IMF. The study selects four main areas for
assessment: exchange rate, inflation, fiscal consolidation, and employment and other
social policies. In relation to the recommendations on inflation the study finds little
evidence of policy shift in line with the need for a change suggested above. There
has been no cost benefit analysis to support recommendations for reducing inflation
and recommendation still focuses on the use of monetary policy only, regardless of
the source of inflation (Roy & Ramos 2012, p. 20). One drawback of the study is that
it limits itself to content analysis only and does not provide any empirical (historical)
evidence in support of its conclusion. This chapter aims at fulfilling this gap by
examining whether there is any relationship between the IMF’s advice and historical
median values of inflation and growth in section 2.3.
Table 2.1: Inflation Targets and IMF Policy, Selected Recent Studies
Studies
Countries
Period
Findings Relevant to This Study
Roy and Ramos
26
2010
Policy recommendations do not reflect IMF’s
(2012)
developing
revised position and in several cases are not
countries
appropriate due to country specific
circumstances.
Anwar and Islam
12 IT and 12
1961 –
Inflation targets – on average less than 5 per
(2011)
non-IT
2009
cent – adopted by the IT regimes are too low,
developing
perhaps influenced by the declining trends of
countries
the 2000s, and not in accordance with historical
trends. The content analysis does not provide a
clear evidence of change in policy advice.
Goldsbrough,
Adovor, and
32 countries
1995 –
22 cases out of 32 arrangements targeted
2007
inflation rate at or under 5 per cent. Conclusion
24
is that a number of programs went beyond the
Elberger (2007)
limit of theoretical and empirical claim that
pushing inflation below 5 per cent is harmful.
IEO (2007)
Chowdhury (2006)
29 Sub-
1999 –
Despite the inconclusive nature of empirical
Saharan
2005
relationship between inflation and growth as
African
acknowledged by the IMF staff, an inflation
developing
target of less than 5 per cent has been suggested
countries
to these countries.
8 Asian
1970 –
Both very low and high inflation are harmful
developing
2002
for growth and poverty reduction. An inflation
rate between 3 and 5 per cent may run the
countries
danger of deflation leading to a stabilisation
trap. Moderate inflation in the range of 10 to
15 per cent is found to stabilise employment.
The IMF study by
35
Selassie (2006)
15
2000 –
On balance it supports the use of single-digit
developing
2003
inflation targets, however suggesting caution
countries
on setting inflation below 5 per cent.
Note: IT stands for inflation targeting.
An influential study providing a critique to the IMF’s post-crisis policy stance
favouring low inflation strategy is Anwar and Islam (2011). Against the backdrop of
a need for “wholesale re-examination” of the IMF policy, the study investigates how
appropriate the target of low single-digit inflation is, to promote growth and
employment in developing countries. The study finds that amongst the 12 developing
countries, currently adopted inflation targeting (IT), the median inflation target is
4.25 per cent, below 5 per cent (see Table 3.2). The individual country targets are
also at or below 5 per cent except for Ghana and Turkey. The targets set for the
countries, as the study shows, are not derived or consistent with the long run
historical trend of the countries. It argues that these inflation targets appear to be
influenced by the declining trend in inflation of the 2000s. Inflation in general came
down in that decade throughout the world and as such a target based on a temporary
phenomenon is questioned by the study. Moreover, this declining trend could be a
35
This study is often referred to as IMF (2006) by others, although the usual disclaimer applies stating
that the views expressed in the paper are that of the authors and do not necessarily reflect the IMF (see
p. vi).
25
result of the dominance of inflation targeting and inflation first policies pursued since
the 1990s.
Table 2.2: Inflation Targeting Countries (Emerging and Developing Countries) 2011
Inflation Targeting Country
Median Target (percentage)
Armenia
4
Brazil
4.5
Chile
3
Columbia
3
Czech Republic
2
Ghana
9.2
Guatemala
5
Hungary
3
Indonesia
5
Mexico
3
Peru
2
Philippines
4
Poland
2.5
Romania
3
Serbia
4.5
South Africa
4.5
Thailand
1.75
Turkey
5.5
Median inflation target (excluding economies in transition:
4.25
Armenia, Czech Republic, Hungary, Poland, Romania, and
Serbia, 12)
26
Median inflation target (all developing countries and economies
3.5
in transition, 18)
Source: Adapted from Anwar and Islam (2011, Table 1, p. 3).
Based on the content analysis of recent Article IV consultation reports for 19
developing countries, the Anwar and Islam (2011) find evidence – similar to Roy and
Ramos (2012) – of IMF’s preference towards low single digit inflation mostly
around 5 per or below, with no clear rationale for it. Anwar and Islam (2011) also
argue that implementation of IT in the presence of supply shocks is challenging in
the case of developing countries. In addition to these findings, Anwar and Islam
(2011) show no significant achievement made by the IT adopted developing
countries in terms of labour productivity, vulnerable employment, working poverty,
and growth compared to their non-IT counterparts. In short, the study provides an
important conclusion that the argument of low inflation being beneficial for growth
is weak.
The studies, immediately preceding the crisis, observe a strong preference of
inflation targets towards a rate of 5 per cent or less. Goldsbrough et al. (2007) and
IEO (2007) reveal that countries with IMF supported programmes had to target an
inflation rate less than 5 per cent.36 The study by Selassie et al. (2006), carried out at
the IMF, also support a single digit target, although the authors note that a target less
than 5 per cent should be pursued with caution as it may entail a loss of output (p.
24). Chowdhury (2006) reviews post 1997-1998 Asian crisis monetary policy in
selected Asian countries. Based on post-Asian crisis economic performance,
Chowdhury (2006) warns that low inflation, in as much as high inflation, can be
harmful for growth. Too low inflation may lead to a stabilisation trap, a situation of
low inflation and insufficient growth for poverty alleviation. Goldsbrough et al.
(2007) think that some of the IMF programmes suggested too low an inflation target
in the respective countries. The binding constraint of conditionality is also revealed
by the empirical analysis of IEO (2007). It states that country macroeconomic
conditions, as proxied by the inflation rate, are the main determinants of whether and
to what extent the IMF programmes permit the spending of incremental aid to Sub36
IEO (2007, p. 18) states that maintaining inflation in the low single digits, 4 – 6 in general, is an
important feature of PRGF-supported programmes of the IMF.
27
Saharan African countries (p. 9). The power to spend the anticipated aid increases
has been strongly biased towards countries with inflation rate below 5 per cent (in
which case they were allowed to spend 79 per cent as opposed to only 15 per cent
where inflation rate was higher). In summary, the pre-crisis period shows a clear
inclination towards targeting a low inflation rate at or below 5 per cent by the IMF
policy in the context of the developing countries. It is important to note that despite
this, real GDP growth remained short of 7 per cent which is considered necessary to
meet the Millennium Development Goal (MDG) target of halving poverty by 2015
(see evaluation by Selassie 2006, p. 8).
In sum, the above review shows that post-crisis policy advice of the IMF continues to
be the same as the pre-crisis advice and does not show any change despite IMF’s
senior officials’ calls and overwhelming research findings pointing to the need for a
change.
2.3 A Review of the IMF Article IV Staff Consultation Reports in Selected
Developing Countries of Asia
The discussion of the above section reveals the prevalence of low inflation policy
strategy in general for developing countries, notwithstanding the suggestions made
by the IMF’s own and other leading economists. The discussion now turns to an
investigation in the case of 12 selected developing countries of Asia. The content
analysis is more extensive unlike the existing studies reviewed in the sense that it
tries to analyse the specific recommendations on monetary and fiscal policy in
relation to inflation and economic growth supported by the trends revealed by the
time series data on each country. Besides, some of these country reports have not
been reviewed in the existing literature.
The analysis of country-specific reports, in this chapter, is carried out in the
following manner. We have selected 12 countries which are Bangladesh, Bhutan,
Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Maldives, Nepal, Pakistan,
and the Philippines. The selection of these developing countries in Asia shows
enough variations in the country-specific circumstances and the levels of economic
and social development. Such variations would help us understand if the country28
specific circumstances matter in explaining the historical trends in growth and
inflation and whether the IMF policy advice varies accordingly. For instance, in the
list we have China, the largest in Asia in terms of size and population with
predominantly a command economy where markets are allowed to function within a
tight regulatory environment; Bangladesh, a geographically small, but densely
populated country with a population of 160 million and growing middle class. It
initially followed a socialist path, but rapidly moved into a more market oriented
system. The selection also includes Nepal, a land-locked country emerging out of
social conflicts.
The country consultation reports of these countries in the years 2009 and 2010 are
selected (depending on their availability). This is to capture the policy advice around
the time of the crisis. To provide some empirical support to the content analysis on
each country the data on inflation and growth are presented in a table. In each case,
the mean values of 2009 and 2012/2013 are shown to reflect the current and forecasts
on inflation and growth. In addition, long-run median and decadal median values
between 1960 and 2009 are included to reveal the pattern of historical experience on
growth and inflation in each country. The median values are used to avoid outliers
resulting from extreme episodes of inflation. The data are gathered from the standard
sources of the World Development Indicators of the World Bank and International
Financial Statistics and World Economic Outlook of the IMF.
The country summaries are provided in the following subsections.
2.3.1 Bangladesh
Table 2.3.1: Average Growth-Inflation Figures in Bangladesh
Country
Bangladesh
Indicators
Long run
Decadal median
median
2009
Growth
5.58
2012
5.9
*
2013
6.4
*
1971-2009
4.72
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
-
3.27
3.42
4.78
5.77
29
Inflation
5.42
10.4
7.9
8.40
-
16.60
10.25
5.75
6.22
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook. The figures for the decade 1960s are not reported as Bangladesh was a part of Pakistan
during the time.
Long-run growth performance in Bangladesh, based on historical evidence, remains
well below the required rate of 8 per cent to graduate to a middle income country by
2021 and to have a significant dent on poverty.37 The long-run median growth is only
4.72 per cent (see Table 3.3.1) and it seems to be held back by infrastructural
bottlenecks (see IMF 2010a, p. 15). Despite the fact that inflation remained below 6
per cent in 2009, the consultation report (IMF 2010a) warned that monetary policy
was “too accommodative” for domestic conditions and preventing an increase in
inflation is an “immediate policy concern.” This perhaps came from the fear that
inflation would reach a double digit figure in the near future, 10.4 per cent in 2012.
This advice was offered despite the fact that the inflationary pressure was due mainly
to food and fuel price rises in the international markets, exchange rate depreciation
(from around 70 taka a dollar to about 83 taka a dollar) and the removal of subsidies
or administrative adjustment of prices upward. Although the report identified that
external supply shocks such as international food and commodity prices were
contributing factors to inflation it suggested for employing tight monetary policy.
The IMF staff suggested that the central bank should take “a pre-emptive and bold
action” to contain “signs of a pickup in prices” (p. 15). The higher interest rate is
believed to be a “small price to pay to prevent a harmful acceleration of inflation” (p.
15).
37
A recent report by the World Bank (World Bank 2012) suggests that the country needs to grow at 8
per cent to become a middle income country by 2021. The report notes that the decline in population
growth is impressive, from nearly 3 per cent per annum in the 1970s to 1.3 per cent in the 2000s, and
increased labour productivity has helped to achieve the current growth rate. However, to achieve
middle income country threshold of US$1450 GNI per capita by 2021 from Bangladesh’s current
US$784 per capita, the required growth rate in GDP is 8 per cent assuming share of remittances is 5
per cent and a constant real exchange rate (ibid p. 4).
30
This fear of inflation going out of hand was not justified, given the inflation history
of Bangladesh. Table 2.3.1 shows that the inflation in 2009 was well below the longrun historical inflation at 8.4 per cent. The figure was also lower than the decadal
medians for 1990s and 2000s. The forecast values of inflation do not show signs of
runaway inflation either (inflation is expected to go down in 2013; see Table 2.3.1).
On the other hand, growth performance was seen by the report as “remarkably well”
in the face of global recession (p. 14). Fiscal conservatism of the government was
said to be responsible for this and maintaining “fiscal prudence and sustainability”
was advised to unleash Bangladesh’s potential (p. 15). However, one wonders how
fiscal conservatism is going to resolve the country’s huge infrastructure shortage
which is also a contributory factor for higher inflation in addition to a major obstacle
to growth. So far the public-private partnership (PPP), which is generally touted as a
solution, is not showing much promise. The PPP experience in the energy sector does
not auger well when shifting contingent liabilities to the government is a major cause
of deteriorating fiscal position.
2.3.2 Bhutan
Table 2.3.2: Average Growth-Inflation Figures in Bhutan
Country
Bhutan
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1980-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
6.51
7.0
9.9
6.75
-
-
7.50
5.33
7.18
Inflation
4.36
8.4
7.3
7.03
-
-
9.90
9.74
4.48
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
31
Bhutan, except for the 1990s, shows strong growth performance at around 7 per cent
and growth is expected to reach nearly 10 per cent in 2013 (see Table 3.3.2). On the
other hand, inflation in 2009, at 4.36 per cent, remained well below its long-run
median, at 7.03 per cent as well as the common 5 per cent benchmark of the IMF.
Inflation in Bhutan is driven by inflation in India as Bhutan’s currency is pegged to
the Indian currency. This is also evident from the historical median-inflation for both
the countries, at around 7 per cent. The country report on Bhutan (IMF 2009a, p. 8)
praises this robust growth without inflationary pressure. The rapid credit growth is
believed to help faster private sector growth and is expected to result in higher
productivity in the country.
Although inflation is stable and future inflation is expected to remain close to its
historical median (see Table 2.3.2) the staff appraisal warned of a potential
overheating in the economy. This is, as the report suggests, due to “spill-overs from
the hydropower and development spending as well as rapid credit growth, financial
sector vulnerabilities, and concerns about debt sustainability” (p. 9). The
government, according to the report, should be careful about fiscal management as
the budgeted fiscal deficit for 2009-2010 exceeds the government’s implicit policy to
limit the deficit under “5 per cent of GDP” (see ibid., p. 10). In line with this, the
staff felt that a near-term “tightening bias” is necessary to ensure macroeconomic
stability.
However, it is not clear if public investment in hydropower and development
spending are growth promoting, how debt can become unsustainable or the economy
can overheat. Instead of advising for a tightening bias, the advice should have been
on ensuring spending on right sectors with greatest growth potential and on revenue
collection by enhancing progressivity of the tax structure and efficiency of tax
administration. If this can be done, the debt can be repaid from higher growth and
consequent revenue dividends. Thus, the IMF’s advice seems short-termist and
follows from the belief that macroeconomic stability in a narrow sense is both
necessary and sufficient conditions for growth and development.
32
2.3.3 Cambodia
Table 2.3.3: Average Growth-Inflation Figures in Cambodia
Country
Cambodia
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1990-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
-1.89
6.2
6.4
7.73
-
-
-
5.86
8.16
Inflation
-0.66
4
3.6
3.92
-
-
-
4.00
3.57
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
A strong growth performance has been registered by the Cambodian economy for
several years, the 2000-2009 average standing at 8 per cent (see Table 2.3.3). The
report on Cambodia (IMF 2009c, p. 3) acknowledges the country’s strong growth
performance and significant reduction in poverty.38 But the global recession seems to
have buffeted the economy causing growth to plummet to -1.89 in 2009. At the same
time Inflation was negative in 2009 and forecasts also show that it would remain
below 5 per cent in the near future. The decline in both growth and inflation reveals
that expansionary macroeconomic policies were required to boost aggregate demand
for growth to recover.
Yet, the staff-report saw an upside risk due to “overly expansionary” fiscal stance (p.
19), exerting “pressure on inflation” (p. 3), and undermining “stability” (p. 10).39 The
report, however, admitted that fiscal easing in the face of weak demand in 2009 was
appropriate but raised concern that 2009 fiscal deficit was expected to widen to 6.75
38
According to the country report (see p. 4) poverty level went down from 50 per cent in the mid1990s to 30 per cent in 2007.
39
In fact the report underscores the need to keep the budget deficits within 5.75 per cent of GDP
which it believes will be “appropriately accommodative in providing adequate space for development
objectives, but eliminating the domestic financing requirement and setting the stage for medium-term
fiscal consolidation” (p. 11).
33
per cent of GDP against the target of 4.25 per cent (p. 10). The report was also
against further easing of monetary policy particularly lowering reserve requirement.
It is “neither warranted based on monetary conditions nor desirable from a prudential
perspective”, according to the report (see p. 14). However, the report does not offer
any advice as to how to support recovery. It displays unwavering faith in
macroeconomic stability in terms of inflation below 5 per cent and budget deficits
below 3 per cent to deliver growth and economic recovery.
2.3.4 China
Table 2.3.4: Average Growth-Inflation Figures in China
Country
China
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
8.8
8.2
8.8
8.84
9.84
7.32
9.53
9.21
9.53
Inflation
-0.70
3.3
3.0
2.15
-
1.05
6.25
4.94
1.31
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
Fiscal stimulus and loosening of monetary policy in the face of global recession have
played an instrumental role in mitigating the effects of the shocks in the Chinese
economy, the IMF report claims (see IMF 2010b, p. 4). According to Table 2.3.4,
there does not seem to be a tendency of inflationary pressure amidst this strong
growth performance. Inflation was in negative territory in 2009 and would remain
around 3 per cent in the upcoming years. Despite this, the country-report raised
concern about inflationary pressure in the period ahead because of rapid expansion of
monetary aggregates and credit growth (ibid., p. 8). The Chinese authority however
34
opposed the view of raising nominal interest rate at this point as they believe that the
inflation outlook was still benign (p. 8).
2.3.5 India
Table 2.3.5: Average Growth-Inflation Figures in India
Country
India
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
8.71
6.9
7.3
5.47
6.08
2.45
5.44
5.69
8.03
Inflation
10.87
8.2
7.3
7.16
3.58
5.99
8.76
9.59
4.32
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
A strong growth performance, at about 8 per cent, in recent decade has made India a
major emerging country of the world. According to the staff-appraisal, the economy
has rebounded ahead of most countries in the world but inflation is intensifying (IMF
2010c, p. 3). Table 3.3.5 shows that inflation in 2009 was at 10.87 per cent but was
expected to come down and remain close to its historical long-run median around 7
per cent. Still the report identifies “elevated inflation” as a major risk which could
“stall the recovery” (ibid., p. 4). An exit strategy from the accommodative policy by
reducing fiscal deficits and gradually tightening monetary policy to anchor inflation
was recommended. In addition, the government was advised to work under a
framework anchoring debt target to reduce it at 60-65 per cent of GDP by 2015 (see
p. 3). To achieve this target, the report suggested that more privatisation and
reduction in public sector’s claim on resources were required (p. 3). It is interesting
to note that the report also observed that “there is a risk that private demand may not
be broaden enough to carry the growth momentum” (p. 5).
35
2.3.6 Indonesia
Table 2.3.6: Average Growth-Inflation Figures in Indonesia
Country
Indonesia
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
4.47
6.1
6.6
5.96
2.81
7.71
6.54
7.14
4.91
Inflation
6.38
6.2
6.0
10.46
128.84
14.30
9.38
8.97
8.34
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
Growth in Indonesia was moderate at 4.47 per cent in 2009. In fact, the median
growth between 2000 and 2009 was 4.91 per cent (see Table 2.3.6) and was about 2
percentage points lower than the median figures of the previous three decades. The
economy has managed to grow at around 7 per cent, on average, in the 1970s, 1980s,
and 1990s. The relatively poor performance in the 2000s is due to the fact that
Indonesia was hard hit by the Asian Currency Crisis of 1997. The impact of the crisis
is reflected in its growth performance in the following decade. The country appears
to find it difficult to regain its past robust growth path. On the other hand, inflation
was around 6 per cent and is expected to remain at that level in 2012 and 2013 (see
Table 2.3.6). According to Table 2.3.6, this inflation figure does not seem to impose
any threat. The figure was still at least 2 percentage points less than the decadal
median values since the 1980s. The Indonesian economy has the experience of
growing faster with higher inflation rates (see the decadal median values of the
1980s, 1990s, and 2000s).
The country report on Indonesia (IMF 2009b, p. 11) found the fiscal stimulus and
monetary easing in the aftermath of the global financial crisis as appropriate as it has
supported the “weaker domestic demand.” It is important to note that Indonesia,
36
before the fiscal stimulus package for 2009, followed several years of prudent fiscal
management and achieved a primary fiscal surplus of about 2 per cent of GDP per
year (see ibid., p. 6). This is the reason why the report was also positive about the
fiscal stimulus since it would not hamper the medium term public debt consolidation.
Although inflation figures in Table 2.3.6 do not appear to be alarming, the staffappraisal suggested that the central bank should be more cautious. It argued that
there was “ample stimulus in the pipeline” (p. 19), in the form of interest rate cuts
and “abundant liquidity in the banking sector” (p. 10), “leading to higher credit
growth and inflationary expectations” (p. 10). In addition, referring to an estimated
Taylor rule40 the report indicated that the central bank’s “policy stance has generally
tended to have an expansionary bias over time” (p. 10). Therefore, it underscored a
need for a concerted effort “based on a more credible and objective inflation
targeting framework to consistently lower inflation and guide inflationary
expectations towards a medium-term target range of 3-4 per cent” (p. 11). This is
believed to “enhance policy credibility and lower economic costs” (p. 11).
2.3.7 Lao PDR
Table 2.3.7: Average Growth-Inflation Figures in Lao PDR
Country
Lao PDR
Indicators
Long run
Decadal median
median
2009
2012*
2013*
1980-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
7.21
8.4
7.1
6.07
-
-
4.77
6.19
6.86
Inflation
0.03
6.7
5.3
10.63
-
-
61.33
16.51
7.72
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
40
Taylor Rule was developed by John B. Taylor of Stanford University in the early 1990s (see Taylor
1993). It provides a guideline for the central bank on how to set the short term real interest rate in
order to stabilise the economy and achieve inflation target. The rule can be written as: r = 0.01 + 0.5y
+ 0.5π, where r is the real interest rate set by the central bank, y is the percentage deviation of real
GDP from a target, and π is the inflation rate.
37
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
As a transitional economy Lao PDR has performed well in recent decades with
growth remaining above 6 per cent on average (see Table 2.3.7). Acknowledging
this, the consultation report on the country identified that the expansionary policies
were responsible for this robust growth particularly in the face of the global recession
(see IMF 2009d, p. 3). According to the report, inflation was expected to remain low
and stable assuming no significant rise in commodity prices (p. 3). Table 3.3.7
reveals that indeed inflation was almost zero in 2009 and forecast figures were well
below the country’s historical median inflation at 10.63 per cent. Yet, when it comes
to policy advice the staff-appraisal took the typical stance. It concluded that “overly
expansionary fiscal and credit policies pose a risk to macroeconomic stability” (ibid.,
p. 3). The authorities have been advised of a “prompt and determined tightening of
monetary and fiscal policy” (p. 15). The report feared that continued credit growth
“could fuel inflation down the road.” It was therefore imperative, as the report
suggested, to send strong signals to the banks to check credit growth by significantly
raising required reserve ratio (p. 3).
2.3.8 Malaysia
Table 2.3.8: Average Growth-Inflation Figures in Malaysia
Country
Malaysia
Indicators
Long run
Decadal median
median
2009
2012*
2013*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
-1.72
4.4
4.7
6.81
7.08
7.72
6.38
8.72
5.62
Inflation
0.58
2.7
2.5
2.81
-0.10
4.07
3.25
3.51
1.67
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
38
Malaysia posted negative growth in 2009 (see Table 3.3.8) and the country report
stated that “forceful counter-cyclical policies” have helped the country to emerge
from “the global recession with strong forward momentum” (see IMF 2010d, p. 4
and 19). The country’s growth forecasts, around 4 per cent, were still well below it
historical standard, at 6.81 per cent. There was also no sign of overheating as
inflation was expected to remain at about 2 per cent. Therefore, the full recovery did
not seem to have taken place. Yet, the IMF report stated that the policy of fiscal
consolidation and normalisation of monetary policy should be underway. The staffappraisal suggested that raising policy rate after aggressive loosening in 2009 was
consistent with the Taylor rule calculations (ibid., p. 10). The staff is concerned
about “side-effects of abnormally low interest rates” (p. 10). Higher interest rate was
believed to send a signal against “investor’s complacency in the pricing of risks after
a year and a half of loose monetary conditions” (p. 10).
2.3.9 Maldives
Table 2.3.9: Average Growth-Inflation Figures in Maldives
Country
Maldives
Indicators
Mean
Long run
Decadal median
median
2009
2012*
2013*
1990-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
-2.32
4.4
3.5
6.97
-
-
-
9.01
5.98
Inflation
3.98
11.5
8.3
4.73
-
-
-
5.84
2.51
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
The external shocks due to the global recession have prompted a severe decline in
economic activity in Maldives and growth dipped by about 4 per cent reaching at 2.32 per cent in 2009 (see IMF 2010e, p. 3 and Table 2.3.9). Future economic
39
outlook of the economy also indicated that growth would be modest at around 4 per
cent in the years 2012 and 2013, well below its average median value, 6.97 per cent,
since the 1990s (see Table 2.3.9). Consistent with a slowing economy, inflation
remained below 4 per cent in 2009; but showed signs of increase in 2012 and 2013
(Table 2.3.9). This could be due to supply shocks resulting from a rise in
international fuel prices and domestic electricity tariffs (IMF 2010e, p. 3). In short
the key problem is that the country is in recession with problems arising mainly from
supply-side shocks. Despite this grim prospect of growth and slow recovery, the
country report on Maldives noted that the crisis has led to “an unsustainable fiscal
expansion” turning it into “a serious near-term risk to macroeconomic stability”
(ibid., p. 3). Monetary policy, on the other hand, according to the staff, has been
constrained by fiscal dominance because of the government borrowing without limit
from Maldives Monetary Authority (p. 6). It seems keeping inflation at around 3 per
cent was viewed as the benchmark for attaining macroeconomic stability by the
report. Thus, the report suggested to pursue tighter monetary and fiscal policy to
“help inflation decline gradually to about 3 per cent in 2012-2014” (p. 10).
2.3.10 Nepal
Table 2.3.10: Average Growth-Inflation Figures in Nepal
Country
Nepal
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
4.31
4.2
3.8
3.95
1.89
2.75
4.35
4.42
4.31
Inflation
11.6
7.8
7.4
8.24
4.05
7.98
10.94
8.29
5.90
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
40
Nepal is one of the poorest countries in Asia with 25.2 per cent people living below
the poverty line.41 Its growth performance is also poor with historical median value,
since the 1960s, standing below 4 per cent (see Table 2.3.10). The IMF itself admits
that the structural problems of the economy has stopped Nepal to achieve higher
growth path (IMF 2010f, p. 8). In spite of the lacklustre growth performance, the
country report on Nepal praised the fiscal discipline maintained by the country and it
was seen as a “remarkable achievement” (ibid., p. 4). Fiscal policy was said to have
continued to be “broadly prudent and public debt has declined to 40 per cent of
GDP” (p. 4). The report’s attention to inflation over growth was also noticeable. It
noted that loose monetary conditions of 2008-2009, which led to rapid credit growth,
were responsible for double digit inflation in 2009 (see p. 3 and 7). In 2009, inflation
reached at around 11 per cent (see Table 2.3.10). The staff-appraisal, therefore,
thought that it was a challenging task to manage the economy since tighter monetary
policy would contain inflation but hurt economic growth (see p. 3). The case of
Nepal is a classic example where a country sacrifices growth opportunities in order
to keep inflation at a single digit level in line with the IMF prescription.
2.3.11 Pakistan
Table 2.3.11: Average Growth-Inflation Figures in Pakistan
Country
Pakistan
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
3.56
3.4
3.5
4.98
5.81
3.99
6.44
4.01
4.26
Inflation
13.64
12.0
12.5
7.15
3.18
7.71
6.22
10.17
7.52
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
41
Poverty headcount ratio at national poverty line (% of population) taken from the World Bank,
World Development Indicators.
41
Pakistan’s recent and historical median growth performance does not show a
promising sign. According to Table 2.3.11, growth was 3.56 per cent in 2009 while
the long-run median is 4.98 per cent. Both figures are well below the 7 per cent
threshold required to take a country into the trajectory of higher development.
Inflation reached a double digit figure in 2009 and is expected to remain so in the
near future. Supply shocks resulting from increased oil and food prices and energy
subsidy financed by the central bank have fuelled the inflation (IMF 2009e, p. 5).
Adverse security developments are also responsible for deteriorating condition in
Pakistan. Despite the dismal growth performance, the authorities have embarked on a
stabilisation programme incorporating “a significant tightening of fiscal and
monetary policies to bring down inflation and strengthen the external position” (ibid.,
p. 5). The authorities believe that the scope for countercyclical fiscal policy is limited
given the inflation situation of the country and they remain committed to achieving
fiscal deficit of 4.3 per cent of the GDP (see IMF 2009e, p. 15). In the case of
monetary policy, the authorities think that it is “premature to reduce the discount rate
at this juncture, as core inflation remains elevated” (ibid., p. 16). These steps taken
by the authorities have received approval in the staff-appraisal which states that
“Pakistan’s stabilisation program is on track” (ibid., p. 21).
2.3.12 The Philippines
Table 2.3.12: Average Growth-Inflation Figures in The Philippines
Country
Pakistan
Indicators
Long run
Decadal median
median
2009
2012
*
2013
*
1960-2009
1960-
1970-
1980-
1990-
2000-
69
79
89
99
09
Growth
1.14
4.2
4.7
4.61
4.82
5.35
3.46
3.01
4.66
Inflation
3.22
3.4
4.1
7.51
5.40
12.14
10.40
7.93
4.96
Source: World Bank, World Development Indicators; IMF, International Financial Statistics, and
World Economic Outlook, and author’s calculations.
Notes: Growth and inflation refers to CPI inflation and real GDP growth respectively. The data for the
year 2009 are stated because it best reflects the current condition at the time of the release of Article
42
IV Consultation-Staff Report. * refers to projected figures taken from the IMF, World Economic
Outlook.
The historical evidence suggests that the Philippines have yet to show strong growth
performance (see Table 2.3.12). Its long run median growth is below 5 per cent and
the figure dropped at 1.14 per cent in 2009. The IMF country report stated that the
slowdown in growth had been “cushioned by supportive fiscal and monetary policies
and resilient remittances” (see IMF 2010g, p. 3). The report praised the inflation
condition of the country noting that the credit growth decelerated and inflation
remained low and inflation expectation was well anchored at a level consistent with
the central bank’s inflation target (ibid., p. 12). Although the recovery was not
promising the report suggested “fiscal withdrawal” and capping the fiscal deficits at
3.5 per cent of GDP to contain the high public debt level and to avoid jeopardizing
investor confidence (see p. 9).42
A summary of the country reports analysed above shows little evidence of change in
the advice on policy by the IMF staff. This finding is mostly consistent with that of
Anwar and Islam (2011). The decadal median values show enough variation and
therefore it is difficult to suggest a unique inflation target that can be followed for all
the countries. It provides a strong case for following what is stated in the preamble of
IMF’s Article IV that country specific circumstances should be taken into
consideration as reiterated by studies such as Roy and Ramos (2012) and Anwar and
Islam (2011).
To end this section we provide an additional analysis based on two regimes – pre and
post structural adjustment programme started in the 1980s by the World Bank and
supported by the IMF. Table 2.4 presents average inflation and growth data for the
two regimes, 1960-1979 and 1980-2009 for South Asian countries (they are
considered because of the availability of relatively longer time series data). These
countries started to embrace the reform programmes since the 1980s. However, post
1980 era records a higher inflation rate for all the countries (ignoring Bangladesh as
it went through an unusual phase in its history in the 1970s) at above 5 per cent (the
42
This suggestion comes in view of the government’s plan to target a deficit of 3 per cent of GDP in
2010 so as to attain a balance-budget by 2013 (see IMF 2010g, p. 9).
43
preferred rate as one would expect after going through the reform programmes).
Growth figures for all these countries, except for Pakistan, are also higher in the post
1980 era. In short, such evidence provides a clear argument against targeting a low
single digit inflation rate.
Table 2.4: Median CPI Inflation and Growth in Countries in South Asia, Pre and Post
1980
Country
Variable
1960-1979
1980-2010
Bangladesh
Inflation
16.60
6.90
Bangladesh
Growth
3.27
4.80
India
Inflation
5.73
8.33
India
Growth
3.79
5.82
Nepal
Inflation
7.58
8.29
Nepal
Growth
2.34
4.31
Pakistan
Inflation
5.56
7.88
Pakistan
Growth
5.36
4.84
Sri Lanka
Inflation
3.19
11.10
Sri Lanka
Growth
4.13
4.97
Note: Pre 1980 period for Bangladesh is 1971 – 1979 a turbulent period in its history.
2.4 Conclusion
The findings of this chapter clearly show that the IMF policy advice is not consistent
with the recent suggestions, particularly made by its own leading influential
economists. Nor does it comply with the historical country-specific experience. Both
content analysis using the Article IV consultation reports and historical evidence
from time series data reaffirm this. The IMF even in the wake of the global crisis
seems to continue to advocate for low inflation strategy without giving due
consideration to the country specific circumstances. Our critique on the continued
policy advice by the IMF has been carried out from 3 different directions so far. We
find inconsistency at all 3 levels (a) with the shift in the IMF’s own thinking as
revealed by its senior economists, (b) with the history of inflation and growth and
country circumstances, and (c) findings from the literature. The IMF policy still
44
tends to follow a pre-set view with predictable conclusions that do not allow for
alternative perspectives. The analysis of this chapter reiterates the need for a change
in the narrow policy advice and put it firmly on its already stated principle of
“fostering economic growth with reasonable price stability.” The next chapter
examines the country-specific experience of inflation and economic growth in some
selected developing countries of Asia from the existing literature.
45
Chapter 3
Cross-Country Evidence on Inflation-Impact on Growth: A
Review of Related Literature
3.1 Introduction
This chapter provides a critical review of the cross-country panel studies on inflation
and growth in the context of developing countries. The key purpose of this chapter is
to examine whether the existing literature provides a strong empirical support to keep
inflation within 5 per cent level in the case of developing countries as suggested by
the IMF. In the following section the evidence on issues relating to growth-inflation
nexus are reviewed followed by a section with concluding remarks.
3.2 Cross-Country Evidence of Growth-Inflation Nexus
On the issue of whether inflation is harmful to growth one of the most influential
study by Bruno and Easterly (1998) states that “the ratio of fervent beliefs to tangible
evidence seems unusually high on this topic, despite extensive previous research” (p.
3). They find robust evidence that growth falls sharply at discrete high inflation
(which they propose to be 40 per cent per annum) crises, then recovers rapidly and
strongly after inflation falls. Like Bruno and Easterly (1998), Barro (1996) also notes
that the clear evidence for adverse effects of inflation comes from the experience of
high inflation. He, however, points out that although the magnitudes of effects are
not that large, over long periods these changes in growth rates have dramatic effects
on the standard of living and, therefore, justify the interest in attaining price stability.
The important question therefore is to find out what level of inflation can be
considered not harmful for economic growth. The next few paragraphs address this
issue and examine the findings from the literature in relation to developing countries.
Table 3 provides a list of selected cross-country studies investigating the growthinflation relationship incorporating developing countries.
46
Table 3: Selected Cross-Country Studies on the Relationship between Growth and
Inflation
Study
Period
Number of
Method
Major findings
Rolling-
Inflation threshold is
window two-
between 8 and 15 per cent.
stage-least-
A positive effect of trade
square
and human capital on
method.
growth is significant when
countries
Yilmazkuday
1965-2004
84 countries
(2013)
inflation is below 8 and 15
per cent respectively.
Lopez-
1961-2007
44 countries
Panel smooth
Inflation has a nonlinear
Villavicencio and
transition
impact on growth.
Mignon (2011)
model
Threshold inflation differs
(PSTR) and
strongly between
dynamic
developed and developing
generalised
countries. For developing
method of
countries it is 17.5 per cent
moments
below which the
(GMM)
relationship is nonsignificant.
Bick (2010)
1960-2004
40 developing
Generalised
Inflation thresholds are
countries
panel
found to be at 12 and 19
threshold
per cent with and without
model.
regime intercept
respectively.
Espinoza et al.
1960-2007
165 countries
(2011)
Logistic
Inflation threshold lies
smooth
between 7 and 13 per cent
transition
for developing countries.
regression
model.
Pollin and Zhu
(2006)
1961-2000
80 middle-income
Pooled OLS,
Inflation threshold roughly
and low-income
Fixed effects,
between 15 and 18 per
countries
Random
cent.
effects, and
Between
effects panel
estimation
47
models.
Drukker et al.
1950-2000
138 countries
(2005)
Non-dynamic,
Threshold level of inflation
fixed effects
is around 19 per cent in the
panel data
full sample.
models.
Sepehri and
1960-1996
Moshiri (2004)
92 countries with
Spline
Inflation threshold is at 15
26 lower-middle-
regression
and 11 per cent for lower-
income and 28
technique.
middle-income and low-
low-income
income countries
countries.
respectively.
Burdekin et al.
1965-1992
21 industrial and
Generalised
Higher inflation threshold
(2004)
and 1967-
51 developing
least squares
for more advanced
1992 for
countries.
(GLS)
countries; 8 and 3 per cent
developed
estimator with
for industrial and
and
fixed effects.
developing countries
developing
respectively.
countries
respectively
Khan and
1960-1998
140 countries
Senhadji (2001)
Conditional
Inflation threshold is at 1-3
least squares
and 11-12 per cent for
industrial and developing
countries respectively. The
positive effect of inflation
on growth is present up to
18 per cent for developing
countries when threshold
level varies from 1 to 50
per cent.
Ghosh and
1960-1996
145 countries
Phillips (1998)
Binary
Inflation threshold at 2-3
recursive
per cent.
trees method.
Bruno and
1961-1992
26 countries
Easterly (1998)
Descriptive
There is no cross-sectional
analysis
correlation between longrun averages of growth and
inflation below inflation
rate of 40 per cent.
Paul et al. (1997)
1960-1989
70 countries
Granger
Low world inflation regime
methodology
is expected to redistribute
real growth opportunities
benefit from the developing
48
countries in favour of
industrialised countries. No
causal relationship in 40
per cent, bidirectional
causality in 20 per cent,
and unidirectional causality
in one third countries are
found. Causality, uni or
bidirectional, is more
prominent in industrial
countries.
Barro (1996)
Sarel (1996)
1960-1990
1970-1990
100 countries
87 countries
Regression
Clear evidence for adverse
with
effects of inflation comes
instrumental
from the experiences of
variables
high inflation.
Spline
Threshold level at 8 per
regression
cent.
There is strong empirical evidence, based on most of the recent cross-country panel
studies, that the relationship between growth and inflation is nonlinear. In other
words, inflation may have both positive and detrimental effects on growth. These
studies are both recent and relatively old. They are also carried out inside and outside
the IMF and the World Bank. For instance, Sarel (1996), a study carried out at the
IMF, points out the importance of nonlinearity ignoring which may lead to estimated
effect of inflation on growth being biased by a factor of three. The study using
annual data for 87 countries over 1970-1990 finds evidence of a structural break of
inflation rate at 8 per cent. Sarel (1996), however, does not differentiate between
developed and developing countries and, therefore, suffers from the potential bias in
the estimation due to combining various countries at different levels of development
(see Sepehri and Moshiri 2004). Other IMF studies, including Ghosh and Phillips
(1998) and Espinoza et al. (2011), also support a nonlinear relationship. Ghosh and
Phillips (1998) also argue that this relationship is convex in nature. So, for instance,
the decline in growth associated with an increase in inflation from 10 per cent to 20
per cent is much higher than that associated with an increase from 40 per cent to 50
per cent. Espinoza et al. (2011) revisit the impact of inflation on growth. They
justifiably use a nonlinear framework – logistic smooth transition regression (LSTR)
49
model – to estimate the inflation threshold incorporating 165 countries over the
period 1960-2007. They find threshold levels in the range of 7 to 13 per cent for
developing countries.
Examples of studies outside the IMF include Pollin and Zhu (2006) and LopezVillavicencio and Mignon (2011). The study by Pollin and Zhu (2006) incorporates a
squared term of inflation in their estimation of the inflation threshold for 80 countries
for the period 1961-2000. On the other hand, Lopez-Villavicencio and Mignon
(2011) employs panel smooth transition (PSTR) model as well as generalised method
of moments (GMM) with a quadratic interaction term of inflation, similar to Pollin
and Zhu (2006), to check the robustness of their results. In short, these findings show
the importance of nonlinearity in the relationship between growth and inflation,
ignoring which might “significantly underestimate the impact of inflation on growth”
(Espinoza, Leon & Prasad 2010, p. 6).
Studies also find that the degree of correlation between growth and inflation may
vary according to circumstances. For instance, the influential study by Bruno and
Easterly (1998) finds correlation with high frequency data and with extreme inflation
observations. Pollin and Zhu (2006) draw the conclusion that the relationship
between growth and inflation is more strongly correlated in the case of policy aiming
at demand management to stimulate growth. Both these results have relevance in
explaining the correlation between growth and inflation in developing countries.
Developing countries are more prone to supply shocks and crises resulting in
episodes of high inflation. At the same time since private sectors are not well
developed, these economies often resort to government initiatives to stimulate
demand and thereby growth.
Although there exists a general consensus on the relationship between growth and
inflation being nonlinear, there is less agreement over the issue of causality. In spite
of their finding that inflation hurts growth Ghosh and Phillips (1998, pp. 708-709)
state that they cannot “claim to have shown that inflation causes growth…[as] it is
difficult to conceive of any methodology that would decisively prove causality from
inflation to growth.” In an earlier and most widely cited study, Barro (1996) suggests
that effects of inflation on growth and investment are significantly negative and the
50
causation is believed to be from higher long-term inflation to reduced growth and
investment. His empirical analysis covers 100 countries from 1960 to 1990. Using a
smaller sample and timeframe, but with a more formal econometric technique –
Granger causality method – Paul et al. (1997) examine the direction and pattern of
causality between inflation and economic growth in 70 countries over the period
1960-89. Their results find unidirectional causality in 26 countries, bidirectional
causality in 16 countries, and no causal relationship in 28 countries. The other
important finding of the study is that majority of the countries which show either uni
or bidirectional causality belong to the industrial country group. In other words, for
developing countries the causality between inflation and growth is not much evident.
Paul et al. (1997) also note that majority of the developing countries showing no
trade-off between inflation and growth are medium to high inflation economies
(ibid., p. 1393). This finding by Paul et al. (1997) seems to contradict the conclusion
drawn by Bruno and Easterly (1998) who state that harmful effect of inflation is
evident only in the presence of extreme inflation.43
The existence of nonlinearity in the relationship suggests that there is a threshold
level of inflation beyond which inflation has an adverse effect on growth. In a study
by Amato and Gerlach (2002, p. 788), the authors state that “there is little hard
evidence to suggest that the level of inflation targets [in developing
countries]…should be much different than in more advanced economies.” Evidence
based on the cross-country studies, however, tends to support the idea that the
threshold level of inflation varies between developed and developing countries with a
relatively higher level for the latter. Sepehri and Moshiri (2004) point out that the
inverted U shaped relationship between inflation and growth vary across countries of
various stages of development. The study by Ghosh and Phillips (1998, p. 709),
carried out at the IMF, also believes that the threshold level of inflation is “expected
to differ, at least somewhat, across countries.” Because of the existence of such
degree of heterogeneity across countries in terms of development, Sepehri and
Moshiri (2004) suggest that it is inappropriate to set “a single numerical policy
target” uniformly for all developing countries (ibid., p. 202). Their basic model is
based on Solow’s augmented production function which is estimated using Sarel’s
43
We, however, know that correlation and causation are not the same. Bruno and Easterly (1998)
looked at the correlation while Paul et al. (1997) examined the causation.
51
(1996) spline regression technique. The dataset contains annual data covering 92
countries (including 26 and 28 lower middle income and low income countries
respectively) over the period 1960-1996. In general, for developing countries the
study finds a threshold at a double digit level and higher than for advanced
economies. They, however, find a higher threshold for lower middle income
countries compared to low income countries (see Table 3) which is inconsistent with
other studies. Generally, as mentioned above, poorer countries are likely to have
higher threshold of inflation affecting growth. This higher inflation tolerance of
developing countries might be due to a number of reasons such as the BalassaSamuelson effect, indexation systems, exchange rate policies, and experience of high
bouts of inflation in these countries (see Lopez-Villavicencio & Mignon 2011, p.
462)
In a similar study around the same time, Burdekin et al. (2004) use a variant form of
Sarel’s (1996) econometric technique and treat developed and developing countries
separately to estimate the effect of inflation on growth. The study uses annual data
for 21 industrial countries from 1965-1992 and 51 developing countries from 19671992. The inflation threshold for developing country, according to this study, is 3 per
cent which is significantly lower than 8 per cent found for the advanced economies.
This finding is at odds with the results found by Sepehri and Moshiri (2004) as well
as other major recent studies. Perhaps a rationale behind this result by Burdekin et al.
(2004) can be found in the explanation by Dorrance (1966). Prices are more
inflexible downwards as a result of more organised trade unions in rich countries
compared to poor countries. Developing economies are also mostly dependent on a
few primary products for exports and agricultural products. Therefore, Dorrance
(1966) argues that the appropriate rate of inflation needed to achieve relative price
flexibility in advanced economies is higher than that of developing countries. One
serious limitation of the study by Burdekin et al. (2004) is that it uses previous period
real GDP per capita as a regressor. The level of real GDP per capita is likely to be
nonstationary and thus using this variable may lead to a spurious relationship.
Not only does the threshold vary between developed and developing countries, the
difference between the figures is quite substantial. One of the most influential studies
in this area, Khan and Senhadji (2001), finds inflation threshold for developing
52
countries at 11-12 per cent. This double digit figure is much higher than the 1-3 per
cent threshold found for the advanced economies. The dataset of this study, done at
the IMF, covers 140 countries over the period 1960-1998. More importantly, the
study conducts sensitivity analysis to see the effect of inflation on growth when the
threshold level varies from 1 to 50 per cent. The sensitivity analysis shows a positive
effect of inflation on growth up to 18 per cent for developing countries (p. 16). In a
more recent study (outside the IMF), Lopez-Villavicencio and Migon (2011) also
find a wide difference between the threshold figures for developed (2.7 per cent) and
developing countries (17.5 per cent). The study shows that for developing countries
the relationship between inflation and growth is non-significant when inflation is
below 17.5 per cent. The results are consistent using both PSTR model and GMM.
Based on their results, the authors question the validity of long-run neutrality of
money since monetary policy may have different effects on output depending on the
inflation level. The findings of both these studies, in short, tell us that governments in
developing countries need not worry too much about runaway inflation and its
marginal impact on growth when inflation is below 18 per cent. This is in sharp
contrast to what IMF advocates for – keeping inflation at 5 per cent level – and
therefore may have profound implications on the policy making in developing
countries. A low inflation threshold such as 5 per cent may be applicable for
advanced economies but not in the case of developing and emerging economies.
Apart from the two studies mentioned above, several other studies find the threshold
for developing countries generally between 7 and 19 per cent. Pollin and Zhu (2006)
estimate the inflation threshold for 80 countries over the period 1961-2000. The
authors, in addition to entire sample period, consider four separate decades and
consistently find that higher inflation is associated with moderate gains in growth up
to around 15-18 per cent inflation. Based on their results, they have questioned the
justification of inflation targeting policies to keep inflation at 3-5 per cent levels.
There are, however, several limitations of this study. First panel estimation models –
pooled OLS, fixed effects, random effects, and between effects – used are not
appropriate in a dynamic setting and fail to take care of the issue of endogeneity
problem. Such problems can be taken care of by using GMM estimations which
some of the other studies relied on. The study also does not include variables relating
53
to money as a control variable in the model.44 Money is an important covariate in
explaining the growth-inflation relationship. Moreover, in the case of regression by
decades, estimates of linear and squared terms of inflation are not significant at 5 per
cent in a number of cases.
Drukker et al. (2005), using an unbalanced panel dataset covering 138 countries
spanning over 1950-2000, find a well-defined threshold level at 19.16 per cent for
the full and non-industrialised samples.45 One limitation of this study is that the
inference made is based on a non-dynamic fixed effects model instead of more
appropriate dynamic models such as GMM. Bick (2010) also finds a similar result,
but argues that the inclusion of regime intercept, used in his study, lowers the
threshold from 19 per cent to 12 per cent. Inflation rates less than 12 per cent are
associated with a significant positive effect on growth. Bick’s (2010) study consists
of a balanced panel dataset46 of 40 developing countries covering the period 19602004. Instead of suggesting a precise threshold point the study by Espinoza et al.
(2011), done inside the IMF, shows that inflation threshold for developing countries
lies between 7 and 13 per cent. For greater precision of the estimates they have used
bootstrapping and Monte Carlo simulations.
Finally, Yilmazkuday (2013) reveals that the positive impact of some of the
determinants of growth on growth depends on level of inflation. The positive effect
of human capital on growth is present and significant when inflation is below 15 per
cent. Financial development is effective only when inflation is below 10 per cent and
trade has a positive impact on growth when inflation remains below 8 per cent. An
interesting finding of the study is that government size negatively affects growth
when inflation is below 10 per cent. This shows that in a low inflationary
environment government expenditure may not be able to positively affect growth.
Thus keeping inflation at a low single digit level may conflict with the need for
government expenditure which most of the developing countries resort to for
development, in the absence of a well-developed private sector. Although the
44
The paper by Khan and Senhadji (2001) also suffers from the same problem.
They also find two but lower threshold levels, 2.57 and 12.61 per cent, for industrial countries.
46
One may question this aspect of the dataset as it is difficult to create a balanced dataset for
developing countries due to poor availability of data.
45
54
threshold figures for inflation vary, the author takes a conservative approach and
suggests that inflation hurts growth when it goes beyond 8 per cent.
One of the limitations in the methodology of the above mentioned studies is that they
usually take five-year averages to smooth out business cycle fluctuations. It is not
appropriate to assume uniform business cycle for all the countries within crosscountry panel studies. Their business cycle may not follow the same pattern. Besides,
averaging out data by taking five-year averages causes reduction in sample which
might make the variables statistically insignificant. These issues are discussed in
detail in the empirical part of the thesis, Chapter 5.
We also notice that certain control variables chosen in the models of the studies
mentioned above may not be appropriate in examining the growth-inflation
relationship. The issue here is how inflation affects growth conditioned upon other
covariates. The interest, therefore, is not in finding the determinant of growth or how
they impact growth. The covariates should be chosen not because they are the
potential candidates of growth determinants but because they may influence the
condition and the way in which inflation affects growth. In this regard, one can argue
that for developing countries consumption is a better regressor than investment (as is
used in most of the studies cited above) since the former has a greater explanatory
power in the changes in aggregate demand and thus both growth and inflation. At the
same time, population growth used as a proxy for labour supply growth may not be
effective as a left hand side variable. In most developing countries population control
in recent decades is a dominant policy strategy; as a result, it has become nearly
constant. Therefore, how powerful it is in explaining the growth-inflation
relationship becomes questionable.
3.3 Conclusion
The review of the existing literature on cross-country panel studies provides strong
evidence that inflation threshold in developing countries is well above 5 per cent
level. Broadly, the threshold varies between 7 and 19 per cent with majority of the
studies supporting a double digit level for developing countries. The findings clearly
reveal that the IMF’s suggestion to keep inflation at 5 per cent or below may be
55
applicable for developed countries, but certainly not for developing countries. Most
studies including the influential ones carried out at the IMF suggest that the threshold
for developing countries is significantly higher than that of advanced economies.
Since the growth-inflation relationship is non-linear, developing countries can gain
from moderate levels of inflation and should not be alarmed when inflation crosses
the 5 per cent benchmark set by the IMF. In fact, Anwar and Islam (2011), as
discussed in Chapter 2, conclude that considering the threshold effects setting too
low an inflation target, particularly at single digits, can impose opportunity costs in
terms of foregone growth and employment creation. Anwar and Islam (2011) also
find little evidence of low inflation being translated into benefits of reduced cost of
borrowing. This is because, as the authors argue, such costs are likely to be
determined by structural factors of the economy. Epstein and Yeldan (2008) also
draw a similar conclusion and state that the IMF prescribed stabilisation program to
attain price stability to ensure growth has not been materialised. They suggest to
design a more socially desirable macroeconomic policy environment to promote
employment, sustained growth, and improved income distribution.
56
Chapter 4
An Enquiry into the Relationship between Inflation and
Growth in Selected Developing Countries of Asia
4.1 Introduction
There is much evidence, from the discussion of the previous 3 chapters, that
moderate inflation in the range between 10 and 15 per cent in the developing
countries may not signal a worrying sign. In other words, inflation within this range
may not cause acceleration in inflation expectations which is feared to affect
economic growth adversely. The critical review and historical analysis also provide
arguments that maintaining inflation at a low single digit level may entail a high
sacrifice for the developing countries in terms of growth, employment generation,
and poverty reduction. Monetary policy aimed at a low inflation target may have
such unwarranted effects especially when inflation is caused by supply side factors.
In short, the fear of runaway inflation – believed to be triggered when inflation
reaches beyond 5 per cent – and the policies targeting a low inflation may create
constraints on the performance and progress of developing countries, which might
otherwise grow at a faster pace.
Against this background, this chapter critically reviews country-specific studies on
the relationship between growth and inflation. A list of 15 developing countries of
Asia is selected to review the country-specific cases. These countries are Bangladesh,
Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Maldives, Nepal,
Pakistan, The Philippines, Sri Lanka, Thailand, and Vietnam. The time series data
used for supporting the critical review are collected from the World Bank’s World
Development Indicators (WDI) and the IMF’s World Economic Outlook (WEO).
The periods considered for inflation and growth are 1960-2009 and 1960-2010
respectively. The difference in the periods is due to the availability of data from the
WDI 2011 at the time of the analysis. In addition, the periods for some of the
countries are much smaller because of poor availability of data.
57
The rest of the chapter proceeds as follows. Section 4.2 looks at trends in inflation
and growth in the countries in question. Section 4.3 provides evidence on the nature
of relationship between inflation and growth from the literature. A discussion on
findings about threshold levels of inflation takes place in Section 4.4. Section 4.5
reviews experiences of policies targeting low inflation in the selected countries. The
debate on sources of inflation in the selected countries is reviewed in Section 4.6.
Finally, Section 4.7 draws conclusion.
4.2 Trends in Inflation and Growth in Some Selected Developing Countries of
Asia
A summary of descriptive statistics of inflation in the 15 selected countries is
presented in Table 4.1. Long term data over the period 1961–2009 show that median
inflation rate varies from a relatively moderate 7–10 per cent to a relatively low 2–4
per cent. For instance for countries such as India, Indonesia, Pakistan, The
Philippines, and Sri Lanka the rate ranges between 7 and 10 per cent while for
Malaysia and Thailand it varies between 2 and 4 per cent. Inflation volatility,
measured by the coefficient of variation (CV), also reveals differences amongst these
countries. For example, while India has median inflation rate of around 7 per cent,
higher than China’s at around 2 per cent, its inflation is less volatile compared to
China’s. This shows that low long-run inflation may not necessarily ensure less
volatility in inflation and therefore less uncertainty arising from it. Such differences
confirm that historical inflation experiences vary across countries. Considering an
identical inflation threshold point such as 5 per cent for all, therefore, is not
appropriate (see for instance Sepehri & Moshiri 2004).
Table 4.1: Summary Statistics of CPI Inflation in 15 Developing Countries of Asia
Country
Period
Mean
Median
Max
Min
SD
CV
Bangladesh
1971 – 2009
10.82
8.40
54.60
-2.40
11.88
1.10
Bhutan
1981 – 2009
7.77
7.03
18.02
1.88
3.87
0.50
Cambodia
1995 – 2009
5.64
3.92
25.00
-0.79
6.87
1.22
China
1970 – 2009
4.56
2.15
24.24
-1.41
6.03
1.32
India
1961 – 2009
7.66
7.16
28.60
-7.63
5.28
0.69
Indonesia
1961 – 2009
52.87
10.46
1136.25
3.72
166.91
3.16
58
LAO PDR
1989 – 2009
24.21
10.63
128.42
0.04
32.01
1.32
Malaysia
1961 – 2009
3.22
2.81
17.33
-0.41
3.11
0.97
Maldives
1988 – 2009
5.72
4.73
20.18
-2.86
5.89
1.03
Nepal
1965 – 2009
8.18
8.24
19.81
-3.11
5.28
0.65
Pakistan
1961 – 2009
8.10
7.16
26.66
-0.52
5.56
0.69
Philippines
1961 – 2009
9.72
7.51
50.34
0.75
8.66
0.89
Sri Lanka
1961 – 2009
8.99
8.45
26.15
-0.16
6.01
0.67
Thailand
1961 – 2009
4.80
4.14
24.31
-0.85
4.85
1.01
Vietnam
1996 – 2009
6.22
6.36
23.12
-1.71
5.79
0.93
Source: Author’s calculations based on the data from the IMF, World Economic Outlook and World
Bank, World Development Indicators.
Table 4.2 records the descriptive statistics relating to growth in the selected
countries. In terms of long-run growth experiences, between 1961 and 2010, China
and Malaysia post relatively good growth performance with, median rates at 8.85 and
6.81 per cent, respectively. Nepal, one of the poorest countries in the region, posts
the worst growth record with a median rate at 3.95 per cent.47 Output growth
volatility also reveals some interesting stylised facts. For example, high growth rate
can be associated with high volatility. This is evident from the Chinese experience.
While its median growth rate, during the period 1961–2010, is the highest amongst
the countries under study, volatility of its growth is also relatively high. On the other
hand, growth variability in Pakistan and Sri Lanka, for example, is relatively low, but
so are their growth rates, standing below 5 per cent. We also note an important fact
from the growth figures shown in Table 4.2. The majority of countries, except for
China and Cambodia (for the latter, relatively shorter time series data are available),
fall short of the required 7 per cent growth to meet their Millennium Development
Goals (MDGs) targets as suggested by the IMF study Selassie et al. (2006).
Table 4.2: Summary Statistics of Real GDP Growth in 15 Developing Countries of Asia
Country
Period
Mean
Bangladesh
1971 - 2010
3.70
Bhutan
1982 - 2010
Cambodia
China
Median
Maximum
Minimum
SD
CV
4.72
9.16
-15.05
3.99
1.08
7.32
6.75
18.42
2.06
3.59
0.49
1994 - 2010
7.41
7.73
12.44
-1.89
3.24
0.44
1961 - 2010
7.66
8.85
17.73
-31.61
7.55
0.98
47
Nepal’s rank is at 157, at the bottom of the ranking amongst these countries according to Human
Development Index (HDI) 2011.
59
India
1961 - 2010
5.47
5.47
19.57
-5.38
3.54
0.65
Indonesia
1961 - 2010
5.40
5.96
11.36
-14.07
3.84
0.71
Lao PDR
1985 - 2010
5.93
6.07
13.27
-2.03
2.84
0.48
Malaysia
1961 - 2010
6.20
6.81
11.08
-7.64
3.41
0.55
Maldives
1996 - 2010
6.24
6.98
16.53
-4.76
5.04
0.81
Nepal
1961 - 2010
3.56
3.95
9.24
-3.02
2.71
0.76
Pakistan
1961 - 2010
5.21
4.98
10.75
0.47
2.30
0.44
Philippines
1961 - 2010
3.94
4.62
8.54
-7.61
3.04
0.77
Sri Lanka
1961 - 2010
4.60
4.89
7.71
-1.56
1.88
0.41
Thailand
1961 - 2010
6.13
5.94
12.48
-11.10
3.81
0.62
Vietnam
1985 - 2010
6.55
6.75
9.11
2.75
1.72
0.26
Source: Author’s calculations based on data from the IMF, World Economic Outlook and World
Bank, World Development Indicators.
Time series graphs of inflation and growth of the countries under study also help
decipher some of the stylised facts about the relationship between the two variables.
These graphs are categorised in terms of countries within the region and are
presented in Figures 4.1a – 4.1.d. In general, trends in inflation and growth in these
countries reveal that over a long period the two variables seem to move together.
There is, however, no particular pattern in the relationship that can be observed from
the graphs across countries. For example, in the case of four countries of South Asia
– Bangladesh, India, Pakistan, and Sri Lanka – there are traces of inflation becoming
both lead and lag variable, implying that the causality between inflation and growth
may run in both ways – inflation causing growth as well as growth causing inflation
(Figure 4.1.a). In the early 1980s, India’s rising growth rates seemed to be preceded
by rising inflation. On the other hand, in the early 1990s rising inflation seemed be
followed by declining growth. We cannot, however, draw conclusion about the
causality between the two based on such casual observations. This requires
econometric techniques such as Granger causality test to determine the direction and
nature of causality.
We also notice some interesting facts about Malaysia between the mid-1980s and
mid-1990s (Figure 4.1.c). High and sustained growth during this period seems to be
associated with rising inflation. The economy of Thailand shows a similar trend in
growth and inflation in the latter half of the 1980s. The Chinese economy, between
the period 1980 and 2010 as illustrated in Figure 4.1.d, also appears to show that
inflation is mostly a lag variable.
60
The evidence from the above discussion lends support to the discussion in Chapter 1.
That is, there are past instances when developing countries had economic growth
with rising inflation. It is also consistent with Bruno and Easterly’s (1996)
observation discussed in Chapter 1. The co-movement of inflation and growth
reveals an interesting feature. When growth rises, so does inflation. But once
inflation reaches a certain level growth starts to decline causing inflation to fall in
turn. This feature to a great extent provides support for the structuralist view –
inflation is an inevitable consequence of economic growth. What is perhaps also
implied that causality mostly runs from growth to inflation.
Figure 4.1.a: Inflation and Growth in South Asia – Bangladesh, India, Pakistan, and
Sri Lanka
Bangladesh
India
60
30
40
20
20
10
0
0
-20
-10
60
65
70
75
80
85
90
95
00
05
10
60
65
70
75
Pakistan
80
85
90
95
00
05
10
95
00
05
10
Sri Lanka
30
30
25
25
20
20
15
15
10
10
5
5
0
0
-5
-5
60
65
70
75
80
85
90
95
00
05
10
CPI Inflation
60
65
70
75
80
85
90
Real GDP Growth
Source: IMF, World Economic Outlook and World Bank, World Development Indicators.
61
Figure 4.1.b: Inflation and Growth in South Asia – Bhutan, Maldives, and Nepal
Bhutan
20
16
12
8
4
0
60
65
70
75
80
85
90
95
00
05
10
90
95
00
05
10
90
95
00
05
10
Maldives
25
20
15
10
5
0
-5
60
65
70
75
80
85
Nepal
20
16
12
8
4
0
-4
60
65
70
75
80
CPI In f la t io n
85
Real GDP Growth
Source: IMF, World Economic Outlook and World Bank, World Development Indicators.
62
Figure 4.1.c: Inflation and Growth in East Asia – Indonesia, Malaysia, Philippines, and
Thailand
Indonesia
Malaysia
60
20
15
40
10
20
5
0
0
-5
-20
1970
1975
1980
1985
1990
1995
2000
2005
2010
-10
1970
1975
1980
1985
Philippines
1990
1995
2000
2005
2010
2000
2005
2010
Thailand
60
30
50
20
40
30
10
20
0
10
-10
0
-10
1970
1975
1980
1985
1990
1995
2000
2005
2010
CPI Inflation
-20
1970
1975
1980
1985
1990
1995
Real GDP Growth
Source: IMF, World Economic Outlook and World Bank, World Development Indicators.
63
Figure 4.1.d: Inflation and Growth in China and East Asia – Cambodia, Lao PDR, and
Vietnam
Cambodia
China
30
25
25
20
20
15
15
10
10
5
5
0
0
-5
1980
1985
1990
1995
2000
2005
2010
-5
1980
1985
1990
Lao PDR
1995
2000
2005
2010
2000
2005
2010
Vietnam
160
25
120
20
80
15
40
10
0
15
10
5
5
0
0
-5
1980
1985
1990
1995
2000
2005
2010
CPI Inflation
-5
1980
1985
1990
1995
Real GDP Growth
Source: IMF, World Economic Outlook and World Bank, World Development Indicators.
4.3 The Nature of Relationship between Inflation and Growth
High episodes of inflation distort macroeconomic stability and adversely affect
economic growth. As a result a strong inflation aversion develops and an antiinflationary psyche starts to dominate the mindset of the policy makers in such
inflation hit countries (see, for instance, Chowdhury & Ham 2009; Chowdhury &
Siregar 2004).48 As Bruno (1992) puts it clearly: “…stabilization may, for a time,
reduce inflation dramatically, but it will not …eradicate inbred inflation
mentality…on the part of all relevant agents, both public and private.” Such high
bouts of inflation, however, are not frequent in economic history and therefore do not
48
A classic example is Indonesia within this region. In view of hyperinflation in the mid-1960s, which
coincided with economic stagnation, inflation was regarded as ‘enemy number one’ (Chowdhury
2002, p. 21).
64
provide a clear picture of the relationship between inflation and growth. To reiterate
the findings of Bruno and Easterly (1998), inflation has a clear detrimental effect on
growth at a very high rate such as 40 per cent. The nature of relationship is not
conclusive below such high levels of inflation in the literature. This section reviews
the issue in the context of the sample countries of Asia. Table 4.3 lists some of the
recent studies investigating the nature of relationship between inflation and growth in
the countries selected.
Table 4.3: Studies on Inflation-Growth Causality
Study
Empirical
Dependent
Regressor
Approach
Variable
s
1971 –
Vector
Growth
Lagged
In the short run
Mukhopadhya
2007
autoregressiv
and
values of
inflation
y (2011)
(annual
e (VAR)
inflation
growth
Granger causes
)
model
and
growth but in
inflation
the long run
Datta and
Country
Malaysia
Period
Findings
growth Granger
causes inflation.
Hussain and
Pakistan
Malik (2011)
1960 –
Cointegratio
Growth
Growth
Inflation is
2006
n and error
and
and
positively
(annual
correction
inflation
inflation
related to
)
model
growth.
Hossain
Banglades
1973 –
Cointegratio
Real
Real
A cointegral
(2010)
h
2008
n and error
balances of
GDP,
relationship
(annual
correction
broad
domestic
exists amongst
)
framework
money and
nominal
money supply,
CPI
interest
growth, and
inflation
rate,
inflation.
foreign
nominal
interest
rate,
nominal
effective
exchange
rate
Mahadevan
India,
1966 –
Multivariate
Labour
CPI and
No causality
65
and Asafu-
Indonesia,
1997
vector error
productivit
money
between
Adjaye (2006)
Malaysia,
(annual
correction
y
supply
inflation and
Philippines
)
model
productivity
, Sri
growth in
Lanka,
Thailand,
Thailand
Indonesia,
(and
Philippines, and
others)
Sri Lanka; one
way causality
from inflation
to productivity
growth in
Malaysia; and
bidirectional
causality in
India.
Ahmed and
Banglades
1981 –
Cointegratio
Growth
Growth
A statistically
Mortaza
h
2005
n and error
and CPI
and CPI
significant
(annual
correction
inflation
inflation
negative
)
models
(2005)
relationship
between
inflation and
growth exists in
the long run.
Hossain
(2005a)
Indonesia
1954 –
Granger
CPI
Money
No short run
2002
causality
inflation
supply
causality from
(annual
model
and money
growth,
inflation to
supply
CPI
growth exists.
growth
inflation,
But a short run
permanen
bi-directional
t income
causality
)
between
inflation and
money supply
growth exists
suggesting that
the former
having a
feedback effect
on the latter
66
during a
hyperinflationar
y period.
Hossain
Indonesia
(2005b)
1952 –
Cointegratio
2002
CPI
Narrow
Price level,
n and error
money
money supply,
(annual
correction
(M1),
and real
)
(ECM)
broad
permanent
model
money
income form a
(M2), real
weakly
GDP,
cointegral
nominal
relationship.
exchange
rate
Mubarik
Pakistan
(2005)
1973 –
Granger
2000
causality test
Growth
CPI
A unidirectional
inflation,
Granger
(annual
populatio
causality exists
)
n growth
from inflation
rate, and
to growth.
investmen
t growth
rate
1950 –
Bivariate
and Siregar
1997
(2004)
Chowdhury
Indonesia
Growth
Inflation
A bi-directional
vector
and
causality
(annual
autoregressiv
squared
between
)
e model
term of
inflation and
(VAR)
inflation
growth exists
but in the long
run inflation is
unlikely to
negatively
affect growth
because of the
evidence of
long run
neutrality of
money.
Chowdhury
(2002)
Indonesia
1950 –
Descriptive
1997
Analyses
n.a.
n.a.
No statistical
significant
(annual
relationship
)
between
67
inflation and
growth and
therefore
provide an
argument
against
tightening of
policies aiming
at low inflation.
Mallik and
Banglades
1974 -
Cointegratio
Growth
Growth
Positive
Chowdhury
h, India,
97
n and error
and
and
relationship
(2001)
Pakistan,
(BGD)
correction
inflation
inflation
between
and Sri
1961-
model
Lanka
97
inflation and
growth.
(IND)
195797
(PAK)
196697
(LKA)
(annual
data)
Notes: The studies are arranged first chronologically and then in alphabetical order.
As noted above, avoiding the influence of few outliers of inflation in the analysis of
inflation-growth relationship is important and appropriate. Chowdhury and Siregar
(2004) argue that once the extreme cases of inflation – a rate greater than 100 per
cent – are removed one observes a positive relationship between the two variables in
the case of Indonesia.49 However, there seems to be no relationship between the two
when inflation is in the range between 8 and 15 per cent. A similar conclusion is
drawn in an earlier study by Chowdhury (2002). In both these studies, initial
observations using scatter plot diagrams show that both high and low growth rates
occur when inflation is in the range of 5–18 per cent.
49
Removing such outliers to look at the relationship between inflation and growth is important in the
case of Indonesia since the country has experienced very high episodes of inflation, particularly in the
1960s when inflation averaged above 196 per cent (Chowdhury & Siregar 2004, p. 140), within the
sample period (1950 – 1997) of the study.
68
The key motivation of Chowdhury and Siregar’s (2004) study is to examine if there
is any scope for a moderate inflation rate above what is targeted in Indonesia around
that period. So the study sets itself to investigate the two important issues – the
nature of relationship between inflation and growth and a range of inflation at which
growth will not be negatively affected. It is set against the backdrop when Indonesia
embraced inflation targeting in its monetary policy after the Asian Currency Crisis of
1997–1998. The inflation target level during the 2000s was set between 3 and 10 per
cent in the country (see Siregar and Goo, 2010, Table 2, p. 115).50 Chowdhury and
Siregar (2004) argue that “over-fixation with a single digit inflation target cannot be
justified based on the fear of inflation going out of control once it is allowed to go
beyond, say 10 per cent” (p. 139). According to them such tight inflation targets may
have hampered economic growth and stalled the nascent recovery process.51
Chowdhury and Siregar (2004) emphasise that the understanding of the nature of
relationship between inflation and growth is important in the presence of excess
capacity and persistent high unemployment or underemployment. The authors argue,
based on their findings, that while policy makers should be cautious against high
inflation they should also be aware that moderate inflation may be required in a
country such as Indonesia to sustain economic growth. In support of the case,
Chowdhury and Siregar (2004) also provide results from econometric tests. The
Granger causality test shows presence of bi-directional effects between economic
growth and inflation. The findings from the impulse response functions show that a
positive supply shock, which the authors have interpreted as a rise in the economic
growth, leads to a decrease in inflation. In addition, a shock to inflation does not
have any effect on economic growth at the impact period. Thus, Chowdhury and
Siregar (2004) conclude that inflation can act as a “lubricant to the engine” of the
economy. They also suggest to inflate the economy to induce growth during the
recovery period.
Chowdhury and Siregar (2004) make an important contribution in establishing the
cases that excluding outliers of inflation there exists a positive relationship between
50
See also Chowdhury and Siregar (2004, Endnotes 3, p. 150).
Indonesia was hard hit by the Asian Currency Crisis 1997 – 98, suffering from severe inflationary
recession. To capture the severity of the crisis Chowdhury and Siregar (2004, p. 138) also provide
some poverty statistics – the rate of poverty went up from a historical low of 11 per cent in 1997 to
around 40 per cent in 1998.
51
69
the two variables and at moderate rates inflation may not be harmful for economic
growth.52 Perhaps a limitation of the empirical method of the study is that it
considers a bivariate framework, incorporating only inflation and growth, for their
analysis. The bivariate vector autoregressive model (VAR), used in the study, would
suffer from omitted variable bias leading to weak explanatory power in explaining
the causality.
A similar positive relationship between inflation and growth is found in four South
Asian countries namely Bangladesh, India, Pakistan, and Sri Lanka in a study by
Mallik and Chowdhury (2001).53 The empirical analysis of the study, using
cointegration and error correction framework, also shows that sensitivity of inflation
to changes in growth is larger than that of growth to changes in inflation. This
implies that moderate inflation may be helpful for growth. Mallik and Chowdhury
(2001), however, provide a cautionary note on possible overheating situation. This is
because economic growth feeds back into inflation causing economy to overheat.
A different finding is suggested in a study by Datta and Mukhopadhyay (2011) in the
context of Malaysia for the period 1971 – 2007. Both short run and long run
causation is found between inflation and growth, similar to Chowdhury and Siregar
(2004). But in this case, Datta and Mukhopadhyay (2011) note a short run negative
causality running from inflation to growth and a long run positive causality running
from growth to inflation. There is also a long run equilibrium relationship between
the two variables, as they are found to be cointegrated. These findings suggest that
inflation is harmful for economic growth in the short run, but growth in the long run
is inflationary. This conclusion is in contrast with that of Chowdhury and Siregar
(2004). Perhaps the historical experience of inflation and growth in the two
neighbouring countries, Indonesia and Malaysia, helps explain the differences. Long
run growth performance of Malaysia is relatively better than that of Indonesia
(median rates 6.81 and 5.96 per cent for Malaysia and Indonesia respectively). Long
run inflation is significantly higher in Indonesia compared to Malaysia (median rates
52
The other significant finding of the study is the threshold level at around 20 per cent for Indonesia
which is discussed in the following section.
53
The findings of this paper are discussed in detail in Chapter 2.
70
10.46 and 2.81 per cent respectively).54 The comparison of long-run median inflation
and median growth in the two neighbouring countries may imply a negative long-run
relationship between inflation and growth. However, it is also important to note that
Indonesia grew in an inflationary environment.55 One could, therefore, ask whether
Indonesia could grow at a faster rate had its inflation rate been lower, or similar to
that of Malaysia. Unfortunately, that counter factual is not available. But perhaps,
Indonesia needed higher inflation (more lubricants) given the lower level of
development and larger infrastructure deficits than Malaysia.
Additionally, Datta and Mukhopadhyay’s (2011) study seems to have serious
methodological limitations. They conclude that inflation and growth are stationary
variables and therefore they are cointegrated. This conclusion appears to be incorrect
based on the standard practice in econometric theory. First, it is very likely that firstdifferenced variables such as inflation and growth rates would be stationary in a
finite horizon, as the study have found. This however does not ensure that the two
variables are cointegrated, as the paper concludes. In order to test for cointegration,
standard practice requires unit root test for variables at their levels – real output and
price level in this instance. If both series (variables at their levels) are non-stationary
(possessing unit root) and error from the regression between the two variables is
stationary (does not have unit root) only then cointegration exists between the two
variables – output and price level. So, the conclusion of Datta and Mukhopadhyay
(2011) that inflation and growth are cointegrated is methodologically flawed.
Unlike the studies above, Hossain (2005a) finds no short run causality from inflation
to growth in complete and subsample periods in the case of Indonesia between 1954
and 2002. Perhaps the difference in the causality results between the two studies –
Hossain (2005a) and Chowdhury and Siregar (2004), both in the context of Indonesia
– is due to the issues relating to modelling and time period considered. Hossain
(2005a) performed the Granger causality test in a trivariate framework incorporating
54
For figures and the discussion on inflation-growth historical experience, both long run and medium
run, see Chapter 3. The long run average is considered taking a five decade period between 1960 and
2009.
55
Even during the high episodes of inflation of the 1950s and 1960s the Indonesian economy grew,
making Mackie (1967) to comment that the economy is somehow immune from adverse consequences
of inflation. Hossain (2005a, p. 64) suggests a possible reason could be the subsistence nature of the
economy during that period. Another important difference between the two countries is that unlike
Indonesia Malaysia has not experienced any hyperinflationary period.
71
money supply growth. The expanded model, as Hossain (2005a) suggests, is
appropriate to examine the effects of inflation on economic growth conditional on
growth in money supply. The overall implication of the result of Hossain’s (2005a)
study is, however, similar to that of Chowdhury and Siregar (2004) – inflation may
not be harmful for growth – and Hossain (2005a) notes that the Indonesian economy
did not suffer much from moderately high or volatile inflation since the early 1970s.
This fact, he comments, is reassuring but requires further investigation.
In a different study Hossain (2005b) provides similar comments on Indonesia’s
remarkable economic growth and structural transformation amidst moderately high
and fluctuating inflation. The empirical results in this case suggest a weak
cointegrating but stable relationship among real income, price level, and money
stock; therefore one can expect a causal relationship amongst them. The
cointegrating relationship amongst the three variables, covering the period 1973–
2008 for Bangladesh, helps to infer that there are forces within the economic system
that brings these variables together if they drift apart temporarily (Hossain, AA 2010,
p. 574).
Mahadevan and Asafu-Adjaye (2006) investigated the causal relationship between
inflation and productivity growth in Asian economies.56 The empirical analysis of
this study employs a multivariate vector error correction model covering the period
1966–1997. Based on the findings, they have grouped the countries in three different
categories. Inflation and productivity growth do not have any causal relationship in
Thailand, Indonesia, the Philippines, and Sri Lanka. A unidirectional causality runs
from inflation to productivity growth in Malaysia and a bi-directional causality runs
in India. Thus Mahadevan and Asafu-Adjaye (2006) conclude that a two-way causal
relationship between inflation and productivity growth does not necessarily imply
that monetary policy must be pursued using specific inflation targets, for instance, in
the case of India. On the contrary, aggressive demand boosting fiscal and monetary
policies may not trigger an inflationary spiral if, for instance, the observation of
Mishra and Mishra (2012a) that the supply curve in India is rather flat showing
evidence of an excess capacity in the economy is true.
56
An inference can be drawn on the impact of economic growth.
72
In the case of Malaysia, Mahadevan and Asafu-Adjaye’s (2006) results suggest that
there is some unexploited scope for monetary policy to target inflation for
productivity growth gains. However, they believe that if the country manages to keep
prices stable in the future then the expected positive effect on productivity growth
may not be significant if inflation targeting is adopted. Unlike its neighbours
Indonesia, The Philippines, and Thailand who sought help from the IMF after the
Asian Currency Crisis 1997-98, Malaysia refused to comply with the IMF’s
suggestions to implement inflation targeting.
In sum, the above discussion shows that inflation and growth may move together in
developing countries. This is because of structural reasons such as inevitable budget
deficits due to the need to finance the effort to close large physical and social
structural deficits with a low tax base, subsistence agriculture, and various other
supply rigidities or bottlenecks.
To end this section, we perform a simple exercise using scatter plots and Polynomial
Kernel Fit curves to provide empirical evidence on the relationship between growth
and inflation from two groups of countries. The plots are presented in Figures 4.2.a–
4.2.d. The two groups are South Asia which includes Bangladesh, India, Pakistan,
and Sri Lanka and Southeast Asia which includes Indonesia, Malaysia, The
Philippines, and Thailand. These countries are chosen because of their better
availability of data on inflation and growth. For South Asia a linear analysis shows
inflation and growth have a positive relationship up to an inflation rate of 28 per cent
(Figure 4.2.a). When inflation reaches 29 per cent the relationship starts to become
negative. The nonlinear analysis using Polynomial Kernel Fit curve shows inflation
can have both positive and negative effects on growth (Figure 4.2.b). This curve is
drawn for the whole sample without any restriction imposed on inflation or real GDP
growth. The inverted U shaped nature of the curve is consistent with the findings
from the cross-country literature discussed in Chapter 2. From the Kernel Fit graph it
appears that a turning point exists in the range between 10% and 15% of inflation.
In the case of Southeast Asia, the linear analysis tells us that the relationship is
positive up to 19 per cent of inflation (Figure 4.2.c). The relationship becomes
73
negative at a higher inflation rate. Comparison between the two groups of countries
provides an important insight. Negative impact of inflation on growth starts at a
higher inflation rate in less developed South Asia compared to more developed
Southeast Asia. This is consistent with the empirical literature, reviewed in Chapter
2, that inflation starts to have negative impact at a higher rate for less developed
economies. The nonlinear analysis using Polynomial Kernel Fit curve shows no clear
relationship between inflation and growth between zero and 10 per cent of inflation
(Figure 4.2.d). But there is a steep decline in growth taking place when inflation goes
beyond 40 per cent. This result is consistent with Bruno and Easterly’s (1998)
observation. The graph is drawn by imposing a restriction on inflation, that is, only
inflation rates less than 100 per cent are considered. This simple exercise reveals
some important results which are consistent with the findings from existing
literature.
Figure 4.2.a: Scatter Plot and Linear Fitted Line in Four Countries of South Asia
20
Real GDP Growth
15
10
5
0
-5
-10
-8
-4
0
4
8
12
16
20
24
28
CPI Inflation
Linear Fitted Line
0.95 Ellipse
74
Figure 4.2.b: Scatter Plot and Polynomial Kernel Fit Curve in Four Countries of South
Asia
20
16
Real GDP Growth
12
8
4
0
-4
-8
-12
-16
-10
0
10
20
30
40
50
60
CPI Inflation
Figure 4.2.c: Scatter Plot and Linear Fitted Line in Four Countries of East Asia
15
Real GDP Growth
10
5
0
-5
-10
-15
-8
-4
0
4
8
12
16
20
CPI Inflation
Linear Fitted Line
0.95 Ellipse
75
Figure 4.2.d: Scatter Plot and Polynomial Kernel Fit Curve in Four Countries of East
Asia
15
Real GDP Growth
10
5
0
-5
-10
-15
-10
0
10
20
30
40
50
60
CPI Inflation
4.4 Identifying a Threshold Level of Inflation
The recognition, at the operational level, that the relationship between inflation and
growth depends on the level of inflation is translated into the use of threshold
identification in the academic literature (see Espinoza, Leon & Prasad 2010, p. 3).
However, the rate of inflation at which its negative effects on growth dominate its
positive effects, making inflation detrimental to growth, remains a controversial issue
(Sepehri & Moshiri 2004, p. 192). Cross country studies carried out at the IMF such
as Khan and Senhadji (2001) and Espinoza et al. (2010) show the existence of a
threshold level of inflation in the context of developing countries. While Khan and
Senhadji (2001) suggest a level between 11 and 12 per cent, a slightly wider range of
7–13 per cent is suggested by Espinoza et al. (2010).57 Outside the IMF, studies such
as Sepehri and Moshiri (2004) notes that the range could vary between 11 per cent
and 15 per cent depending on the stage of development a country is in. These
57
Khan and Senhadji (2001, p. 16) also notes a positive effect of inflation on growth only present for
inflation rates lower than 18 per cent for developing countries. This is found by performing a test of
the sensitivity to the location of the threshold.
76
findings are discussed in Chapter 2. Generally, the cross-country literature suggests a
higher threshold for poorer countries.
In general, as summed up in Hwang and Wu (2011, p. 69) the techniques used to
identify the turning point of inflation in the nonlinear relationship between inflation
and growth include (a) certain benchmarks of inflation chosen arbitrarily, for
instance by Fischer (1993), (b) spline regression method, such as Sarel (1996), (c)
method of bootstrapping, for example by Khan and Senhadji (2001), and (d)
incorporating a quadratic term of inflation, as used by Pollin and Zhu (2006).
Findings of these cross-country studies provide a general view of threshold level in
developing countries. Policy makers in a particular country would be more interested
to know the evidence on a country specific context. The knowledge of such a turning
point of inflation helps maximise the high growth-low inflation objective. Table 4.4
lists some of the recent country-specific studies attempting to gauge the threshold
level of inflation in developing Asia. The selection of the studies is based on the
sample countries under investigation. A critical review of the analyses and findings
of the studies are provided below.
Table 4.4: Studies on Threshold Level of Inflation
Study
Empirical
Dependent
Approach
Variable
1960 –
Cointegration
Malik
2006
(2011)
(annual)
Hussain and
Country
Pakistan
Period
Regressors
Findings
Growth
Growth and
Threshold
and error
and
inflation
level at 9 per
correction
inflation
cent.
model
Hwang and
Wu (2011)
China
1986 –
Spline
2006
(annual)
Growth
Capital
Threshold
function
growth rate,
level at 2.5
regression
labour
per cent.
growth rate,
human
capital
growth rate,
and CPI
inflation rate
77
1972 –
Threshold
Growth
Lagged
Threshold
and Ham
2007
vector
and
values of
level at 10
(2009)
(annual)
autoregressive
inflation
growth and
per cent is
inflation
suggested.
Chowdhury
Indonesia
model
(TVAR)
Hayat and
Bangladesh
Kalirajan
1976-
Vector
Per capita
Literacy
No particular
2005
autoregressive
growth and
rate, life
threshold
(VAR) model
inflation
expectancy,
found. Rise in
agriculture
inflation from
value added,
any level is
gross capital
harmful for
formation,
growth
(2009)
export, and
government
consumption
as a
percentage
of GDP,
growth in
broad
money
supply, and
dummy
variables.
Munir et al.
Malaysia
(2009)
1970-
Threshold
2005
Growth
Inflation,
Threshold at
autoregressive
financial
3.89 per cent
(TAR) model
depth, gross
capital
formation
1981 –
Cointegration
Growth
Growth and
Threshold
Mortaza
2005
and error
and CPI
CPI inflation
level at 6 per
(2005)
(annual)
correction
inflation
Ahmed and
Bangladesh
cent.
models
Hussain
(2005)
Pakistan
1973 –
Threshold
2005
model
(annual)
Growth
CPI
No clear
inflation,
evidence of a
population
threshold
growth rate,
level is
investment
found. A
income
range of 4–6
ratio, and
per cent is
78
M2 GDP
suggested.
ratio
Mubarik
Pakistan
(2005)
1973 –
Threshold
2000
models
Growth
(annual)
CPI
Threshold
inflation,
level at 9 per
population
cent.
growth rate,
investment
growth rate
1950 –
OLS using a
and Siregar
1997
(2004)
(annual)
Chowdhury
Indonesia
Growth
A linear and
Threshold
quadratic
a squared
level at 20
specification
term of
per cent is
inflation
suggested.
1971 –
Cross
Per capita
Wholesale
No threshold
Kalirajan
1998
sectional
growth
price index
level of
(2003)
(annual)
regression
(WPI)
inflation is
inflation,
found. Any
rate of
increase in
rainfall,
inflation from
literacy rate,
the previous
population
period
growth rate,
negatively
private
affects
sector
growth.
domestic
Bringing
investment
down
(% of GDP)
inflation to
rate, public
single digit
sector
level, at par
domestic
with its trade
investment
partners’
(% of GDP)
inflation,
rate,
would help
government
increase the
consumption
per capita
expenditure
growth by
(% of GDP)
about 2
rate, terms
percentage
of trade
points.
Singh and
India
Notes: The studies are arranged first chronologically and then in alphabetical order.
79
Among the studies on inflation threshold, presented in Table 4.4, the highest level of
about 20 per cent is suggested by Chowdhury and Siregar (2004) in the case of
Indonesia.58 The study estimates the turning point in a nonlinear framework,
expressing growth as a quadratic function of inflation.59 However, the singleequation-OLS framework used in the study is subject to reverse causality problem
particularly when the study itself identifies a bi-directional causality between the two
variables. Thus, the study may overestimate the threshold level and the estimates
using a better methodology may produce a lower threshold.
For example, a much lower turning point between 8.5 and 11 per cent is found by
Chowdhury and Ham (2009) for Indonesia by using a threshold Vector
Autoregressive (TVAR) model. They have used annual data between 1972 and 2007,
acknowledging that the results are limited by small sample size and, therefore, their
investigation was exploratory in nature. Nevertheless, in light of the findings, the
authors argue that targeting a rate below 5 per cent, as set by the central bank of the
country, is “too much on the cautionary side…(appears) an overkill, and
hence…harmful for the economy” (p. 653). Additionally, they point out that
investment in Indonesia has declined as a result of high lending rates – a common
instrument to fight inflation. However, they did not investigate causes of the decline
in investment. Investment depends on both real cost of borrowing and expectations.
It is not clear whether investment has declined due to high real cost of borrowing, as
claimed by Chowdhury and Ham (2009), or due to poor expectations resulting from
uncertainty in economic recovery.
On the empirical side, the achievement of Chowdhury and Ham (2009) is to employ
a superior econometric method (compared to OLS) – the threshold VAR trying to
capture the structural break – the level at which inflation turns detrimental. The
authors carefully take the outliers in the inflation series into consideration by
incorporating a pulse dummy. However, there seems to be a number of limitations in
the empirical methods used by them. For instance they employ inflation and growth
58
The study, as mentioned in the previous section, finds a positive relationship between inflation and
growth, excluding inflation outliers, and no relationship when inflation is in the range of 8 – 15 per
cent.
59
Pollin and Zhu (2006) also used this standard technique of finding the turning point of a quadratic
function.
80
rates in an unrestricted VAR framework. It is argued as appropriate on the ground
that the rates are stationary variables and, therefore, spurious regression is avoided.
However, it does not provide any information on the nature of stationarity of the
level variables of inflation and growth – price level and output level respectively. If
the price level and output level are non-stationary but cointegrated then the
appropriate framework is a restricted model – Vector Error Correction Model
(VECM). An unrestricted model using the first differences (inflation and growth),
even though they are stationary, is not considered a correctly specified model in the
presence of cointegration. Secondly, Chowdhury and Ham (2009) argue for selecting
a short lag-order so that the estimation does not lose degrees of freedom. It does not
follow the standard lag order selection criteria such as AIC or BIC to determine the
appropriate lag length to remove autocorrelation. The model’s adequacy, therefore,
becomes rather weak.
The difference between the suggested threshold levels in a particular country context
is indeed noticeable. Considering that Indonesia’s historical median inflation rate is
10.46 per cent the findings of Chowdhury and Ham (2009) appear to be more
consistent than what is suggested by Chowdhury and Siregar (2004). However,
Indonesia is an inflation prone country; yet, showed the capacity to expand in a
relatively high inflationary situation in the past. Therefore, the stylised fact that
countries in a higher development phase should have a lower threshold level of
inflation may not hold in the case of Indonesia. A comparison between Indonesia’s
long run median inflation rate and that of three South Asian countries reveals some
support for this (Figure 4.3). Indonesia is ahead of these countries in terms of
economic development (a higher average per capita income and long run median
growth rate as well) but has a relatively higher inflation experience.
81
Figure 4.3: Inflation and Growth in Selected Countries (Long Run Median in per cent)
4.98
Pakistan
7.52
7.15
5.96
Indonesia
Long Run Median Growth
8.34
10.46
Median Inflation in the
2000s
5.47
4.32
India
Long Run Median Inflation
7.16
4.72
6.22
Bangladesh
8.4
0
5
10
15
Source: Author’s calculation based on data gathered from IMF, International Financial Statistics and
World Bank, World Development Indicators.
A threshold level of 6 per cent is suggested by Ahmed and Mortaza (2005) for
Bangladesh, using annual data between 1981 and 2005. The measure of threshold is
an important contribution, perhaps first of its kind in the case of Bangladesh. This
initiative provides some clear empirical evidence to the policy makers, helping them
to conduct monetary policy. To achieve better results, its empirical estimation
carefully ignores the outliers in the inflation and growth series of the 1970s. The
outliers arise from unusual circumstances in the history of the country around that
time.60 The empirically derived threshold level, however, is not consistent with the
historical experience of the country. Long run median inflation for Bangladesh is 8.4
per cent, (see Figure 4.3). Besides, the experience of the last two decades shows that
growth has gone up steadily from 4.78 to 5.77 per cent, to a historical high, when at
the same time inflation has increased from 5.75 to 6.22 per cent. In other words,
there is no strong evidence from the historical data that growth has declined when
inflation has crossed the 6 per cent margin. The suggested threshold level of 6 per
cent or below appears to be very conservative also, considering the findings for other
countries for instance India, Indonesia, and Pakistan (see Table 4.4). Bangladesh falls
60
In 1971 after a war Bangladesh became independent. In 1974 the country suffered from famine and
severe flooding.
82
at a much lower path of development among these countries and therefore likely to
have a higher threshold level (see Figure 4.4 which shows that countries with lower
per capita GDP tend to have higher long run inflation).61 For the same reasons the
comments by Hossain (2010) is also not well founded. Hossain (2010) comments
that for Bangladesh the level of threshold would be much lower than what is
proposed by Khan and Senhadji (2001) for developing countries (11–12 per cent).
Figure 4.4: Scatter Plot between Average Real GDP Per Capita and Long Run Inflation
12
Indonesia
Long Run Median Inflation
10
Bangladesh
Sri Lanka
8
The Philippines
Pakistan
6
India
4
Nepal
Malaysia
Thailand
China
2
0
0
500
1000
1500
2000
2500
3000
Average Real GDP Per Capita
Source: Author’s calculation using data from World Bank, World Development Indicators and
International Monetary Fund, International Financial Statistics.
Note: Only the countries for which long data series are available are included. Both median inflation
and average real GDP per capita are calculated over the period of 1960 – 2009. For Bangladesh the
period is 1971 – 2009.
On the empirical side, Ahmed and Mortaza (2005) have used the techniques
developed by Khan and Senhadji (2001) – a bivariate model using dummy variable
to capture the structural break. Using a bivariate model would be subject to the
problems of omitted variable bias as mentioned above and perhaps a superior method
61
6 per cent is also lower than what is suggested by Khan and Senhadji (2001) and Espinoza et al.
(2010) for developing countries.
83
would have been to estimate a multivariate model using instruments to avoid
simultaneity bias.
Evidence from the other countries of the South Asian subcontinent also provides
some interesting facts. For Pakistan two studies carried out at the same time find
contrasting results. For example, Mubarik (2005) suggests a turning point of inflation
at 9 per cent. Hussain (2005), on the other hand, criticises Mubarik’s (2005) results
and finds no clear threshold level. He suggests a “tolerable” level would be in the
range of 4–6 per cent in the presence of both supply and demand shocks.
Like many contemporary studies Mubarik (2005) too is inspired by the work of Khan
and Senhadji (2001) and follows its framework. The measure of threshold point, 9
per cent, appears to be close to the findings (11-12 per cent) of Khan and Senhadji
(2001) whose sample includes Pakistan. Mubarik’s (2005) empirical model consists
of four variables – economic growth, inflation, population, and total investment
growth rates. He, however, does not include any policy variables, monetary or fiscal,
in the model. As a result the dynamics of how inflation and growth gets affected by
policy instruments, such as money supply, interest rates, exchange rate, and fiscal
deficits, remains unclear. In the case of data transformation, Mubarik (2005) uses
Hodrik Prescott (HP) filter to further smoothen the data.62 He argues that there is still
enough volatility in the variables even after log transformation.63
In the other study on Pakistan, Hussain (2005) criticises the use of HP filter to
smoothen the data series and measure the output gap. Although the use of HP filter to
remove volatility in growth is a common technique in econometric literature,
Hussain (2005) points out that it lacks substantive economic content and often
embodies problems relating to estimation in the presence of autocorrelation. Unlike
Mubarik (2005), Hussain (2005) includes policy variables such as money supply
GDP ratio within its multivariate framework and, therefore, provides somewhat a
stronger basis in explaining the effects of monetary instruments. However, relying
only on a monetary framework, which the model does, may suffer from problems of
62
Using HP filter to remove volatility in growth is a common technique in economic literature.
Log transformation is particularly useful when data series are erratic in nature. Smoothing using log
helps reduce the influence of outliers.
63
84
sufficient explanatory power. For instance, Khan and Sakib (2012) suggest that
monetary determinants are rather marginal and discard monetary growth as a
potential cause of high inflation in Pakistan. A variable such as political instability
has a much greater power in explaining inflation in the country, as they suggest.
The other key shortcoming of the study by Hussain (2005) is perhaps the suggestion
of the lower bound of threshold level at 4 per cent. Given the historical median
inflation rate at around 7 per cent and 11–12 per cent threshold suggested by Khan
and Senhadji (2001) (whose sample includes Pakistan) this seems to be quite a
conservative suggestion. The upper bound of the threshold range at 6 per cent may
find some rationale from the long run experience of Pakistan. The highest decadal
growth, in Pakistan’s history, was registered in the 1980s at 6.4 per cent when
inflation remained at 6.2 per cent. Other high inflationary episodes recorded a lower
associated growth. Another limitation of this study is that it fails to differentiate
between the sources of inflation while suggesting the threshold. The discussion of the
possible unwarranted effects of keeping inflation at such a low level in the presence
of supply shocks remains absent in the study.64
Similar to the findings of Hussain (2005), Singh and Kalirajan (2003), using annual
data from India for the period 1971–1998, strongly suggest that there is no threshold
level. Inflation is said to be harmful and any increase in inflation from any level has
negative effect on growth. This is indeed a very strong statement, not found in the
wider literature, and contrary to the historical experience of the country. Singh and
Kalirajan (2003) suggest that monetary policy in India should be focused towards
maintaining price stability. This is in sharp contrast to the suggestion made by Jha
(2008). Jha (2008) argues that in the presence of widespread poverty monetary policy
targeting low inflation cannot be appropriate for a country such as India.
The empirical model of Singh and Kalirajan (2003) uses cross sectional regression,
within a multivariate framework, and suggest that policy should always create a
downward pressure on inflation, “without having to worry about what the threshold
level is” (p. 393). The authors note that average annual inflation in India during the
64
Even studies carried out at the IMF such as Selassie et al. (2006) underscore the importance of this
aspect of countercyclical monetary policy (see Chapter 3).
85
sample period was 8.2 per cent, higher than that of most of its major trading partners
(all of which are developed countries). Their results indicate that bringing down
inflation at a very low level, close to that of its trading partners in the developed
world, would help increase the per capita growth by about 2 percentage points.
However, they fail to address the idea that inflation-growth profiles vary
significantly between developing and developed countries, for instance as suggested
by Sepehri and Moshiri (2004). Therefore, targeting the same inflation rates of the
trading partners such as the USA and Germany may have serious negative
consequences for India.
The result by Singh and Kalirajan (2003) that any increase in inflation is harmful
also contradicts with nonlinear nature of relationship between inflation and growth.
Historical evidence suggests that India managed to sustain growth rates higher than 5
per cent at a time when inflation was around 9 per cent.65 Both Hussain (2005) and
this study appear to have found similar results – no clear threshold level and inflation
having a universal negative impact on growth – from their empirical results. The
methods used in both studies do not explain clearly how they take care of the
extreme values of inflation due to, for instance, a crisis or a shock. It is evident from
Figure 4.1a that both India and Pakistan experienced high inflationary episodes
during the early 1970s, at the time of first oil price shock. The results investigating
the growth-inflation relationship could have been driven by the outliers in inflation
data, as noted and explained by Bruno and Easterly (1998).
The discussion on threshold level provides some interesting insights. The studies
suggesting low inflation threshold level, for instance Ahmed and Mortaza (2005),
Hussain (2005), and Singh and Kalirajan (2003), seem to be influenced by the
decadal inflation experience of the 2000s. Figure 4.2 shows that in all cases inflation
in the 2000s was less than its historical figures (except for Pakistan where both
figures were close). The countries, in general, experienced low inflation in the 2000s,
but this should not be the benchmark for setting the threshold standard (Anwar &
Islam 2011). In addition, for most of the countries (except for India) the inflation
65
The decadal average growth rates of the 1980s and 1990s in India were 5.44 and 5.69 per cent
(increasing) respectively, when inflation rates were 8.76 and 9.59 per cent (also increasing)
respectively.
86
rates in the 2000s were higher than 5 per cent. The findings of most of the above
studies reviewed also suggest a threshold above 5 per cent. In short, there is no
strong evidence in support of the IMF’s claim, that countries require their inflation to
be below 5 per cent to generate long term growth.
The findings also provide strong evidence against one size fits all policy. The advice
to keep inflation at a very low level for all countries is not supported by different
threshold findings for different countries. It is also interesting to note different
threshold findings for the same country. This could be due to modelling issues such
as univariate or multivariate framework and selection of explanatory variables; and
methods of empirical estimation taking into account reverse causality and effects of
outliers or the sample size and period covered.
4.5 Experiences with Policies Targeting Low Inflation
Emerging and developing economies, following the experience of developed
countries, have started to adopt an inflation targeting approach to monetary policy to
maintain price stability in recent years (Mishra & Mishra 2012a). There is a pressure
on developing countries from the IMF to target low inflation and gear policy
instruments accordingly. This section reviews the issue of inflation targeting at a low
level in the context of the sample countries. Table 4.5 lists some of the recent studies
incorporating the experiences of low inflation targeting in developing Asia.
Table 4.5: Studies on Low Inflation Targeting
Study
Country
Period
Empirical
Dependent
Approach
Variable
Inflation
Regressors
Findings
Lagged
Inflation
Gerlach
Indonesia,
1985: 1 –
Hansen’s mean
and
Philippines,
2010: 1
unbiased
values of
persistence has
Tillmann
Thailand,
(quarterly)
estimator of
inflation
declined
(2012)
China, and
the sum of
because of
Malaysia
autoregressive
pursuing
(among
coefficients
inflation
others)
targeting and
therefore IT
87
can be
successfully
adopted by
emerging
market
economies.
1996:1 –
Instrumental
WPI
Output gap,
Flexible
and
2007:3
variable-
inflation
WPI
domestic
Mishra
(monthly)
generalised
and output
inflation,
inflation
method of
gap
expected
targeting is
moments (IV-
WPI
seen as a better
GMM)
inflation,
alternative
real
compared to
effective
strict one in
exchange
the presence of
rate, real
insufficiently
interest rate
integrated
Mishra
India
(2012a)
financial
markets and
rigidities in the
economy.
1996: 1 –
Vector
WPI
World oil
Inflation
and
2005: 3
autoregressive
inflation
prices,
targeting
Mishra
(monthly)
model (VAR)
federal
framework is
funds rate,
suggested to
output gap,
achieve a
WPI
better
inflation,
monetary
exchange
management.
rate,
The pass
monetary
through of the
policy
international
instruments
supply shocks
(growth
to domestic
rate of
inflation is
reserve
fast.
Mishra
(2012b)
India
money,
M0, yield
of 91 day
treasury
88
bill rate,
and call
money
rate), gross
bank credit,
and broad
monetary
aggregates
(M3)
Siregar
Indonesia
1990s: 1 –
Autoregressive
and Goo
and
2008: 12
(2010)
Thailand
(monthly)
Inflation
Nominal
Pursuing the
distributed lag
effective
inflation
(ARDL) model
exchange
targeting
and Mark
rate, world
policy is seen
switching
inflation
as successful.
model
rate, and
Inflation has
openness
gone down in
the post-IT
period. The
pass through
effects has
declined
considerably
except for
tradable goods
prices of
Indonesia.
Jha
(2008)
India
1992: 4 –
Vector
WPI
Industrial
The rationale
1998: 3
autoregressive
inflation
production
for introducing
(monthly)
model (VAR)
growth,
inflation
and Granger
real
targeting as an
causality test
effective
exclusive
exchange
concern for
rate,
monetary
narrow
policy is
money, call
inappropriate
money rate,
particularly in
CPI for
the presence of
industrial
widespread
workers.
poverty. IT
would not be
89
effective, even
if adopted in
the monetary
policy, since
short term
interest rate
does not have
a significant
effect on
inflation.
Notes: The studies are arranged first chronologically and then in alphabetical order.
In the presence of widespread poverty the objective of monetary policy cannot be
exclusively inflation control. This argument is put forward by Jha (2008) which
evaluates the case for IT in India. Jha argues that poverty and its alleviation should
be the “cornerstone of success of any policy” in a country which has a long standing
problem of poverty. He believes “higher economic growth along with some
supporting redistribution measures” can play a crucial role in reducing poverty.
Crucially, Jha (2008) notes that the rate of poverty reduction was higher in the 1980s
compared to the reform period of post 1991.66 Although the trend has been reversed
later, he believes that there exists enough scope for poverty reduction through higher
growth. A rapid reduction in poverty in India is attainable through a sustained
economic growth of 8 per cent (Jha 2008, p. 260). The two important issues the
monetary policy should address in this regard are interest rate and exchange rates.
Jha (2008) suggests that low interest rate, to generate investment, and a slightly
undervalued exchange rate with low volatility, to boost exports, are critical to
sustaining high growth rates (p. 260).
Jha (2008) also argues that the rationale for IT is incomplete in India. There is
evidence of sacrifice in terms of output loss as a result of pursuing IT. Output
movements in transition countries adopting IT have been higher than in developed
market economies, Jha notes. Therefore, following the footsteps of the developed
countries in pursuing IT cannot be justified. In addition, he argues that although IT
may have been responsible for maintaining a low inflation regime, it has not brought
66
India suffered a balance of payment crisis in 1991.
90
down the inflation rate itself substantially or changed the volatility of the exchange
rate.
The potency of monetary policy in targeting inflation is also questioned by Jha
(2008). He identifies price level stabilisation as an overriding short term concern of
monetary policy in India. However, the causality tests show that short term interest
rate – the key instrument with which monetary policy targets inflation – does not
have a significant effect on inflation.67 Therefore, Jha (2008) concludes that the
central bank of India could not implement IT effectively even if it wants to. The
reason behind this result, Jha (2008) argues, is that monetary policy in India is
constrained by a number of issues, such as incomplete liberalisation of financial
markets. The interest rate transmission channel is incomplete due to these limitations.
Because financial market liberalisation is not complete a strong monopoly elements
still exists in the banking system. Mishra and Mishra (2012a, p. 1053) also point out
that financial markets in India are still not sufficiently integrated to ensure quick
transmission of interest rate impulses (supported by low sensitivity of demand) and
there are still rigidities in the economy, as indicated by a flat Phillips curve. In the
presence of such anomalies Jha (2008) supports the multiple indicator approach of
monetary policy adopted by the central bank of India in April 1998.68 Such policy
direction, as he suggests, would help maintain stable interest and inflation rates and a
slightly undervalued currency in order to promote higher export led growth.
The above discussion reveals why rule based interest rate policy, particularly of
Taylor type, may not be efficient to stabilise a developing economy. This is also
supported by Mishra and Mishra (2012a). The study attempts to answer the question
of the probable consequences of shifting to an inflation targeting framework of
monetary policy and how different shocks will affect the economy under such
framework. It uses a general linear model of the economy with quadratic loss
function to be minimised by the central bank for India. The results of the study
67
Granger causality tests indicate a weak relation between call money rate and measures of inflation.
Empirical investigation of the paper raises a question though. Call money rate is found to be I(1), a
non-stationary series possessing unit root. In a finite sample (April, 1992 – March, 1998) it is unusual
that the rate has unit root.
68
The key objectives of this policy include (1) a stable inflation environment, (2) appropriate liquidity
condition to support higher economic growth, (3) orderly conditions in the exchange rate market to
avoid excessive volatility in exchange rate, and (4) stable interest rates (RBI 2002 cited in Jha (2008,
p. 264)).
91
indicate a short run trade-off between inflation and output because of the presence of
rigidities in the price setting behaviour. In light of the above results, they suggest that
flexible domestic inflation targeting and discretionary optimisation in monetary
policy would work better for economic stabilisation in India.
However, in another study, Mishra and Mishra (2012b) suggest that the IT
framework helps achieve better monetary management. They build a short run
comprehensive VAR model of monetary policy for the Indian economy to examine a
hypothetical inflation targeting monetary policy regime.69 The authors note that the
multiple indicator approach of monetary policy is not efficient because “the
multiplicity of objectives leads to inherent conflict among such objectives … in
particular between exchange rate stabilization and inflation stabilization” (p. 87). It
creates confusion in the market which remains unsure of which variable the central
bank will choose to defend.
The empirical estimation of Mishra and Mishra (2012b) is based on two models.
First a benchmark case is constructed in line with the multiple indicator approach
currently practiced by the central bank of India. In this case, the monetary policy
instrument is set after looking at current values of inflation, output, and exchange
rate. The second model is a pure inflation targeting case. Here, monetary policy
instruments are allowed to react to inflation only contemporaneously. The results
suggest that demand effects of changes in interest rate are stronger than exchange
rate effects. The increase in interest rate (or negative monetary shocks) does not
appreciate the exchange rate as much in the inflation targeting scenario as in the
benchmark case. This helps mitigate the potential conflict between exchange rate and
interest rate, one of the main monetary policy dilemmas in inflation targeting, as the
study suggests. However, the interpretation is not consistent with the results
presented in their study. The impulse response functions under both baseline and
inflation targeting models (see Figure 1 and 2, p. 93 and p. 95, respectively) show an
important fact. Of the five variables – inflation, output gap, nominal effective
exchange rate, growth in bank credit, and money supply growth – on which response
of call money rate shock is tested, only the response in growth in bank credit appears
69
The study is an extension of their work, Mishra and Mishra (2009), in which they suggest that the
Indian economy satisfies the preconditions for inflation targeting.
92
to be significant. None of the responses in other variables appear significant. In short,
interest rate does not appear to be effective in controlling inflation. This is consistent
with the conclusion drawn by Jha (2008) which also finds interest rate being
ineffective in creating a response to inflation in India.
Monetary policy in developing countries grapples with the dilemma relating to
inflation, interest rate, and exchange rate, as mentioned above. This is evident in the
case of Indonesia and Thailand as noted in Siregar and Goo (2010). In the case of
Thailand, the monetary authority shifted to a full IT rule from the IT framework –
defined as a flexible approach to the IT policy, during the volatile period. As for
Indonesia, managing exchange rate volatility continues to be one of the objectives of
interest rate policy in addition to anchoring inflationary expectation. Siregar and Goo
(2010) evaluate the overall performance of the IT regime adopted by Indonesia and
Thailand after the Asian Currency Crisis 1997-98. The results demonstrate that the
IT regime in these two economies has had some success, but not during the
immediate aftermath of the Lehman Brothers’ collapse in 2008, in the run up to the
global financial crisis and the Great Recession. Their test results seem to suggest that
during the volatile period, covering the era of Asian Currency Crisis 1997-98 and its
aftermath and the Global Financial Crisis 2007-08, the output gap did not
significantly influence the interest rate policy of both Bank of Indonesia and Bank of
Thailand.
Siregar and Goo (2010) also note that there seems to be no trade-off between
inflation and economic growth, covering monthly data for the two periods – two
years before and after the implementation of IT. The average GDP growth rates as
they note of Indonesia and Thailand after two years of implementing IT were
significantly higher and less volatile (smaller standard deviations) than the rates in
two years prior to IT. These results, however, do not seem to be consistent with the
descriptive statistics using annual data presented in Table 4.6. To test the validity of
the claims made by Siregar and Goo (2010), Table 4.6 presents some descriptive
statistics (5 year averages) from two periods. The two periods are 1992–96 and
2002–06, pre and post IT-start in the two countries.70 A five year period average is
70
Both countries started implementing IT in the year 2000.
93
considered, assuming that it will reasonably capture the effects. The turbulent periods
of Asian Currency Crisis (1997-98), Global Financial Crisis (2007-08) and the Great
Recession (2008-09) are omitted to avoid any outlier effects.
Table 4.6: Inflation and Growth Statistics in Indonesia and Thailand Pre and Post IT
Implementation
1992 – 1996
2002 – 2006
(5 year average)
(5 year average)
Country
Indonesia
Thailand
Statistics
Inflation
Growth
Inflation
Growth
Mean
8.63
7.33
9.65
4.97
SD
0.92
0.44
3.11
0.47
CV
0.11
0.06
0.32
0.09
Mean
4.82
7.78
2.89
5.54
SD
1.09
1.23
1.72
0.97
CV
0.23
0.16
0.60
0.18
Source: Author’s calculations based on data from World Bank, World Development Indicators and
IMF, International Financial Statistics.
The superior growth performance after the implementation of IT in Indonesia and
Thailand as claimed by Siregar and Goo (2010) does not seem to be valid when we
analyse the growth averages using annual data.71 Growth rates in both countries are
less in the post IT period. In Indonesia, it has gone down from 7.33 per cent to 4.97
per cent while in Thailand, the figure drops from 7.78 per cent to 5.54 per cent
(Table 4.6). Coefficient of variation, which is a better measure of volatility in
variables compared to standard deviation, shows similar results. Output growth
volatility has gone up in both countries in the post IT era (see Table 4.6). Although
the mean inflation has dropped in Thailand in the post IT era, the same did not
happen in Indonesia. Perhaps a more strict IT rule followed by Thailand is
responsible for the decline in average inflation.72 Interestingly enough, IT does not
seem to cause inflation volatility to go down. In fact, the volatility, as measured by
71
Siregar and Goo (2010) use monthly data set.
As Siregar and Goo (2010) note that Indonesia pursued a less strict IT rule, paying attention to
managing its exchange rate volatility also. Developing countries do so to maintain its competitiveness
in export market. The figures of inflation target in the two countries reveal that Thailand followed a
strict IT compared to Indonesia. According to Table 2 (p. 115) of the paper inflation target level
during the 2000s was set between 3 per cent and 10 per cent in Indonesia and between 0 and 3.5 per
cent in Thailand.
72
94
the coefficient of variation, has risen in both countries after the implementation of IT.
In short, the statistics presented in Table 4.6 show a considerable loss in output
(evident from declining growth rate and higher output growth volatility) after
pursuing a narrow IT based policy.
Similar to Siregar and Goo (2010) a cross country study by Gerlach and Tillmann
(2012) suggests that inflation persistence has declined in the economies using IT but
not elsewhere. They explore how successful monetary policy incorporating inflation
targeting is, in terms of bringing down persistent inflation shocks, in a sample of
economies in Asia-Pacific. For the purpose of comparison, the sample includes
countries practising IT, such as Indonesia, Philippines, and Thailand (among others),
and countries without IT, including China and Malaysia (among others). The study is
motivated by the observation that the introduction of monetary policy strategies
focused on achieving low and stable inflation is associated in many countries with a
sharp decline in the persistence of inflation shocks. The important conclusion is that
inflation targeting outperforms alternative strategies, such as exchange rate pegs and
‘eclectic’ strategies, when performance of monetary policy is measured in terms of
inflation persistence rather than the level of inflation. Gerlach and Tillmann (2012),
therefore, support that IT can successfully be adopted by emerging market
economies. A significant innovation of the study is that it measures inflation
persistence by the sum of the coefficients in an autoregressive representation of
inflation using the median unbiased estimator developed by Hansen (1999). Thus far,
as they argue, the literature on inflation persistence in emerging market countries
mostly relies on OLS estimates of the AR(1) coefficient. The least squares estimate
suffers from a bias as the sum of the autoregressive coefficients approaches unity.
Moreover, confidence bands based on a normally distributed estimator do not have
correct coverage. Gerlach and Tillmann (2012) underscore the importance of reliable
confidence bands to check whether persistence falls over time. The use of Hansen’s
(1999) grid-bootstrap estimator solves these issues.
In the sample Asian economies, after the Asian Financial Crisis of 1997 – 1998, the
drop in the persistence is particularly large in those economies that formally adopted
IT as a monetary policy strategy. It is important to note from the findings of Gerlach
and Tillmann (2012) that the fall in the inflation persistence is not synchronised
95
across IT countries. Inflation persistence in Thailand falls immediately after the new
monetary regime became effective. For the Philippines, however, a substantial
reduction occurs only at the end of the sample period. Likewise persistence in
inflation in Indonesia falls much later than in other countries. These facts raise a
number of questions about the conclusion drawn by Gerlach and Tillmann (2012).
First, even if a country follows IT the fall in persistence may take time. In that sense
policies, such as higher interest rate and tighter credit control aimed at reducing the
persistence, may involve a high sacrifice ratio in terms of loss in output. Secondly,
one may ask how important this result is in a general macroeconomic perspective.
Even though inflation has come down more rapidly in the IT countries (for instance
Indonesia, Thailand, and The Philippines) their economic performance is less
impressive compared to non-IT counterparts (for example China and Malaysia).73 So
reducing inflation persistence cannot be an end in itself. It should be a means to
reach the objective of growth and economic development.
In sum, the above discussion provides insights on a number of issues. There is much
evidence that countries trying to keep inflation at a very low level have to sacrifice in
terms of growth. This is evident from higher growth volatility. Monetary policy also
faces a dilemma in controlling inflation and maintaining export led growth. Tight
monetary policy using higher interest rate trying to curb inflation may cause
appreciation of domestic currency. This negatively affects competitiveness in the
international market and hampers export led growth.
4.6 Determinants of Inflation: Demand Driven versus Supply Side
The cause of inflation whether it arises from demand or supply side factors is
important in determining monetary policy stance. In the event of a supply shock
inflation which also causes drop in output, a tight monetary policy to fight inflation
may have unwarranted consequences. It may cause output to fall further, leading to
rise in unemployment and poverty. With reference to India’s attempt to address
recent food price inflation, a former World Bank economist Surjit Bhalla says “Let’s
73
Malaysia is ranked highest amongst these Asian countries according to the Human Development
Index (HDI) 2011.
96
kill GDP, inflation will fall.”74 Table 4.7 records some of the recent studies relating
to this issue in the context of the sample countries of Asia.
Table 4.7: Determinants of Inflation
Study
Empirical
Dependent
Approach
Variable
Computable
Macro
wa and
general
variables
(supply side
Bandara
equilibrium
such as
factor) would
(2012)
model (CGE)
employmen
have an
t, real
overall
export, real
negative
imports,
impact on the
real
country’s
household
growth and
consumptio
poverty.
n, real
Complementa
GDP, terms
ry policies
of trade,
such as fuel
and
subsidy
household
scheme,
level
targeting low
absolute
income
poverty
groups are
Naranpana
Country
Sri Lanka
Period
n.a.
Regressors
Findings
Oil price
High oil price
suggested as
necessary.
1951 –
Generalised
CPI
Lagged
The effects of
Saqib
2007
Method of
inflation
inflation
monetary
(2011)
(annual)
Moments
rate, broad
determinants
(GMM)
money
on inflation
supply (M2)
are ‘marginal’
growth rate,
and political
growth rate
instability is
of credit to
positively
private
associated
sector,
with inflation.
Khan and
Pakistan
74
Source: The Financial Express, 15 October 2011; available via the internet at
http://www.financialexpress.com/news/column-let-s-kill-gdp-inflation-will-fall/860148
97
growth rate
of budget
deficits,
agricultural
output, trade
share,
growth rate
of real GDP
per capita,
growth rate
of oil price,
government
crisis, and
cabinet
changes
2000 –
Generalised
Nominal
Output gap,
Loose
and Rosario
2010
method of
interest rate
long run
monetary
(2010)
(quarterl
moments
inflation
policy is seen
y)
(GMM)
target, other
as a cause
variables
behind high
such as
inflation
exchange
during the
rate, money
GFC of 2007
growth, and
– 2008.
Ramayandi
Indonesia
international
interest rate
Jongwanich
Developin
1996: 1 –
Vector
Oil and
Shocks
Against the
and Park
g Asia
2009: 1
autoregressiv
food price
correspondi
backdrop of
(quarterl
e (VAR)
inflation,
ng to
GFC 2007-
y)
model
output gap,
demand,
2008, Asia’s
change in
supply,
inflation is
exchange
exchange
largely home-
rate
rate, import,
grown and has
producer
arisen due to
and
excess
consumer
aggregate
price
demand and
inflation
inflationary
(2009)
expectations
rather than
98
external price
shocks.
Monetary
policy is seen
as a powerful
tool to combat
inflation.
Islam
Banglades
1987 –
Descriptive
(2008)
h
2007
analyses
n.a.
n.a.
High
commodity
(annual)
price, supply
side
constraints in
the
commodity
markets, and
undervaluatio
n of currency
are the main
causes of
inflation.
Noneconomic
factors such
as corruption
and political
uncertainties
are also
responsible
for inflation.
Lim (2008)
Philippine
1950 –
Descriptive
s
2007
analysis
(annual)
n.a.
n.a.
Inflation is
mostly due to
supply side
causes and an
alternative
monetary
policy to
inflation
targeting is
required,
encompassing
a more
99
development
oriented
programme.
Siregar and
Thailand
1985 –
Autoregressi
CPI
Nominal
Loose
Rajaguru
and
2001
ve distributed
inflation
effective
monetary
(2005)
Indonesia
(annual)
lag (ARDL)
exchange
policy,
model
rate, GDP,
particularly
domestic
supply of
interest rate,
narrow
foreign
money,
interest rate,
explains the
money
severe
supply (M0)
inflationary
(and
others)
pressure in
Indonesia
during the
Asian
Financial
Crisis of
1997-98
compared to
other
countries
studied in the
paper.
Management
of base money
and exchange
rate volatility
is important in
achieving
overall price
stability.
1984: 2 –
Structural
Change in
Lagged
Adoption of
Ward
1999: 1
vector
nominal
values of the
IT in
(2002)
(quarterl
autoregressiv
exchange
dependent
monetary
y)
e (SVAR)
rate, money
variables
policy may be
model
growth,
effective in
change in
future. Since
short term
demand
Siregar and
Indonesia
100
interest
shocks are
rate, real
more
output
important
growth,
than supply
inflation,
shocks,
change in
government
world short
can play a
term
greater role
nominal
using fiscal
interest
policy.
rate, and
world
inflation
rate
Notes: The studies are arranged first chronologically and then in alphabetical order.
Lim (2008) supports the view that the inflation experience in the Philippines has
been mostly a supply led and cost push phenomenon. He argues this just by using
two types of supply side shocks – currency depreciation and oil price shock – one
can explain practically all the above-10 per cent inflation in modern Philippine
history. High inflation periods are not triggered by high domestic demand but by
supply shocks. Lim (2008) also argues that if one uses monthly or quarterly data on
inflation one will also see that agricultural price shocks make their impact on price
inflation due to weather disturbances leading to food shortages. He documents that
even with a lax monetary policy, lending to the private sector has not increased
adequately amid fiscal difficulties; this contributes to lagging investment and
employment creation. Monetary policy is not independent from the other macro
sectors as well as the real and external sectors of the economy. Lim (2008) therefore
proposes alternative monetary policies to IT that take into consideration the bigger
and more complex role of monetary policy in an economy that requires a more
development promoting programme. He argues that high liquidity and large
monetary expansion in the mid-1990s did not have any impact on inflation (which
remained below double digits and continued to decline until the Asian Currency
Crisis 1997-98) because of the financial liberalisation. As a result of financial
liberalisation the link between quantitative monetary targets and inflation had
101
weakened. This is because of the structural breaks in the income velocity of money
and volatilities and instabilities in the money multiplier.
A contrasting view of the cause of inflation is expressed by Jongwanich and Park
(2009). They test whether inflation surge in developing Asia during 2007 – 2008 was
primarily the result of external price factors such as oil and food shocks. Their
empirical result suggests that inflation is largely home-grown and has arisen because
of excess aggregate demand and inflationary expectations, rather than external price
shocks. They, therefore, suggest that the monetary policy is a powerful tool in
fighting inflation in Asia. This argument is based on the premise that monetary
policy is potent in controlling inflation expectation regardless of the cause of it,
demand pull or cost push factors. Jongwanich and Park (2009) divide the inflation
drivers into cost push factors, mainly international oil and food prices, and demand
pull factors, mainly excess aggregate demand and inflation expectations proxied by
output gap and lagged domestic inflation respectively. Using variance decomposition
analysis they show that excess aggregate demand and inflation expectations account
for much of the consumer price inflation in the nine Asian countries studied.75 For
instance over a year more than 20 per cent consumer price inflation variation in
Indonesia and Malaysia resulted from demand pressure. Inflationary expectations
explain around 60 per cent of consumer price variations in Malaysia. On average the
two non-external factors jointly explain about 60 per cent of consumer price inflation
in the region as a whole. The external cost push factors, oil and food prices, on the
other hand explain only around 20 per cent of the variation in consumer price
inflation.
Jongwanich and Park (2009) note that the emergence of excess demand during this
period was in part caused by lax monetary policy and sustained balance of payments
surplus in many Asian countries. The resulting expansion of domestic liquidity
helped fuel both the growth of aggregate demand and an increase in the output gap
ratio. Just as importantly easy monetary policy, as evident from declining nominal
75
The phenomenon has a rationale which the authors have not mentioned. The rising aggregate
demand makes sense since these economies are growing as they are trying to come out of the
adversities of the crisis.
102
lending rates, has eroded the anti-inflationary credibility of monetary authorities and
thus contributed to the formation of higher inflationary expectations.
Empirical evidence on the relative importance of aggregate demand shocks over
aggregate supply shocks in affecting macroeconomic fluctuations is also found in
Siregar and Ward (2002). Based on an open economy model, they investigate the
issue in the case of Indonesia. In an earlier study, Siregar and Ward (2001), based on
a closed economy model, noted the opposite result. In Siregar and Ward (2001) the
fluctuations are predominantly explained by shocks to aggregate supply with
aggregate demand shocks playing a lesser role. The drawback of this study, as their
later study notes, is the failure to capture the explicit transmission mechanisms for
foreign shocks to affect the economy. The later study also suggests that monetary
policy would not be totally effective as a measure for targeting output levels or
economic growth. The results show that output effects of monetary policy shocks are
small and statistically significant only in the short run. It may however, be useful in
stabilising demand side variables, particularly inflation rate. The limited role of
aggregate supply shocks in determining fluctuations in the variables may be a
reflection of serious supply side bottlenecks in the economy. Besides, due to data
limitations the study does not cover the two major oil price shocks (1973 and 1979)
which had been favourable to the Indonesian economy to some extent.
Although the findings of the above studies do not put much emphasis on the impact
of food and oil prices, they may have considerable effects on inflation in food and oil
importing developing countries. Naranpanawa and Bandara (2012) note that oil and
net food importing developing countries were severely affected by food and oil price
shocks in 2007 and 2008 creating negative impact on poverty, growth, and inflation.
Using simulated results they find that high oil price in Sri Lanka has led to a decline
in demand for imported and domestic commodities and a fall in investment, leading
to a reduction of real GDP by 3.14 per cent. Higher oil prices in combination with
associated higher import prices tend to increase cost of production leading to
reduction of business profitability. In addition this will unavoidably lead to higher
inflation which will in turn lower the purchasing power of consumers. Change of
prices of basic needs commodities are given by the percentage change in the poverty
line which shows an increase of 1.05 per cent, thus affecting low income households
103
adversely. Hence, reduction of business profitability, together with a sharp decline in
aggregate demand results in a massive drop in employment by 5.8 per cent. Higher
oil prices have fed into significant increase in domestic prices in oil importing
developing countries. Therefore, many developing countries are vulnerable to the oil
price shock. The results suggest that in the short run high oil prices would have an
overall negative impact on Sri Lanka’s economic growth and also exacerbate
poverty.
In support of supply side causes of inflation, Islam (2008) notes that supply side
constraints in the commodity markets in Bangladesh have instigated price hikes. He
also notes that as a result of undervalued currency Bangladesh is suffering from
currency induced inflation particularly in the presence of high international oil and
food prices. Islam (2008) identifies the difficulty in allowing appreciation of the
currency as the export sector might lose its competitiveness as a result of this.
According to this study, there are both monetary and structural reasons for inflation
in Bangladesh.
Siregar and Rajaguru (2005) explain that in the case of Indonesia their results
robustly confirm the significant roles of expected depreciation of currency, money
supply, and domestic interest rate in explaining inflation rate in the country. Among
these significant factors, the test results also suggest that the base money is the most
significant and persistent contributor to the substantial increase in the overall price
level in Indonesia during the post crisis period. The test results also indicate that the
role of money supply is the most significant one for the Indonesian case, contributing
as much as 37 per cent of the variation in the inflation rate. In Thailand the role of
exchange rate variable clearly dominates contributing around 9 – 23 per cent of the
variation in the inflation rate. Preceding findings have suggested that while the loose
management of the base money in Indonesia has been the primary cause of high and
persistent inflation, the volatility of the local currency contributed the most to the
price changes in Thailand during the post 1997 crisis. For example from December
1997 to December 1998, Indonesia had expanded (year on year) its monthly base
money by an average of about 75 per cent. For the same 12 month period, Thailand
on the other hand had successfully tightened their monetary policy and reported a
monthly average year on year contraction of base money by around 0.35 per cent. As
104
for Thailand weak and volatile local currency contributed significantly more to the
price fluctuations than the base money.
The case of Indonesia requires some more explanation from the events that took
place around that time. Excess liquidity was created in order to provide substantial
support to the troubled banks. The day after the first post crisis agreement was signed
with the IMF, the government of Indonesia announced the liquidation of 16 banks. It
created a shock wave that resulted in a total loss of confidence in the banking system.
Within a month after the announcement of the closures of 16 banks, the level of base
money has grown by more than 36 per cent largely due to Bank Indonesia Liquidity
Supports to troubled banks and to lessen the impact of depositor runs on banks. So
the rise in the base money was in effect an attempt to stop bank run which could have
led to another crisis. One questionable issue relating to empirical investigation of the
study is that it finds interest rate, both domestic and foreign, to be non-stationary.
The rate variables having unit roots in a finite sample is a very unlikely case. In a
finite sample such series should show mean reversion process.
There are other studies which support the view that expansionary monetary policy
through rise in aggregate demand causes inflationary situation in developing
countries. Ramayandi and Rosario (2010) argue that the lack of discipline in
monetary policy in Indonesia is responsible for the surge in inflation rate. The
expansionary monetary policy, the authors argue, led to rise in aggregate demand
with a growing and unchecked private credit, all proving to be unproductive in
stabilising the economy. They suggest a need for monetary policy discipline to
safeguard the country’s economic stability. The authors present a comparison
between the actual policy rate and its benchmark path derived from an estimated
policy reaction function. They notice two episodes – between 2005Q2 and 2006Q3
and between 2007Q4 and end of 2008 – when huge deviations are observed and the
actual policy rate remains below the benchmark rate. Notably inflation peaked in
both cases. Output gap behaved differently in the two episodes. Within episodes 1,
inflation surged about 17 per cent while there was no significant pressure observed in
the output gap. In contrast, episode 2 shows that a peak in inflation was accompanied
by a systematic pressure in the output gap. The authors suggest that the actual policy
rate should have been increased in response to a rise in inflation expectation and or
105
output gap. In the case of episode 1, this argument does not seem to be valid. The
inflation rate came down in the subsequent quarters even though there was a
difference between the actual and benchmark rates. So the difference cannot be held
responsible for creating a problem of inflation. It is also important to note that during
this period the output gap was below zero, perhaps the reason why the authorities
were reluctant to raise interest rate. In the case of the second episode, inflation seems
to be a lag variable – output gap has an increasing trend followed by a similar trend
in inflation. Considering that inflation is rising and output gap is also positive there is
perhaps some justification for raising the interest rate (as reflected by a greater
increase in the benchmark rate). However, one notices that both variables, inflation
and output gap, dipped in the last quarter of 2008. Whether a rise in the actual policy
rate (in line with the benchmark rate) – a single instrument – would have managed to
curb the rise in inflation rate in the midst of the global financial crisis remains a
question. The authors’ suggestion seems to follow the “one target one instrument”
and strict rule based monetary policy which has received criticism in the face of the
crisis.
An interesting departure from these conventional studies to find the causes of
inflation is the study by Khan and Saqib (2012). It investigates the effects of political
instability on inflation in Pakistan. Applying the GMM technique and using data
from 1951 to 2007, they have examined this link through two different models. The
results of the monetary model suggest that the effects of monetary determinants are
rather marginal and inflation depends on the political environment of Pakistan. They
have discarded monetary growth as a potential cause of high inflation in Pakistan
(high inflation is defined as inflation rate more than 7 per cent – average annual
inflation rate in the period 1951 – 2007) on the grounds that effect of money growth
on inflation is dependent on political environment. The nonmonetary model’s
findings explicitly establish a positive association between political instability and
inflation. This is further confirmed through an analysis based on interactive dummies
that reveal political instability significantly leading to high (above average) inflation.
Khan and Saqib (2012) argue that political instability undermines the competence of
a government and diminishes its ability to deal with shocks that eventually result in
macroeconomic disequilibrium such as inflation. The authors note that the
106
conventional view that political instability leads to high inflation due to
government’s excessive reliance on seignorage may not hold in a low to moderately
high inflation country such as Pakistan. Government crisis is found to be more
important than oil price in explaining inflation. Government crisis has a stronger
effect on inflation in situation of high inflation. When inflation is above average an
additional government crisis increases inflation by 0.715 percentage points from its
average. The study suggests that unless political reforms aimed at mitigating
government crises and cabinet changes are not undertaken, inflation stabilization
efforts by the technocrats would fail to yield long term price stability.
4.7 Conclusion
This chapter provides a critical review of country-specific studies on growthinflation relationship in some selected developing countries of Asia. Stylised facts
from growth-inflation data and the review of literature reveal some interesting
insights about the relationship. The discussion shows that inflation and growth may
move together in the developing countries of Asia. There are a number of reasons
behind this. They include structural causes such as inevitable fiscal deficits due to the
need to finance the effort to close large physical and social infrastructure deficits
with a low tax base, subsistence agricultural practices, and various other supply
rigidities or bottlenecks. There are instances when some of these countries grew
amidst inflation.
The findings from the review of literature and the historical experience of inflation in
the Asia-Pacific region (as evident from mean inflation in Table 4.1) also show that
for majority of the countries mean inflation threshold lies above 5 per cent. In
addition we find strong evidence against a one size fits all policy. Thus the advice by
the IMF to keep inflation at a very low level for all countries is not supported by
different threshold levels found for different countries. It is also interesting to note
findings of different threshold levels for the same country. This could be due to
modelling issues such as univariate or multivariate framework and selection of
explanatory variables; and methods of empirical estimation taking into account
reverse causality and effects of outliers or sample size and periods covered.
107
The discussion from the literature also provides evidence that the countries trying to
keep inflation at a very low level sacrifice in terms of growth. This is evident from
higher growth volatility. Monetary policy in the developing countries also faces a
challenge in controlling inflation and maintaining export-led growth. Contractionary
monetary policy using higher interest rate to fight inflation is responsible for this as
higher interest rate causes currency appreciation and thus negatively affects
competitiveness in the international market. Tight monetary policy could also
adversely affect growth when inflation is caused by supply side factors. In the event
of negative supply shock fighting inflation using higher interest causes a further
decline in output and growth.
108
Chapter 5
A Panel Study on Growth-Inflation Relationship in Selected
Developing Countries of Asia
5.1 Introduction
This chapter attempts to employ cross-country panel estimation techniques to
investigate the growth-inflation relationship in selected developing countries of Asia.
The objective of the chapter is to provide empirical support to the critical review of
literature presented in Chapters 2, 3, and 4. A key issue we examine here is whether
there is significant evidence of an inflation-threshold close to 5 per cent, beyond
which inflation becomes harmful for economic growth. We also investigate if the
threshold varies under different structural and economic circumstances. Our intention
is to establish the argument empirically that keeping inflation at 5 per cent in the
developing countries is not justified. The previous chapters have established the case
strongly by analysing the extant literature and descriptive statistics from developing
countries of Asia. Although important, empirical evidence on this issue with
particular emphasis on developing countries of Asia is relatively scant. This chapter
aims at fulfilling this gap. It provides empirical evidence using techniques, such as
dynamic panel estimation (System Generalised Method of Moments), not employed
before in analysing the case of developing countries of Asia. The use of modern
panel data techniques allows us to take full advantage of time series variation as well
as variations across countries.
The findings from the analysis in the context of 14 developing countries of Asia for
the period 1961 and 2010 help us conclude that policy prescription for keeping
inflation at a low level such as 5 per cent has a very weak empirical foundation. The
results using different panel estimation techniques suggest that inflation within the
range of 8-15 per cent may not be harmful for economic growth. We have also noted
that the threshold levels vary according to the levels of development. There is strong
evidence that for poorer groups of countries threshold tends to be higher. These
findings are in sharp contrast to what the IMF and the conventional wisdom of
109
mainstream economics preach – inflation below 5 per cent is beneficial for growth in
the developing countries.
This section of the chapter proceeds with a brief discussion on overall picture of the
growth-inflation relationship evident from a selected developing countries of Asia.
The rest of the chapter has three main parts. Section 5.2 explains the research
methods relating to selection of variables and empirical models. The empirical
results are presented in Section 5.3 and a conclusion is provided in Section 5.4.
To begin with, Figure 5.1 presents pooled annual observations from a selection of 25
developing countries of Asia for the period 1961-2010.76 There does not seem to be a
stable long run relationship between inflation and growth according to the figure.
The real GDP growth rate shows a gradual decline as the range of inflation increases
from 0-5 to 5-10 and 10-20 per cent. This happens for a relatively large number of
observations; 248, 297, and 173 respectively (see Figure 5.1). However, the highest
growth rate is registered in the inflation range between 20 and 40 (for a relatively
small number of observations of 42). Beyond the inflation rate of 40 per cent, growth
becomes negative which is consistent with what is noted by Bruno and Easterly
(1998). Perhaps the information in Figure 5.1 reveals two important facts. First,
evidence of high growth within the inflation range of 20-40 per cent tells us that
there are instances when developing countries within this region grew amidst
relatively high inflation. A number of countries such as Lao PDR, Sri Lanka,
Mongolia, Kyrgyz Republic, Tajikistan, and Uzbekistan could be cited as examples.
In these countries, at different points in time, growth was above 5 per cent amidst
high inflation. On the other hand, growth experience in the initial ranges of inflation
(0-5, 5-10, and 10-20 per cent) provides a rationale for the suggestion that inflation
should be kept within 0-5 per cent. These preliminary observations, however, do not
provide a case for a robust relationship between inflation and growth and that indeed
an inflation-threshold exists at a very low level. Such examinations are carried out in
the following sections.
76
The countries, in Figure 5.1, are selected based on their similar historical background, so that the
sample is representative of the population, and at the same time to help capture variations in the
developing countries of Asia. It is done keeping in mind that panel estimation techniques can take care
of such country heterogeneity properties to some extent, if not fully. However, the number of
countries reduces in the panel estimation as revealed in subsequent sections. This is primarily because
of lack of data on regressors for the countries.
110
Figure 5.1: Inflation and Growth in Selected Asian Countries, 1961-2010
7
Real GDP growth rate
6
6.2
5.5
5.3
4.7
5
4
3
2
1
0
-1
-2
0-5 (248)
>5-10 (297)
>10-20 (173)
>20-40 (42)
>40 (40)
-1.2
CPI inflation range (%) with number of observations within brackets
Sources: Author’s calculations using data from the World Bank, World Development Indicators
(WDI); International Monetary Fund, World Economic Outlook (WEO).
Notes: Pooled annual observations based on 25 countries of Asia. The countries are Bangladesh,
Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Maldives, Nepal, Pakistan, The
Philippines, Sri Lanka, Thailand, Vietnam, Fiji, Kazakhstan, Kyrgyz Republic, Mongolia, Papua New
Guinea, Samoa, Solomon Island, Tajikistan, Turkmenistan, and Uzbekistan.
5.2 Estimation Methods
The panel dataset initially included information from 25 developing countries in Asia
for the period 1961-2010. These countries were selected from regions such as South
Asia, East Asia, Asian countries within the Commonwealth of Independent States
(countries in former Soviet Union), and small island nations. The list was comprised
of Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Lao PDR, Malaysia,
Maldives, Nepal, Pakistan, The Philippines, Sri Lanka, Thailand, Vietnam, Fiji,
Kazakhstan, Kyrgyz Republic, Mongolia, Papua New Guinea, Samoa, Solomon
Islands, Tajikistan, Turkmenistan, and Uzbekistan. However, because of poor or no
availability of data, particularly on control variables such as government
consumption (% of GDP) and real household consumption per capita, we restricted
regression analyses mostly to 14 countries of the list. So, the countries for panel
estimations are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia,
Pakistan, The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz Republic, Papua
111
New Guinea, and Tajikistan. We have excluded China despite data availability as the
country is an outlier because of its size and economic structure. In short, the dataset
is an unbalanced panel covering 14 countries spanning over up to 50 years (19602010).77 Under such circumstances, the potential dimension of the panel is
14×50=700 observations. But in practice because of missing observations, the
dimension is smaller.
The empirical approach, in essence, involves regressing two measures of growth –
real GDP growth and real GDP per capita growth – on inflation, conditioned upon
other variables suggested by the related literature.78 The dataset is gathered from the
standard and most widely used sources – the World Bank’s World Development
Indicators (WDI); the IMF’s International Financial Statistics (IFS) and World
Economic Outlook (WEO). The panel estimations use annual data in order to
maximise sample size and to measure the parameters of interest more precisely. This
empirical approach differs from most frequent practice in the literature – smoothing
data using five or ten year averages. There are two main arguments in favour of
using annual observations. First, the relationship between inflation and growth is
more evident in the case of higher frequency of the data as noted by Bruno and
Easterly(1998). They state, “[the] results get stronger as one goes from the crosssection to ten year averages to five year averages to annual data” (p. 4). Khan and
Senhadji (2001, p. 16) also note that “high-inflation effect [on growth]…is more
powerful for yearly data”. The second reason is based on the argument set forth in
Baltagi et al. (2009). They state that averaging out annual data over, for instance, five
year periods results in reduction in sample thereby raising the possibility of making
most of the variables statistically insignificant. The authors explain that “smoothing
out of time series data removes useful variation from the data, which could help to
identify the parameters of interest with more precision” (p. 286). Apart from these
two reasons we also believe that assuming a uniform business cycle pattern for all
countries in the panel, which the data-smoothing technique does, is not appropriate
(see discussion in Chapter 3).
77
The growth rates are available from 1961 once we take the first difference of the natural logarithm
of level variables. The dataset is still unbalanced because information on variables for the 14 countries
is not available for all years.
78
The selection of variables is explained in the section that follows.
112
5.2.1 Selection of variables and summary statistics
A large number of possible specifications relating to the selection of variables
(regressors) exist in the cross-country growth literature (Lopez-Villavicencio &
Mignon 2011, p. 458). Our choice of control variables is similar to the choice in the
previous studies although it is not identical. We are interested to find out how
inflation affects growth conditioned upon other covariates. We have chosen the
covariates because they may influence the condition and the way in which inflation
affects growth.
In order to assess the nature of growth-inflation relationship, economic growth is
selected as the dependent variable. Both real GDP growth and real GDP per capita
growth are used as a measure of economic growth. Figure 5.2 shows the distribution
of the two variables in the sample of 14 countries. The distributions of the two
measures of economic growth look similar. Economists are particularly interested in
looking at output per capita measure of growth as it provides a better indicator of a
country’s development. Total real output per capita also allows us to take the relative
economic size of the country into account (Busse & Hefeker 2007, p. 403). However
in this study because we are interested to see whether the country simply produces
more output or not, independent of its population growth, we choose the real GDP
growth as well. Besides, growth in per capita GDP in developing countries is
affected by how successful the country is in controlling its population growth, an
issue which is not a prime focus of this study. So, in short, while performing the
estimation we give priority to the real GDP growth as a dependent variable. Since the
distribution of the two measures of growth looks similar, we do not expect much
difference in the results.
113
Figure 5.2: Distribution of Real GDP Growth and Real GDP Per Capita Growth in
15
10
0
5
Density
0
5
Density
10
15
Selected Developing Countries of Asia, 1961-2010
-.4
-.2
0
Real GDP Growth
.2
-.4
-.2
0
Real GDP Per Capita Growth
.2
Sources: Graphs generated by author using data from World Bank, WDI.
Note: Countries (N= 14) are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia, Pakistan,
The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan.
Next, inflation is included as the key explanatory variable of interest – to examine
the impact of inflation on growth. Inflation is defined as the growth rate of consumer
price index (CPI). The measure of inflation based on CPI is preferred over GDP
deflator as the latter is a derived product of GDP and therefore would have an
obvious association with output growth.79 In relation to inflation the first concern is
the presence of outliers, very high observations of inflation for few countries, which
might have strong influence on the results. In order to avoid problems due to outliers,
79
As Sarel (1996, p. 201) notes that “[i]t is better to use CPI data than implicit GDP
deflators…because changes in GDP deflators are, by construction, negatively correlated with the
growth rates.”
114
three different cases are considered.80 In the first instance, the models include cases
where inflation rate is less than 40 per cent. Pollin and Zhu (2006) in all their
estimated models exclude observations in which inflation exceeded 40 per cent.
Similar practice is carried out in one of the models used in de Mendonca and
Guimaraes e Souza (2011).81 The elimination of cases of high inflation (annual
inflation rate greater than 40 per cent) is done in line with the observation made by
Bruno and Easterly (1998) that inflation is indeed harmful for growth beyond the rate
40 per cent. Excluding the cases of inflation greater than 40 per cent, however,
reduces the number of observations. In order to maintain the number of observations
in the models two other cases are considered. The second case considers inflation as
ln(1+π), where π is inflation. We follow this approach in line with Kumar and Woo
(2010).82 Transformation of a variable to natural logarithm is expected to produce a
distribution that is closer to normal. This log transformation technique to avoid the
effect of outlier is common in the empirical literature. For instance Sarel (1996)
suggests that the log transformation helps to reduce, at least partially, the strong
asymmetry in the distribution of inflation. Finally, the third case considers a
normalisation process by transforming inflation rate as π/(1+ π) following de
Mendonca and Guimaraes e Souza (2011).83 Figure 5.3 shows the distribution of the
different forms of inflation. In the first panel (top left) of Figure 5.3 the distribution
of inflation across the full sample of 14 countries and time period (1961-2010) is
shown. It is evident that the distribution is highly skewed. The second panel (top
right) shows the distribution of inflation when inflation rates greater than 40 per cent
are removed from the sample. The bottom two figures correspond to the distributions
of the converted inflation. In all three cases, the distributions are relatively less
skewed than the original one. What we also notice is that the two converted inflation
distributions look more centralised than the distribution of inflation rate less than 40
80
Determination of the turning point at which a rise in inflation would cause growth to fall would vary
according to the cases. We mention how the turning point is measured in the section where the results
are presented.
81
See their fourth model and the explanation that follows (p. 4).
82
We take ln(1+π) instead of ln(π) because of the negative values of inflation rate.
83
The authors carry out this transformation in their fifth model following the suggestion of
Cukierman et al. (1992).
115
per cent. We are interested to see whether such differences in the distributions of
inflation have any implications in estimated results.84
Figure 5.3: Distribution of Inflation in Selected Developing Countries of Asia, 1961-
0
0
.2
2
4
6
Density
.4
.6
Density
.8
8
1
10
2010
5
10
CPI Inflation
15
20
-.1
0
.1
.2
.3
.4
CPI Inflation when the rate is less than 40 per cent
4
Density
0
0
2
1
2
Density
6
3
8
4
0
0
1
2
ln(1+CPI Inflation)
3
0
.2
.4
.6
.8
(CPI Inflation) / (1+CPI Inflation)
1
Sources: Graphs generated by author using data from World Bank, WDI and IMF, IFS and WEO.
Note: Countries (N= 14) are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia, Pakistan,
The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan.
Figure 5.4 attempts to capture the relationship between real GDP growth and the
logarithm of “1 plus inflation”.85 The graph is drawn following Khan and Senhadji
(2001, Figure 1, p. 4) who smoothed out data by reducing the full sample to five
observations. The arithmetic mean of real GDP growth is taken for five equal
subsamples corresponding to increasing levels of inflation (ibid., p. 3).86 It is
84
For instance taking a different digit arbitrarily in the place of “1” in ln (1+π) would change the
distribution. If this has implications in the estimated results it might raise questions about using such
conversions.
85
Graph is similar between real GDP growth and π/(1+ π).
86
There are 449 observations in our sample of 14 countries over the period 1961-2010. The first four
subsamples include 90 observations of inflation and growth each and the last one includes 89.
116
interesting to note that the observations from Figure 5.4 differ from what was noticed
by Khan and Senhadji (2001). In both cases the relationship between inflation and
growth is positive for low levels of inflation. But unlike Khan and Senhadji (2001)
we do not see growth to decline drastically when inflation moves to a moderately
high level. This also does not corroborate the findings of Ghosh and Phillips (1998)
who warn of a danger of a steep drop in growth beyond the threshold level of
inflation. The findings of Khan and Senhadji (2001) also show that the negative
effect of inflation on growth weakens at very high inflation rates, supporting
Fischer’s (1993) findings. Our findings, however, are different and more in line with
what Bruno and Easterly (1998) suggested. As we see from Figure 5.4, that growth
declines gradually when inflation starts to move towards a higher level. It is at a very
high level of inflation that growth falls sharply. The differences between the findings
are perhaps obvious. Khan and Senhadji (2001) in their analysis, displayed in Figure
1 (p. 4), did not differentiate between industrial and developing countries. Our
analysis consists of a much smaller group of developing countries. This perhaps
reiterates the importance of making the distinction between advanced and developing
countries while performing the analysis as pointed out by Sepehri and Moshiri
(2004).
Figure 5.4: Relationship between Real GDP Growth and Inflation
Mean of real GDP growth
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
1
2
3
4
5
Five subsamples corresponding to increasing levels of
ln(1+Inflation)
Sources: Author’s calculations using data from World Bank, WDI and IMF, IFS and WEO.
117
Note: Countries (N= 14) are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia, Pakistan,
The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan.
Apart from inflation, a number of control variables which might influence the
growth-inflation relationship are considered as regressors. The mnemonic used for
some of these variables are shown in parentheses. The variables are as follows:
(1) Lagged growth: Growth lagged in one period is taken on the right hand side
to reflect the dynamic nature of the relationship and to capture the possibility
of partial adjustment towards the steady-state. The coefficient of this variable
is expected to be positive and lie between zero and one. As Greene (2003, p.
307) explains that incorporating dynamics in this way allows us to consider
the “entire history of the right hand side variables, so that any measured
influence is conditioned on this history.”
This in turn has implications for the choice of estimator. The preferred estimator in
these circumstances is dynamic Generalised Method of Moments (GMM). In
standard static panel models such as Fixed Effects (FE) and Random Effects (RE),
the lagged dependent variable as a regressor is not used to avoid possible bias in the
estimator. We expect that previous year’s growth would have a positive impact on
current year growth. Inclusion of the lagged term also helps reduce the problem of
autocorrelation.
(2) Real household consumption per capita (HCONPC): To measure the effect of
aggregate demand on growth-inflation relationship, real household
consumption per capita measured in constant US dollar is included as a
control variable. The inclusion of this variable is justified since consumption
is assumed to be the largest component of aggregate demand. Besides, higher
household consumption per capita is assumed to be growth enhancing and an
indication of poverty reduction. We prefer to use this variable to investment
since investment data for poorer countries are problematic. The expected sign
of its coefficient is positive.
118
(3) Financial Deepening (FD): Broad money-GDP ratio is taken as a control
variable to measure the effect of financial deepening on the growth-inflation
relationship. Various measures are used as a proxy for FD in the literature.
We use M2/GDP which is the liquidity liabilities of the financial system. It is
also known as monetisation variable which, in a growing economy, helps us
capture the real size of the financial sector. M2 equals currency plus demand
and interest bearing liabilities of banks and non-bank financial intermediaries.
Therefore, as Guiliano and Ruiz-Arranz (2009) note, this measure is the
broadest measure of financial intermediation that includes three types of
financial institutions such as the central bank, deposit money bank, and other
financial institutions. We are, however, aware of the limitation of the use of
this proxy. For instance, Khan and Senhadji (2003) argue that M2/GDP is a
poor proxy for financial development because they merely show the capacity
of the financial system to provide transaction services rather than the capacity
to transfer funds from savers to borrowers.
Next, our task is to determine the expected sign of FD. Earlier studies such as
McKinnon (1973), Shaw (1973), and Kapur (1976) argue that financial development
has a positive impact on growth. So if the ratio of broad money to GDP is growth
enhancing, money supply is expected to have a greater impact on growth and less
impact on inflation. This is because a developed financial system absorbs the money
supply and diverts it to the real sector, thus generating growth. Thus we expect a
positive sign of this coefficient. The expected positive sign of the coefficient would
also mean that expansionary monetary policy may not be harmful for the real sector
of the economy.
On the other hand, economists such as Robinson (1952) and Lucas (1988) doubt the
role played by financial development in promoting economic growth. For example,
Bangake and Eggoh (2011, p. 178) point out that many of the Asian economies grew
fast in the 1970s and 1980s without a developed financial system.87 If the sign of the
coefficient of this variable is negative it may provide support for the monetarist view
– an increase in the ratio of money supply to GDP implies pressure on inflation and
87
They also note that many OECD countries engaged in financial reforms in the 1980s, yet savings,
investment, and growth in them have not accelerated.
119
therefore negative impact on growth. It holds to be true provided that too much
money is chasing too few goods leading to an inflationary situation. The monetary
expansion may also lead to bubbles (which might result into an inflationary situation)
in the financial system if monetary transmission mechanism is not effective enough
to channel the funds from financial system to the real sector. In fact, developing
countries may have underdeveloped financial system which may have a high ratio of
money to GDP, as money is used as a store of value in the absence of other attractive
alternatives (see Khan & Senhadji 2003). Baltagi et al. (2009) in this connection
stress the importance of economic institutions such as property rights. If property
rights are weak, financial development may not be sufficient to promote growth.
Weak property rights may discourage investment even when bank loans are
available. In such circumstances, we might expect a negative sign of the FD
coefficient.
(4) Government consumption expenditure (GOVCON): Government
consumption as a per cent of GDP is taken to determine the effect of fiscal
policy on growth-inflation relationship. In terms of the availability of data
from standard sources, this appears to be the best proxy to measure the
impact of the size of government. The sign of coefficient could be either
positive or negative. A negative sign might indicate that higher government
spending is inflationary (Fiscal Theory of Price Level) that is bad for
growth.88 In addition, an argument in favour of the negative sign is that as the
size of the government becomes larger it crowds out the private sector, thus
adversely affecting growth.
Arestis and Sawyer (2003), however, argue that the argument of crowding out is not
valid when fiscal deficits correct a deficiency in private aggregate demand and fiscal
policy is viewed in terms of functional finance. Hemming et al. (2002) identify a
number of reasons why the effect of fiscal policy tends to be positive and quite large.
These conditions include a demand constrained economy with excess capacity; a
closed economy or an open economy with a fixed exchange rate; and households
88
The Fiscal Theory of Price posits that increased government consumption and debt adds to
household wealth and hence, to demand for goods and services, leading to price pressures (Kwon,
Mcfarlane & Robinson 2009).
120
with limited horizons or liquidity constraints. So, we can also expect a positive sign
when government spending is beneficial in raising the productive capacity of the
economy and thus growth inducing.
(5) Trade openness (OPEN): Summation of export and import as a per cent of
GDP is taken as a control variable to measure the trade openness. This
measure of openness is considered most suitable among others. For instance,
other forms of measure of openness could include capital account tracing the
flow of financial products. This may not be appropriate to consider in our
model as financial markets in these economies are integrated with each other
to varying degrees. A more open economy is subject to shocks which could
be either positive or negative. Therefore, the sign of this coefficient in the
growth regression remains uncertain.
The relationship between trade openness and growth is a highly debated topic but
still an unresolved issue in the growth and development literature (Yanikkaya 2003).
A wide range of empirical studies support that open economies grow faster than
closed economies. Openness to trade favours growth because it provides access to
imported inputs, which embody new technology; increases the effective size of the
market facing producers, which raises the returns to innovation; and affects a
country’s specialisation in research-intensive production (Harrison 1996). So, we can
expect a positive sign of OPEN in our estimated model. However, Yanikkaya (2003)
citing other literature89 states that if trading partners are asymmetric countries in the
sense that they have considerably different technologies and endowments, even if
economic integration raises the worldwide growth rate, it may adversely affect
individual countries. Earlier, Rodrik (1999a) also expressed his reservations about
the overwhelming support in favour of trade liberalisation and its positive impact on
growth. He states that “[j]ust as the advantages of import-substitution policies were
overstated in an earlier era, today the benefits of openness are oversold routinely in
the policy-relevant literature and in the publications of the World Bank and the IMF”
(Rodrik 1999a, p. 25). We can, therefore, expect a negative sign of OPEN as well.
89
For instance, see studies such as Grossman and Helpman (1991a, 1991b), Lucas (1988), RiveraBatiz and Xie (1993), and Young (1991).
121
(6) Agriculture’s share of GDP (AGR): Since agriculture is still the mainstay of
the economy in most of the developing countries, the share of agriculture
output as a per cent of GDP is considered as a control variable. In an
influential study Johnston and Mellor (1961) state that agriculture
productivity is vital for economic development, especially for developing
countries. According to the study, agriculture contributes to economic growth
by providing enough food supply, increasing agriculture exports, transferring
adequate labour supply to the manufacturing sector, contributing capital for
infrastructure and industrial expansion and stimulating industrial expansion
by raising the net cash incomes of the farm population. However, Dowling
and Valenzuela (2004) note that the experience of a broad range of countries
indicates that the relative importance of the agricultural sector to the economy
diminishes in favour of manufacturing and service sectors with growth over
time. The accepted explanation for this relationship is the change in the
composition of demand, of which the decline in the share of food (Engel’s
Law) is the most notable feature (Chenery 1960, p. 624).
Therefore, from the discussion, we expect that AGR would help us capture the
structural changes in the economy and any impact on growth-inflation nexus as a
result of the change. A greater level of development would mean that economic
transformation is taking place and economies are less dependent on the primary
sector. A negative sign of the coefficient, therefore, is expected which would indicate
that such transformation is taking place and is beneficial for economic growth.
However, we do not rule out the possibility of a positive sign of the coefficient of
AGR either. As Chenery (1960) observes that this over-all relationship may not
necessarily apply to every individual country. He argues that within limits, the
changing composition of domestic demand for food can be offset through foreign
trade. A country having a continuing comparative advantage in primary production,
he points out, may, therefore, reach a high level of income without an increase in the
share of industry in total output.
(7) Oil and commodity price shocks: Developing economies are prone to supply
shocks caused by oil and commodity prices in the international markets. Oil
price directly affects the supply side of the economy and therefore growth.
122
Commodity prices in the international market may also affect domestic
growth directly, especially when such commodities are important inputs in
production. Additionally, fluctuations of commodity prices may act as an
incentive or disincentive for domestic production and therefore affect growth.
To assess such impacts two dummy variables are created. The oil dummy,
DUMOIL, takes the value 1 for the years 1971, 1974, 1979, 1999, 2000,
2004, 2005, and 2008 and the value 0 otherwise. In these years, growth rate
of oil price index is 20 per cent above its historical mean that is 7.44 per cent.
The dummy captures the three major international oil price shocks. The
commodity price dummy, DUMCOMPR, is constructed in a similar fashion.
It takes the value 1 for years 1973, 1974, 2004, and 2006 when the growth
rate of commodity price index is above 20 per cent of its historical mean at
3.85 per cent. The dummy takes the value zero for other years. The
commodity dummy helps capture the shocks of the 2000s. Both dummies
take the value 1 only when growth rates show positive 20 per cent deviation
from trend. This is because our interest is to see the influence of negative
supply shocks as a result of rising oil and commodity prices. Figure 5.5
shows the deviations of oil and commodity price growth rates from their
trends – historical mean at 7.44 and 3.85 per cent respectively. Because of the
positive correlation between oil and commodity prices, discussed later, we
believe constructing such dummies to gauge their impacts is more
appropriate. The expected sign of the coefficients of these dummies is
negative – rising oil and commodity prices in the international markets acts as
a negative shock, adversely affecting growth. However, we should also keep
in mind that some of the economies may benefit from oil price rises. The
economy of Indonesia, for instance as discussed in the previous chapter,
seemed to have benefited from rising oil prices. In addition, the effect may
not be captured in a straight forward way since governments in developing
countries often subsidise oil dependent sectors to mitigate the negative shocks
resulting from rising oil price. On the other hand, increase in commodity
prices in the international market may positively affect economies which are
net exporters of those commodities.
123
Figure 5.5: Deviation from Trend of Growth Rates in Oil and Commodity Price
Indexes, 1961-2010
120
100
80
60
20
0
-20
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Percent
40
-40
-60
-80
-100
Deviation of oil price growth from historical trend
Deviation of commodity price growth from historical trend
Source: Authors calculations using data from IMF, IFS.
Notes: Oil price index and commodity price index refer to UK Brent Crude Oil Index (2005=100) and
World Bank non-energy commodity price index for lower middle income countries (2005=100)
respectively.
Summary statistics of the growth rates of the above variables for the period 19612010 are provided in Table 5.1. In general, long run average (unweighted) economic
growth in the sample countries is below 5 per cent. The average inflation is around
17 per cent and it is significantly more volatile (as evident from the standard
deviation) than economic growth over this long period. Real household consumption
per capita has registered less than 2 per cent average growth over this period. Mean
growth rates in financial deepening and government consumption, both as a per cent
of GDP, are less than 5 and 1 per cent, respectively. The latter shows that the size of
the government proportional to GDP has not grown much over the long period.
Average growth rate in trade openness is around 2 per cent, reflecting the fact that
the countries in the sample are becoming more open economies. It is also important
to note that average growth of share of agriculture to GDP is around negative 2 per
cent, revealing a declining trend in the primary sector of the economies. This is
perhaps an indication that structural transition is taking place in these traditional
124
agro-based economies. In the international markets, oil price on average has
increased more and remained more volatile compared to commodity prices (Table
5.1).
Table 5.1: Summary Statistics of Growth Rates of Selected Variables, 1961-2010
Variable
Economic
growth
CPI inflation
Real
household
consumption
per capita
Broad
money-GDP
ratio
Government
consumptionGDP ratio
Trade
openness
AgricultureGDP ratio
Oil price
index
Commodity
price index
Observations
Mean
Standard
deviation
Minimum
Maximum
538
4.63
5.35
-33.64
19.57
465
17.64
103.42
-7.63
1877.37
470
1.81
7.88
31.12
-53.96
435
4.23
10.35
-87.44
64.17
513
0.55
13.47
-65.10
152.59
529
2.05
16.90
-107.95
114.99
507
-2.14
7.39
-42.23
47.22
50
7.43
27.50
-64.86
111.20
50
3.84
13.57
-23.22
42.46
Sources: Author’s calculations based on data from World Bank, WDI; IMF, IFS and WEO.
Notes: Countries (N= 14) are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia, Pakistan,
The Philippines, Thailand, Vietnam, Kajakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan. The maximum number of observation for each variable is 714.
The correlation matrix of the growth variables, presented in Table 5.2 also provides
some interesting facts about the possible long run relationship amongst the variables.
These associations, however, do not provide an understanding about the direction of
causality. There exists a moderate negative association between inflation and GDP
growth and it is significant at 5 per cent level. Not surprisingly, real household
consumption per capita and agriculture share of GDP have significant positive and
negative association with GDP growth, respectively. Higher GDP growth and higher
consumption per capita (supposedly a reflection of poverty reduction) should go
hand in hand while moving away from traditional sector should correlate with higher
125
growth. The other growth rates of other variables that have significant correlation
with GDP growth are oil price and commodity price growth rates, both having a
moderate positive relationship. It is interesting that both oil and commodity price
growth rates have a positive association with GDP growth, contrary to what is
perhaps expected. As explained above, it is possible since some of the countries
within the sample have oil, such as Indonesia and may benefit from rising oil prices.
Net commodity exporters, for instance Thailand and Vietnam which export rice, in a
similar manner may benefit from commodity price rises in international markets (see
discussion in Chapter 4).
Table 5.2: Correlation Matrix of Growth Variables
Growth
Growth
CPI inflation
Real
household
consumption
per capita
Broad
money-GDP
Government
consumptionGDP
Trade
openness
AgricultureGDP
Oil price
Commodity
price
CPI
inflation
Real
household
consumption
per capita
Broad
moneyGDP
Government
consumptionGDP
Trade
openness
AgricultureGDP
Oil price
Commodity
price
1
-0.277
1
0.493
-0.237
1
-0.02
-0.122
0.093
1
0.016
0.048
-0.086
0.266
1
-0.011
0.046
0.028
-0.032
-0.147
1
-0.139
-0.019
-0.069
0.004
-0.05
-0.102
1
0.122
0.115
0.131
-0.119
-0.079
0.3
-0.126
1
0.232
0.071
0.187
-0.127
-0.134
0.259
0.066
0.449
Sources: Author’s calculations based on data from World Bank, WDI; IMF, IFS and WEO.
Notes: Bold faced figures refer to correlation significant at 5 per cent level of significance. Countries
(N=14) are Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia, Pakistan, The Philippines,
Thailand, Vietnam, Kazakhstan, Kyrgyz Republic, Papua New Guinea, and Tajikistan.
Growth in Financial depth and government consumption expenditure (per cent of
GDP) has a negative and positive relationship with GDP growth in the long run
respectively. The rationale for such an association can be found in the economic
theory. These relationships, however, are not significant. Similarly, growth in trade
openness does not have a significant relationship with economic growth, even though
126
1
the sign of the correlation coefficient seem to suggest that openness is harmful for
growth.
Table 5.2 also shows some other significant relationships amongst variables.
However, since the correlation matrix does not give us an idea about the causality, it
is not clear the way in which the variables are affecting each other. Inflation has a
negative association with real household consumption per capita which seems
consistent if we believe higher inflation hits the poor and is harmful for poverty
reduction. Its negative correlation with broad money-GDP ratio is also interesting.
Both cases are possible – higher inflation leads to tight monetary policy (reducing
money supply) causing the M2-GDP ratio to fall or expansionary monetary policy
having a positive effect on growth and thus bringing down inflationary pressure on
the economy. The moderate positive correlation between inflation and oil price
growth seems to be consistent with the empirical evidence from the developing
countries. Rising oil price is expected to exert pressure on inflation.
Time series graphs presented in Figure 5.6 also help decipher some important facts.
Mean growth rate in the sample countries shows major declines in the early 1970s
and 1990s and late 1990s. There was one major hyperinflationary period in the 1960s
and one inflationary spike during the Asian Financial Crisis 1997-1998. These
episodes are mostly driven by the experiences of Indonesia around that time. Apart
from growth and inflation experiences, one revealing fact is that real household
consumption per capita shows a significant upward trend since the early 2000s.
Financial deepening shows more or less an upward trend with some setbacks in the
1990s. On the other hand, government consumption-GDP ratio shows a more
restrained trend. It peaks in the late 2000s perhaps due to the expansionary policy to
help recover the economies from the Great Recession of 2008-09. Trade openness
shows a significant upward trend in the 1990s perhaps due to globalisation policies
dominant around that time. The mean of agriculture-GDP ratio shows a continuous
decline over this period of time.
127
Figure 5.6: Mean of Cross-Country Data for Each Year, 1960-2010
Mean of Real GDP Growth
Mean of CPI Inf lation
.08
Mean of Real Household Consumption Per Capita
2.0
900
800
.06
1.5
700
.04
1.0
600
.02
500
0.5
.00
400
-.02
0.0
60
65
70
75
80
85
90
95
00
05
10
300
60
Mean of Broad Money -GDP Ratio
65
70
75
80
85
90
95
00
05
10
60
Mean of Gov ernment Consumption-GDP Ratio
18
120
60
16
100
50
14
80
40
12
60
30
10
40
20
8
65
70
75
80
85
90
95
00
05
10
05
10
70
75
80
85
90
95
65
70
75
80
85
90
95
00
05
10
60
65
70
75
80
85
90
95
Mean of Agriculture-GDP Ratio
40
35
30
25
20
15
65
70
75
80
85
90
95
00
05
10
00
05
10
20
60
45
60
00
Mean of Trade Openness
70
60
65
Source: Author’s calculations based on data from World Bank, WDI; IMF, IFS and WEO.
Note: Unweighted mean values of the variables for the 14 countries which are Bangladesh, Cambodia,
India, Indonesia, Lao PDR, Malaysia, Pakistan, The Philippines, Thailand, Vietnam, Kajakhstan,
Kyrgyz Republic, Papua New Guinea, and Tajikistan.
In summary, the selection of variable to examine the growth-inflation relationship is
done with a view to incorporating economic factors relating to structural, demand
and supply side shocks, and macro policies affecting the issue. From an analytical
point of view the aim is to create a parsimonious model in explaining the research
issues.
5.2.2 Empirical model
To investigate the potential nonlinearity of the relationship between inflation and
growth, the following panel model is developed.
128
yit = µi + βt + β1 πit + β2 π2 it + ∑
Zit + εit
(5.1)
for country, i = 1,…, N and time, t = 1,…,T. In equation (5.1), yit is the growth
measured using two alternative ways – first difference of natural log of real GDP and
first difference of natural log of real GDP per capita; µi is an unobservable time
invariant country specific effects to capture heterogeneity in the growth-inflation
relationship across countries; βt is a time specific effect incorporating dummies for
different time periods; πit is the inflation rate measured as the first difference of
natural log of consumer price index (CPI) or its transformed form as explained
above; Zit is a vector of control variables, the regressors which help explain the
growth-inflation relationship; and εit is the classical error term, assumed to be
independent and identically distributed with mean zero and variance
, which varies
with countries and time in the regression. The country specific effects, µi, and the
error term, εit, have the standard error component structure
E [µi] = E [εit] = E [µi εit] = 0
(5.2)
and the transient errors are not serially correlated:
E [εit εis] = 0 for s ≠ t
(5.3)
Inspection of the time series graphs of the control variables reveals that taking the
control variables in their first differenced form is appropriate to avoid spurious
regression. Although, theoretically ratio variables such as M2-GDP and government
consumption-GDP should show mean reversion process and therefore should be
stationary, the visual inspection of the time series casts doubt on this. So following
Kwon et al. (2009) the preferred form of data for the regression analyses is first
differences.90 In doing so, the above general version of the model can be rewritten as
follows:
90
Estimations are carried out using control variables at their level forms as well to compare
differences with their first differenced counterparts. These are discussed in the next section.
129
Growthit = µi + βt + β1 ∆ ln (CPI)it + β2 (∆ ln (CPI)it)2 + β3 Growthit-1
+ β4 ∆ ln (HCONPC)it + β5 ∆ ln (FD)it + β6 ∆ ln (GOVCON)it + β7 ∆ ln (OPEN)it
+ β8 ∆ ln (AGR)it + β9 DUMOILt + β10 DUMCOMPRt + εit
(5.2)
where, Growth is measured by two alternative ways, ∆ ln (real GDP) and ∆ ln (real
GDP per capita). CPI refers to consumer price index and HCONPC, FD, GOVCON,
OPEN, AGR refer to real household consumption per capita, broad money-GDP
ratio, government consumption expenditure as a per cent of GDP, trade openness as
defined above, agriculture share of GDP respectively. DUMOIL and DUMCOMPR
are the dummy variables for oil price growth and commodity price growth
respectively, as explained above. The rest of the notations are also explained in the
previous section.
The inclusion of time fixed effects requires some explanations. We use time fixed
effects in our model to make the estimation more robust. As Kumar and Woo (2010)
explain that this is to account for the possibility of any structural changes over the
sample period, including changes in trends in global growth or global risk factors.
Besides, the autocorrelation tests and robust standard errors reported later in the
chapter, we assume absence of autocorrelation across countries in the error term.
Thus including time dummies increases the chances of this assumption to hold (see
Kathavate & Mallik 2012; Roodman 2006). In all our estimations the time fixed
effects are found to be significant. One could, however, find contrasting evidence on
this. For instance, a recent similar study by Rao and Hassan (2011) ignores these
effects since they are found to be insignificant. We should, however, note that Rao
and Hassan’s (2011) study uses five year averages as opposed to annual data used by
us. We have also used robust standard errors in all our estimations to take care of the
heteroscedasticity or unequal variance unlike Rao and Hassan (2011). We have
preferred the use of robust standard errors since in practice we usually do not know
the structure of heteroscedasticity. Thus, it is safe to use robust standard errors
especially when one has a large sample size. Even if there is no heteroscedasticity,
the robust standard errors will become just conventional OLS standard errors. Thus,
the robust standard errors are believed to be appropriate even under
homoscedasticity.
130
5.3 Empirical Results
As a starting exercise, we estimate the impact of inflation on economic growth by
ordinary least squares (OLS). We are interested in testing whether the marginal
impact of inflation on growth is statistically significant. To begin with, Table 5.3
reports the OLS results following five time periods: 1960-2010, 1970-2010, 19802010, 1990-2010, and 2000-2010. Annual data for all variables are used and cases
with inflation rate above 40 per cent are avoided. This allows us to cover the long run
(fifty and forty year time horizons) as well as the medium term (twenty and ten year
time horizons). Such differing estimation periods provide us with an understanding
of any changes in inflation-growth nexus over time. However, OLS estimates cannot
be taken seriously in order to interpret the causality as it suffers from omitted
variable bias or heterogeneity bias resulting from possible correlation between
country-specific fixed effects and the regressors. Any significant correlation between
unobserved country specific factors and the right hand side regressors renders the
OLS estimations inconsistent (Hansen & Tarp 2001). The second is the endogeneity
problem due to potential correlation between the regressors and the error term.
Besides, this dynamic pooled OLS model (as a result of including the lagged
dependent term as a regressor) is likely to suffer from coefficient bias since the
lagged dependent variable may be correlated with time invariant country specific
effects (see Bond 2002).
Table 5.3: Impact of Inflation on GDP Growth, OLS Estimations
Dependent variable is growth measured by real GDP growth
(1)
(2)
(3)
(4)
(5)
1960-2010
1970-2010
1980-2010
1990-2010
2000-2010
0.00184
0.0308
0.00971
0.0396
0.129
(0.0677)
(0.0757)
(0.0873)
(0.105)
(0.143)
-0.0569
-0.124
-0.0255
-0.0757
-0.0419
(0.236)
(0.258)
(0.312)
(0.339)
(0.345)
Turning point
1.616872
12.41935
19.03922
26.15588
153.9379
Growth (-1)
0.203***
0.226***
0.24***
0.222**
0.146
(0.0743)
(0.0773)
(0.0855)
(0.0904)
(0.19)
Inflation
Inflation2
131
∆ ln HCONPC
0.281***
0.262***
0.241***
0.241***
0.195***
(0.0483)
(0.0461)
(0.0456)
(0.0524)
(0.0593)
-0.0439
-0.0394
-0.0418
-0.0377
-0.0407
(0.0306)
(0.0316)
(0.0339)
(0.0373)
(0.0787)
0.031
0.0284
0.0305
0.0537
0.0413
(0.0299)
(0.0304)
(0.0328)
(0.0362)
(0.0432)
0.0128
0.0233
0.0324
0.0264
0.0258
(0.0191)
(0.0196)
(0.0214)
(0.024)
(0.0314)
-0.0492
-0.0519
-0.0494
-0.056
-0.0864
(0.0407)
(0.0424)
(0.0443)
(0.0487)
(0.0561)
-0.00231
-0.00177
0.00348
0.00326
-0.00106
(0.0043)
(0.0043)
(0.0048)
(0.0051)
(0.0058)
0.00395
0.00394
0.00088
0.00173
0.00294
(0.0086)
(0.0086)
(0.0102)
(0.0106)
(0.0112)
0.0363***
0.0328***
0.0322***
0.0308***
0.0324***
(0.0048)
(0.0052)
(0.0056)
(0.0071)
(0.01)
380
348
295
224
129
R-squared
0.278
0.28
0.29
0.261
0.181
Adjusted R-squared
0.259
0.259
0.265
0.226
0.111
∆ ln FD
∆ ln GOVCON
∆ ln OPEN
∆ ln AGR
DUMOIL
DUMCOMPR
Constant
Observations
F
Countries (N =14)
9.22
10.1
9.56
7.89
5.26
Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia,
Pakistan, The Philippines, Thailand, Vietnam, Kazakhstan, Kyrgyz
Republic, Papua New Guinea, and Tajikistan,
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid outlier effect of inflation.
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
Turning point of inflation = [(Coefficient of linear term) / (2×coefficient of squared term)] ×
100.
5.
Growth (-1) refers to economic growth lagged by one period.
In all five cases reported in Table 5.3, the signs of the coefficients of linear and
squared terms of inflation confirm a nonlinear (inverted u-shaped curve) relationship
between inflation and growth. However, none of the coefficients is significant,
applying the robust standard error estimates. Lagged growth rate seems to have a
strong and significant positive effect on growth in the medium and long run but the
positive effect in the short run (2000-2010) is insignificant. Growth in real household
consumption per capita (HCONPC) also has a strong positive effect on growth across
132
all five time periods. This result is expected since aggregate demand is supposed to
have a strong positive impact on growth.
Apart from these two variables none of the other variables seem to have a significant
impact on GDP growth. Growth in financial deepening shows a negative impact on
GDP growth which is not uncommon in the findings of growth literature (see, for
instance, Rajan & Subramanian 2008, Table: 9, p. 658). Government expenditure
does not affect GDP growth negatively both in the short run and long run, as the
conventional wisdom suggests. Openness seems to have a growth enhancing effect.
Agriculture share of GDP has a negative impact on GDP growth. The possible
rationale for this is explained earlier – as the economy moves away from the primary
sector, becoming more industrialised, it moves to a higher growth path. As we
mentioned above, the results from Table 5.3 merely provides us with an initial view
of the story and we must be cautious interpreting these results.
Figure 5.7 shows a scatter plot between inflation and unexplained growth derived
from the OLS estimation in column 1 of Table 5.3. It does not show any clear
evidence of a strong negative relationship between the two. However, as we have
said that these results are based on some preliminary estimations. A more rigorous
approach follows in the following sections.
133
.2
Figure 5.7: Conditional Correlation between Inflation and Growth, 1961-2010
0
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Residuals
.4
Fitted values
Source: Graph generated from the estimation done by the author in column 1 of Table 5.3.
Note: All cases of inflation greater than 40 per cent are excluded in the estimation to avoid the outlier
effect of inflation.
5.3.1 Static panel estimation results
This section presents results based on Fixed Effects (FE) and Random Effects (RE)
models the two most common models used in panel data estimations. Such panel
estimations are superior to simple OLS as they can capture the country heterogeneity
more efficiently. We do not use the lagged dependent variable on the right hand side
of the regression as it may cause bias in the estimators. Kumar and Woo (2010, p.
12) state that “in the dynamic panel setting, the within transformation in the
estimation process of FE introduces a correlation between transformed lagged
dependent variable and transformed error,…[making] FE inconsistent.” Therefore all
estimations performed in this section are within the static framework. In the case of
RE models, it is assumed that the observable regressors are uncorrelated with the
unobservable characteristics in both country specific effects and error term. This
134
assumption is somewhat relaxed in the case of FE model which does not impose that
country specific effects and observable regressors are uncorrelated.
Using the two estimation techniques several regressions are run. Tables 5.4.1, 5.4.2,
and 5.4.3 record the best possible results from various estimations. To begin with,
Table 5.4.1 provides results where regressors FD, GOVCON, OPEN, and AGR are
in their level form. In both sets of estimations (using two measures of the dependent
variable) the Hausman test shows that the FE model is preferable to the RE one. The
FE estimates in Table 5.4.1 provides turning points of inflation at around 15 and 17
per cent for real GDP growth and real GDP per capita growth as dependent variables,
respectively. Both coefficients of linear and squared of inflation are significant. In
terms of taking care of the outliers of inflation, we consider case 1 of inflation,
ignoring all observations when inflation rate is greater than 40 per cent. In this
instance, apart from growth in HCONPC no other explanatory variables are found to
be significant.91
Table 5.4.1: Fixed and Random Effects Panel Regressions (Case 1)
Dependent variable
Inflation
2
Inflation
Turning point
∆ ln HCONPC
ln FD
ln GOVCON
ln OPEN
Real GDP Growth
Real GDP Per Capita Growth
(1)
(2)
(3)
(4)
FE1
RE1
FE2
RE2
0.177*
0.0612
0.155*
0.0182
(0.0882)
(0.106)
(0.0846)
(0.106)
-0.563**
-0.212
-0.433**
-0.02
(0.247)
(0.268)
(0.187)
(0.23)
15.71
14.43
17.89
45.50
0.234**
0.274***
0.23***
0.281***
(0.0797)
(0.0825)
(0.073)
(0.0814)
-0.0116
-0.00445
-0.0136*
-0.00874*
(0.0077)
(0.0051)
(0.0069)
(0.0051)
0.0167
-0.0107
0.0214
-0.0102
(0.0162)
(0.0085)
(0.0178)
(0.0097)
0.0227
0.00681
0.0206
0.00473
(0.0135)
(0.0044)
(0.0126)
(0.0053)
91
We also made an attempt to estimate the equations, in the static and dynamic frameworks (results of
the latter are presented in the following sections), with a conditionality variable (country × DUMOIL)
and (country × DUMCOMPR) – the multiplicative dummies – to test if oil and commodity price
shocks have a growth effect in countries with oil reserves and self-sufficiency in food production.
These versions of estimates were found to be insignificant and therefore are not reported.
135
ln AGR
0.00607
-0.00297
-0.00164
-0.012
(0.0111)
(0.0076)
(0.0115)
(0.0087)
0.011
-0.00331
-0.00226
0.0151
(0.0232)
(0.0178)
(0.0212)
(0.018)
-0.0269
-0.0111
-0.0192
0.00427
(0.033)
(0.0181)
(0.0323)
(0.0203)
388
388
388
388
14
14
14
14
R-squared overall
0.20
0.35
0.20
0.38
Within
0.34
0.31
.0.35
0.31
DUMOIL
DUMCOMPR
Observations
Number of Countries
Between
Hausman test:
Chi-square/(p-value)
Countries
0.08
0.81
0.15
0.83
36.84
54.58
(0.003)
(0.00)
Bangladesh, Cambodia, India, Indonesia, Lao PDR,
Malaysia, Pakistan, The Philippines, Thailand, Vietnam,
Kazakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan.
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effect of inflation.
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
5.
In Hausman test the null hypothesis is that Random Effect model is preferable to Fixed
Effect model.
6.
Constant term and time dummies are not reported to conserve space.
Since we argued that our preferred form of the control variables is in first differenced
form (growth rates92) Table 5.4.2 presents results incorporating the first differenced
forms. Here again FE is more suitable than RE according to Hausman test. In FE
models only the squared term of the inflation is significant but the linear one is not.
All cases of inflation rate greater than 40 per cent are excluded. The turning points in
this case (from the preferred FE models) seem to be more conservative than the
previous ones, around 13 and 14 per cent for two measures of dependent variables,
respectively. Growth in HCONPC shows strong positive impact on economic growth
92
First difference of natural logarithm of a variable is a close approximation of the growth rate of that
variable.
136
as the previous models presented in Table 5.4.1. In the case of other control
variables, growths in FD and AGR have significant negative impact on economic
growth. In terms of shocks, both oil and commodity prices are significant, the former
having a negative and the latter having a positive impact on growth. We explored
rationale behind such possibilities in the earlier section.
Table 5.4.2: Fixed and Random Effects Panel Regressions (Case 2)
Dependent variable
Inflation
2
Inflation
Turning point
Real GDP Growth
Real GDP Per Capita Growth
(1)
(2)
(3)
(4)
FE3
RE3
FE4
RE4
0.163
0.0751
0.139
0.0633
(0.093)
(0.0759)
(0.086)
(0.0829)
-0.622**
-0.267
-0.481**
-0.0996
(0.246)
(0.245)
(0.187)
(0.211)
13.10
14.06
14.44
31.77
0.232***
0.282***
0.227***
0.294***
(0.074)
(0.0729)
(0.0668)
(0.0701)
-0.0835**
-0.0238
-0.0817**
-0.00975
(0.0364)
(0.0353)
(0.0325)
(0.034)
0.0188
0.0217
0.0107
0.0141
(0.0266)
(0.0317)
(0.0275)
(0.0338)
∆ ln OPEN
0.00338
-0.00388
-0.00513
-0.0117
(0.016)
(0.0181)
(0.0146)
(0.0184)
∆ ln AGR
-0.0649*
-0.0869**
-0.0867***
-0.117***
(0.0335)
(0.0382)
(0.0164)
(0.0326)
-0.0303**
0.0217
-0.0323**
0.0353**
(0.0104)
(0.0202)
(0.0109)
(0.0156)
0.0637**
0.0144
0.0764***
0.0245
(0.0218)
(0.0163)
(0.0185)
(0.0182)
380
380
380
380
14
14
14
14
R-squared overall
0.31
0.35
0.32
0.38
Within
.0.36
0.33
.0.38
0.34
∆ ln HCONPC
∆ ln FD
∆ ln GOVCON
DUMOIL
DUMCOMPR
Observations
Number of countries
Between
Hausman test:
Chi-square/(p-value)
Countries
0.004
0.61
0.03
0.77
45.07
63.68
(0.00)
(0.00)
Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia,
Pakistan, The Philippines, Thailand, Vietnam, Kazakhstan,
Kyrgyz Republic, Papua New Guinea, and Tajikistan.
Notes:
137
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effect of inflation.
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
5.
In Hausman test the null hypothesis is that Random Effect model is preferable to Fixed
Effect model.
6.
Constant terms and time dummies are not reported to conserve space.
Table 5.4.3 shows the results using the case 3 of inflation where inflation is
transformed as π/(1+ π). In terms of the turning points of inflation, the results are
more conservative than the ones presented in previous tables. According to the FE
estimates, as this is preferred over RE, the turning points are around 8 per cent with
only squared term of inflation being significant. The only other result that is
significantly different from the previous cases is the impact of oil price shocks. In
this instance, it has a significant positive impact on growth.
Table 5.4.3: Fixed and Random Effects Panel Regressions (Case 3)
Dependent Variable
Inflation
Inflation2
Turning point
∆ ln HCONPC
∆ ln FD
∆ ln GOVCON
∆ ln OPEN
∆ ln AGR
DUMOIL
Real GDP Growth
Real GDP Per Capita Growth
(1)
(2)
(3)
(4)
FE5
RE5
FE6
RE6
0.0951
0.0768
0.0745
0.0741
0.0814
0.069
0.0862
0.0785
-0.609***
-0.503***
-0.456**
-0.339**
0.158
0.139
0.152
0.139
8.46
8.26
8.89
12.27
0.229***
0.278***
0.222***
0.288***
0.0755
0.0725
0.0678
0.0692
-0.0784*
-0.0198
-0.0773**
-0.00579
0.0389
0.0368
0.0343
0.0356
0.0263
0.0283
0.0205
0.0234
0.027
0.0311
0.027
0.0325
-0.0141
-0.0206
-0.0253**
-0.0319**
(0.011)
(0.0129)
(0.0115)
(0.0139)
-0.0788**
-0.101**
-0.101***
-0.132***
(0.0359)
(0.0399)
(0.0216)
(0.0336)
0.0431*
0.0274
0.0548***
0.0416**
138
0.022
0.0218
0.0182
0.0172
0.0761**
0.018
0.0906***
0.0285
(0.0253)
(0.0165)
(0.0217)
(0.0181)
384
384
384
384
14
14
14
14
R-squared overall
0.39
0.43
0.37
0.43
Within
.0.44
0.42
0.44
0.40
DUMCOMPR
Observations
Number of countries
Between
Hausman test:
Chi-square/(p-value)
Countries
0.00
0.65
0.03
0.78
42.75
62.17
(0.00)
(0.00)
Bangladesh, Cambodia, India, Indonesia, Lao PDR, Malaysia,
Pakistan, The Philippines, Thailand, Vietnam, Kazakhstan,
Kyrgyz Republic, Papua New Guinea, and Tajikistan.
Notes:
1.
Estimation is based on annual observations and inflation, π, in the table is transformed as (
) to avoid the outlier effect of inflation.
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation. It is calculated as β1 / (2 β2 + β1) where β1 and β2 are the
coefficients of linear and squared terms of inflation respectively.
5.
In Hausman test the null hypothesis is that Random Effect model is preferable to Fixed
Effect model.
6.
Constant term and time dummies are not reported to conserve space.
In summary, perhaps the estimates of turning point between 15 and 17 per cent
according to FE1 and FE2 presented in Table 5.4.1 are better than the others since
both the coefficients of inflation are significant in this instance. In short, the turning
point does not seem to be 5 per cent which calls for caution for policy makers when
targeting inflation below 5 per cent.
5.3.2 Dynamic panel estimation results
In this section, we perform dynamic panel estimation techniques since FE and RE
provide biased results incorporating lagged dependent variable as a regressor. It is
difficult to find an appropriate external instrument for inflation and other economic
variables to overcome the endogeneity problem. We use System Generalised Method
of Moment (SGMM) approach arising from the works of Arellano and Bover (1995)
139
and Blundell and Bond (1998) to take care of this endogeneity issue. This approach
uses suitable lagged levels and lagged first differences of the regressors as their
instruments. It has recently gained popularity and is extensively used in applied
economic research (see Kumar & Woo 2010). This estimator helps eliminate any
endogeneity that may arise because of the correlation of country-specific, timeinvariant, factors and the right hand side variables. In addition, in this type of
regressions, lagged values of the regressors are used to prevent simultaneity or
reverse causality. We also use the one-step estimator as opposed to two-step
estimator since the latter does not produce any meaningful results.
Table 5.5.1 provides initial results by regressing real GDP growth on different
regressors. Adding different regressors changes the threshold levels of inflation. It
indicates that the relationship between economic growth and inflation is not simple
and it is necessary to take into account the effects of other variables into this
relationship. The results showing a threshold level of 12.94 per cent, in column 3 and
column 4, seems to be a good estimate as both the inflation coefficients are
significant at 1 per cent level. The results are robust since post-regression diagnostic
tests are satisfactory showing that the underlying assumptions of the model are valid.
For instance, AR (1) and AR (2) tests are performed to test first and second order
serial correlation in the disturbances. One should reject the null hypothesis of the
absence of first order serial correlation and not reject the absence of second order
serial correlation (see Baltagi, Demetriades & Law 2009). Our tests satisfy these
conditions. The other diagnostic test, Sargan test does not reject the overidentification restrictions. In fact these conditions relating to post-regression
diagnostic tests are met in all SGMM estimations that follow.
Table 5.5.1: Impact of Inflation on Growth, Dynamic Panel Estimations
Dependent variable is real GDP growth
Growth (-1)
Growth (-2)
(1)
(2)
(3)
(4)
SGMM1
SGMM2
SGMM3
SGMM4
0.131
0.152**
0.15**
0.15**
(0.0857)
(0.0719)
(0.0733)
(0.0733)
-0.141***
-0.0967*
-0.0483
-0.0483
(0.05)
(0.0534)
(0.0736)
(0.0736)
140
Inflation
2
Inflation
Turning point
0.0158
0.0504
0.167***
0.167***
(0.0465)
(0.042)
(0.0562)
(0.0562)
-0.0345
-0.0488*
-0.645***
-0.645***
(0.0336)
(0.0267)
(0.115)
(0.115)
22.89
51.63
12.94
12.94
0.208***
0.237***
0.237***
(0.0552)
(0.0673)
(0.0673)
-0.0596***
-0.0596***
(0.0203)
(0.0203)
0.0524***
0.0524***
(0.0168)
(0.0168)
0.0128
0.0128
(0.0195)
(0.0195)
-0.0267**
-0.0267**
(0.0124)
(0.0124)
∆ ln HCONPC
∆ ln FD
∆ ln FD (-1)
∆ ln GOVCON
∆ ln GOVCON (-1)
∆ ln OPEN
∆ ln OPEN (-1)
∆ ln AGR
∆ ln AGR (-1)
0.0154
0.0154
(0.0189)
(0.0189)
0.075*
0.075*
(0.0397)
(0.0397)
-0.0565*
-0.0565*
(0.0319)
(0.0319)
-0.089**
-0.089**
(0.0349)
(0.0349)
DUMOIL
0.0202***
(0.0078)
DUMCOMPR
0.057***
(0.0155)
Observation
Number of countries
SGMM estimation
method
AR (1) test (p-value)
AR (2) test (p-value)
Sargan test (p-value)
Countries
435
396
370
370
14
14
14
14
One step
One step
One step
One step
-2.98
-2.83
-2.9
-2.9
(0.00)
(0.00)
(0.00)
(0.00)
0.24
-0.58
0.31
0.31
(0.80)
(0.55)
(0.75)
(0.75)
353.18
432.82
537.81
537.81
(0.14)
(0.14)
(0.87)
(0.87)
Bangladesh, Cambodia, India, Indonesia, Lao PDR,
Malaysia, Pakistan, The Philippines, Thailand,
Vietnam, Kazakhstan, Kyrgyz Republic, Papua New
Guinea, and Tajikistan.
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effects of inflation.
141
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
5.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
6.
AR (1) and AR (2) tests are Arellano-Bond first and second order serial correlation tests
respectively. The null hypothesis is that residuals show no serial correlation.
7.
Sargan test is for over identifying restrictions. The null hypothesis is that over-identifying
restrictions are valid.
8.
Time dummies are not reported to conserve space.
9.
Variables lagged in one period are represented by -1 within parentheses after the variable.
Table 5.5.2 and 5.5.3 have produced GMM estimation results in the case of
dependent variable real GDP growth and real GDP per capita growth, respectively,
using three different cases of inflation conditioned upon other variables. In the first
case, the threshold figure varies from 10 to 15 per cent, while in the second case, the
threshold varies from 11 to 14 per cent. The results of threshold inflation depending
on measures of economic growth (GDP vs. GDP per capita) do not vary much.
Table 5.5.2: System GMM Estimations (Case 1)
Dependent variable is real GDP growth
Growth (-1)
(1)
(2)
(3)
SGMM5
SGMM6
SGMM7
0.15**
0.154**
0.153**
(0.0733)
(0.0733)
(0.0731)
-0.0483
-0.0446
-0.0455
(0.0736)
(0.0736)
(0.0739)
Inflation
0.167***
0.248***
0.315***
(0.0562)
(0.0607)
(0.0623)
Inflation2
-0.645***
-1.12***
-1.64***
(0.115)
(0.139)
(0.175)
12.94
14.89
10.62
0.237***
0.235***
0.234***
(0.0673)
(0.0659)
(0.0654)
-0.0596***
-0.0592***
-0.059***
(0.0203)
(0.0198)
(0.0197)
0.0524***
0.0531***
0.0523***
(0.0168)
(0.0165)
(0.0164)
Growth (-2)
Turning point
∆ ln HCONPC
∆ ln FD
∆ ln FD (-1)
142
∆ ln GOVCON
∆ ln GOVCON (-1)
∆ ln OPEN
∆ ln OPEN (-1)
∆ ln AGR
∆ ln AGR (-1)
DUMOIL
DUMCOMPR
Observations
0.0128
0.0124
0.0142
(0.0195)
(0.0192)
(0.0196)
-0.0267**
-0.025**
-0.0252**
(0.0124)
(0.0121)
(0.012)
0.0154
0.0125
0.0106
(0.0189)
(0.0165)
(0.016)
0.075*
0.0788**
0.0806**
(0.0397)
(0.04)
(0.04)
-0.0565*
-0.0647**
-0.0675**
(0.0319)
(0.0315)
(0.0317)
-0.089**
-0.0931***
-0.0939***
(0.0349)
(0.0345)
(0.0342)
0.0202***
0.0194**
0.0188**
(0.0078)
(0.0081)
(0.0082)
0.057***
0.0133
0.0156*
(0.0155)
(0.0094)
(0.0092)
370
373
373
Number of countries
SGMM estimation
method
14
14
14
One step
One step
One step
AR (1) test (p-value)
-2.9
-2.9
-2.9
(0.00)
(0.00)
(0.00)
AR (2) test (p-value)
0.31
0.32
0.28
(0.75)
(0.74)
(0.77)
Sargan test (p-value)
537.81
544.33
547.88
Countries
(0.87)
(0.85)
(0.82)
Bangladesh, Cambodia, India, Indonesia, Lao PDR,
Malaysia, Pakistan, The Philippines, Thailand,
Vietnam, Kazakhstan, Kyrgyz Republic, Papua New
Guinea, and Tajikistan.
Notes:
1.
Estimation is based on annual observations. To avoid outlier effect of inflation three cases
are considered. In column 1 all cases of inflation greater than 40 per cent are excluded. In
column 2 inflation, π, is transformed as ln (1 + π) while in column 3 it is transformed as (
).
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
5.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation. In column 1, 2, and 3 it is calculated as (β 1 / 2β2), (
–
1), and β1 / (2 β2 + β1) where β1 and β2 are the coefficients of linear and squared terms of
inflation respectively.
143
6.
AR (1) and AR (2) tests are Arellano-Bond first and second order serial correlation tests
respectively. The null hypothesis is that residuals show no serial correlation.
7.
Sargan test is for over identifying restrictions. The null hypothesis is that over-identifying
restrictions are valid.
8.
Time dummies are not reported to conserve space.
9.
Variables lagged in one period are represented by -1 within parentheses after the variable.
Table 5.5.3: System GMM Estimations (Case 2)
Dependent variable real GDP per capita growth
Growth (-1)
Growth (-2)
Inflation
2
Inflation
Turning point
∆ ln HCONPC
∆ ln FD
∆ ln FD (-1)
∆ ln GOVCON
∆ ln GOVCON (-1)
∆ ln OPEN
∆ ln OPEN (-1)
∆ ln AGR
∆ ln AGR (-1)
DUMOIL
DUMCOMPR
(1)
(2)
(3)
SGMM8
SGMM9
SGMM10
0.188**
0.193**
0.193**
(0.0841)
(0.0834)
(0.0827)
0.00421
0.00193
0.00057
(0.0499)
(0.0498)
(0.0507)
0.157***
0.248***
0.309***
(0.0539)
(0.063)
(0.0667)
-0.555***
-1.07***
-1.54***
(0.102)
(0.156)
(0.214)
14.17
14.18
11.15
0.234***
0.23***
0.229***
(0.0555)
(0.0532)
(0.0527)
-0.0598***
-0.0606***
-0.06***
(0.0228)
(0.0228)
(0.0227)
0.053***
0.0545***
0.0537***
(0.0128)
(0.0116)
(0.0117)
0.00632
0.00653
0.00825
(0.0215)
(0.0211)
(0.0215)
-0.0097
-0.00814
-0.00802
(0.0145)
(0.0137)
(0.0137)
-0.00412
-0.0105
-0.0121
(0.0173)
(0.0163)
(0.0156)
0.0762*
0.0792**
0.081**
(0.0392)
(0.0397)
(0.0398)
-0.0917***
-0.0991***
-0.101***
(0.0242)
(0.0237)
(0.0241)
-0.0708*
-0.0744*
-0.075*
(0.0409)
(0.0393)
(0.0391)
-0.00773
-0.00818
-0.0087
(0.0075)
(0.0079)
(0.0081)
0.0344***
0.0158
0.0178*
(0.0131)
(0.0101)
(0.0101)
144
Observations
370
373
373
Number of countries
SGMM estimation
method
14
14
14
One step
One step
One step
AR (1) test (p-value)
-2.58
-2.57
-2.57
(0.00)
(0.01)
(0.01)
AR (2) test (p-value)
1.28
1.32
1.3
(0.19)
(0.18)
(0.19)
Sargan test (p-value)
545.72
554.65
558.17
Countries
(0.81)
(0.76)
(0.73)
Bangladesh, Cambodia, India, Indonesia, Lao PDR,
Malaysia, Pakistan, The Philippines, Thailand, Vietnam,
Kazakhstan, Kyrgyz Republic, Papua New Guinea, and
Tajikistan.
Notes:
1.
Estimation is based on annual observations. To avoid outlier effect of inflation three cases
are considered. In column 1 all cases of inflation greater than 40 per cent are excluded. In
column 2 inflation, π, is transformed as ln (1 + π) while in column 3 it is transformed as (
).
2.
All standard errors are robust and reported below coefficient estimates.
3.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
4.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
5.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation. In column 1, 2, and 3 it is calculated as (β 1 / 2β2), (
–
1), and β1 / (2 β2 + β1) where β1 and β2 are the coefficients of linear and squared terms of
inflation respectively.
6.
AR (1) and AR (2) tests are Arellano-Bond first and second order serial correlation tests
respectively. The null hypothesis is that residuals show no serial correlation.
7.
Sargan test is for over identifying restrictions. The null hypothesis is that over-identifying
restrictions are valid.
8.
Time dummies are not reported to conserve space.
9.
Variables lagged by one period are represented by -1 within parentheses after the variable.
5.3.3 Summary of the results from static and dynamic panel estimations
A summary of the results from static and dynamic panel estimations are presented in
Tables 5.6.1 and 5.6.2, considering the dependent variable real GDP growth and real
GDP per capita growth respectively. In the case of static estimations only FE
estimates are reported as they are superior to RE estimates (revealed by Hausman
145
test). The results on threshold levels broadly vary from 8 to 15 per cent. Columns 1
and 2 in Table 5.6.1 show FE estimates on turning points based on case 1 (inflation
less than 40 per cent) and case 2 (inflation transformed into (π/1+π)) of inflationtreatment, respectively. It is interesting to note that case 1 provides a higher
threshold, at 13 per cent, than case 2, at around 8 per cent. Perhaps the explanation
behind this is that in the former estimation, we dropped the cases of inflation higher
than 40 per cent altogether. This ignores the unusual cases of growth as well (for
instance severe decline in growth rates as a result of very high inflation). In the latter
case, however, only inflation is transformed to avoid the outlier effect on growth.
The unusual cases of growth and other control variables were not dropped. We notice
a similar situation in columns 1 and 2 of FE estimates in Table 5.6.2. The turning
points are slightly higher, around 14 and 9 per cent, respectively.
In the case of dynamic panel estimation, using SGMM, we notice variations in
turning points depending on the way in which we treat the dependent variable and
inflation cases. The estimated thresholds broadly vary between 10 and 15 per cent. In
short, we observe differences in inflation threshold due to different modelling
techniques and estimation methods. But none of these estimates justifies a case for
keeping inflation at 5 per cent or below.
Table 5.6.1: Summary of Results from Static and Dynamic Panel Estimations (Case 1)
Dependent variable is real GDP growth
Static Models
Dynamic Models
(1)
(2)
(3)
(4)
(5)
FE3
FE5
SGMM5
SGMM6
SGMM7
13.10
8.46
12.94
14.89
10.62
Growth (-1)
NA
NA
(+)**
(+)**
(+)**
Growth (-2)
NA
NA
(-)
(-)
(-)
∆ ln HCONPC
(+)***
(+)***
(+)***
(+)***
(+)***
∆ ln FD
(-)**
(-)*
(-)***
(-)***
(-)***
∆ ln FD (-1)
NA
NA
(+)***
(+)***
(+)***
∆ ln GOVCON
(+)
(+)
(+)
(+)
(+)
∆ ln GOVCON (-1)
NA
NA
(-)**
(-)**
(-)**
Turning point of
inflation
146
∆ ln OPEN
(+)
(-)
(+)
(+)
(+)
∆ ln OPEN (-1)
NA
NA
(+)*
(+)**
(+)**
∆ ln AGR
(-)*
(-)**
(-)*
(-)**
(-)**
∆ ln AGR (-1)
NA
NA
(-)**
(-)***
(-)***
DUMOIL
(-)**
(+)*
(+)***
(+)**
(+)**
DUMCOMPR
(+)**
(+)**
(+)***
(+)
(+)*
Table 5.6.2: Summary of Results from Static and Dynamic Panel Estimations (Case 2)
Dependent variable is real GDP per capita growth
Static Models
Dynamic Models
(1)
(2)
(3)
(4)
(5)
FE4
FE6
SGMM8
SGMM9
SGMM10
14.44
8.89
14.17
14.18
11.15
Growth (-1)
NA
NA
(+)**
(+)**
(+)**
Growth (-2)
NA
NA
(+)
(+)
(+)
∆ ln HCONPC
(+)***
(+)***
(+)***
(+)***
(+)***
∆ ln FD
(-)**
(-)**
(-)***
(-)***
(-)***
∆ ln FD (-1)
NA
NA
(+)***
(+)***
(+)***
∆ ln GOVCON
(+)
(+)
(+)
(+)
(+)
∆ ln GOVCON (-1)
NA
NA
(-)
(-)
(-)
∆ ln OPEN
(-)
(-)**
(-)
(-)
(-)
∆ ln OPEN (-1)
NA
NA
(+)*
(+)**
(+)**
∆ ln AGR
(-)***
(-)***
(-)***
(-)***
(-)***
∆ ln AGR (-1)
NA
NA
(-)*
(-)*
(-)*
DUMOIL
(-)**
(+)***
(-)
(-)
(-)
DUMCOMPR
(+)***
(+)***
(+)***
(+)
(+)*
Turning point of
inflation
In the following section, we perform some robustness checks by taking subsamples
and using our preferred estimation technique SGMM.
5.3.4 Robustness checks and comparing the differences in the threshold levels of
inflation
Table 5.7.1 presents the results on turning points based on different time frames. The
findings broadly provide us with estimated threshold levels within the range of 8-15
147
per cent, close to what we have estimated in the above sections. All estimates show
threshold levels above 10 per cent, in other words, double digit figures.
Table 5.7.1: Inflation Turning Points in Different Time Frames
Dependent variable is real GDP growth
Inflation
2
Inflation
Turning
point
(1)
(2)
(3)
(4)
(5)
(6)
(8)
SGMM11
19602010
SGMM12
19702010
SGMM13
19802010
SGMM14
19902010
SGMM15
20002010
SGMM16
19601989
SGMM17
19601979
0.167***
0.177***
0.149***
0.225***
0.248**
0.161**
0.19***
-0.645***
-0.679***
-0.631***
-0.723***
-0.84***
-0.726***
-0.703***
12.94
13.03
11.8
15.56
14.76
11.08
13.51
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effect of inflation.
2.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
3.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
5.
Estimates of column (1) are reported from column (4) of Table 5.5.1.
6.
Control variables, time dummies, and post estimation tests (AR test and Sargan test) are not
reported to conserve space.
Table 5.7.2 shows the findings from subsamples based on different regions and
income groups. There is strong evidence from the results that poorer countries have a
higher threshold level of inflation. For instance, in column 1, when we drop
relatively richer East Asian countries, we find the threshold at around 14 per cent.
The threshold reduces, in column 2 and 3, as the mean real GDP per capita and real
household consumption per capita increases. This result convincingly proves one of
our research issues that threshold varies according to economic circumstances of
groups of countries. The result on threshold also shows that our estimates from
earlier sections are robust, since the range falls within 8-15 per cent.
148
Table 5.7.2: Impact of Inflation on Growth, the Regional Effect
Dependent variable is real GDP growth
(1)
(2)
(3)
SGMM18
Excluding East
Asia
SGMM19
Excluding
South Asia
SGMM20
Excluding Former
Command Economies
Inflation
2
Inflation
Turning point
Number of countries
Countries dropped
from the sample of 14
countries
0.216**
0.132**
0.094*
-0.756***
-0.596***
-0.571***
14.28
11.07
8.31
10
11
Indonesia,
Malaysia, The
Philippines, and
Thailand
Mean real GDP per
capita
Mean real household
consumption per capita
Bangladesh,
India, and
Pakistan
8
Cambodia, Lao PDR,
Vietnam, Kazakhstan,
Kyrgyz Republic, and
Tajikistan
534.24
1099.92
1268.83
385.9
682.1
724.15
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effect of inflation.
2.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
3.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
5.
Control variables, time dummies, and post estimation tests (AR test and Sargan test) are not
reported to conserve space.
6.
Unweighted mean values of real GDP per capita and real household consumption per capita
within each group over the period 1990-2010 are reported.
Next, we are interested to look at how the threshold of inflation might vary according
to changes in agricultural dependence, financial deepening, and trade openness. First,
Table 5.7.3 groups the countries according to above and below sample mean based
on these three criteria.
149
Table 5.7.3: Averages of Selected Variables in the Sample Countries, 1990-2010
Agriculture share of
GDP: Sample mean
24.63
Countries below sample mean
Countries above sample mean
Country
Country
Mean
Mean
Kazakhstan
10.28
Lao PDR
47.01
Thailand
10.44
Cambodia
38.91
Malaysia
11.1
Kyrgyz Republic
35.88
Indonesia
16.18
Papua New Guinea
34.74
The Philippines
16.28
Tajikistan
27.55
India
23.28
Vietnam
25.85
Bangladesh
23.89
Pakistan
24.07
Financial deepening:
Sample mean
45.25
Countries above sample mean
Countries below sample mean
Country
Country
Mean
Mean
Malaysia
114.37
Tajikistan
9.9
Thailand
97
Lao PDR
14.29
The Philippines
52.34
Cambodia
15.52
India
52.03
Kyrgyz Republic
15.66
Kazakhstan
19.83
Vietnam
Trade openness:
Sample mean
47.6
Papua New Guinea
34.4
Bangladesh
37.3
Pakistan
41.65
Indonesia
42.98
88.08
Countries above sample mean
Countries below sample mean
Country
Country
Mean
Mean
Malaysia
188.57
India
30.23
Papua New Guinea
113.91
Bangladesh
33.23
Vietnam
113.57
Pakistan
34.61
Thailand
111.71
Indonesia
58.04
Tajikistan
108.1
Lao PDR
67.33
Cambodia
104.72
The Philippines
86.09
Kyrgyz Republic
96.13
Kazakhstan
89.37
Table 5.7.4 presents the regression results based on the above criteria. The results are
consistent with what we have argued so far. The threshold varies according to the
levels of economic development, and less developed countries tend to have a higher
150
threshold level of inflation. For instance, in the case of agro dependence, countries
more dependent on agriculture appears to have a higher turning point, around 13 per
cent, compared to that of countries relatively less dependent on agriculture (turning
point at around 10 per cent; see columns 1 and 2 in Table 5.7.4). We find similar
evidence in the case of financial deepening and trade openness. The findings on
threshold vary, but remain within the range between 8 and 15 per cent. This again
proves that our estimates are robust.
Table 5.7.4: The Impact of Inflation on Growth Based on Structural Characteristics of
the Economy
Dependent variable is real GDP growth
Inflation
2
Inflation
Turning
point
Number of
countries
Countries
(1)
(2)
(3)
(4)
(5)
(6)
SGMM21
SGMM22
SGMM23
SGMM24
SGMM25
SGMM26
Agro dependence
Financial deepening
Trade openness
Least
Most
Most
Most
Least
Least
0.0764*
0.635***
0.0903*
0.651***
0.114
0.171***
-0.357***
-2.35***
-0.576***
-2.34***
-0.719**
-0.763***
10.7
13.51
7.83
13.91
7.92
11.2
4
Kazakhstan,
Thailand,
Malaysia,
and
Indonesia
4
Lao PDR,
Cambodia,
Kyrgyz
Republic,
and Papua
New
Guinea
4
Malaysia,
Thailand,
The
Philippines,
and India
4
Tajikistan,
Lao PDR,
Cambodia,
and Kyrgyz
Republic
4
Malaysia,
Papua
New
Guinea,
Vietnam,
and
Thailand
4
India,
Bangladesh,
Pakistan, and
Indonesia
Notes:
1.
Estimation is based on annual observations and all cases of inflation greater than 40 per cent
are excluded to avoid the outlier effect of inflation.
2.
***, **, and *, denote significance at 1%, 5%, and 10% respectively.
3.
Regressions use the Blundell and Bond (1998) system GMM (SGMM) estimator.
4.
The turning point of inflation is estimated by examining the partial derivatives of GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
5.
P-value for the linear term of inflation in column (5) is 0.153 and therefore the estimate is
significant at 16% significance level.
6.
Control variables, time dummies, and post estimation tests (AR test and Sargan test) are not
reported to conserve space.
151
7.
4 least and most agro dependent, financial deepening, and trade open countries are selected
from Table 5.7.4 for each group of estimation.
5.4 Conclusion
The empirical evidence based on panel estimations finds no support to keep inflation
at a very low level in the selected developing countries of Asia. The results are based
on the estimation techniques which take care of endogeneity problem, an issue many
past studies have failed to address. Our technique to find the threshold level of
inflation is similar to that of Pollin and Zhu (2006). The findings are broadly similar
to those of Pollin and Zhu’s (2006) study as well. Their study covers a wider range of
countries (80 middle and low income countries). The findings of this chapter are
based on a much smaller sample size of 14 countries. While Pollin and Zhu (2006)
suggest a threshold level of inflation between 15 and 18 per cent, our estimates are
slightly more conservative, between 8 and 15 per cent. But the range is still close to
the findings from other cross-country studies reviewed in Chapter 3. In short, our
results find no justification for targeting inflation at 5 per cent or below as advised by
the IMF. The next chapter seeks to investigate this empirical issue in a countryspecific context.
152
Appendix to Chapter 5
Table A.5.1: List of Variables and Their Sources
Mnemonic
Variable description
Source
Indicator code
RGDP
GDP (constant 2000 USD).
GDP, gross domestic product, at
purchaser's prices is the sum of gross
value added by all resident producers
in the economy plus any product
taxes and minus any subsidies not
included in the value of the products.
It is calculated without making
deductions for depreciation of
fabricated assets or for depletion and
degradation of natural resources. Data
are in constant 2000 U.S. dollars.
Dollar figures for GDP are converted
from domestic currencies using 2000
official exchange rates. For a few
countries where the official exchange
rate does not reflect the rate
effectively applied to actual foreign
exchange transactions, an alternative
conversion factor is used.
WDI
NY.GDP.MKTP.KD
RGDPCAP
GDP per capita (constant 2000 USD).
GDP per capita is gross domestic
product divided by midyear
population. Data are in constant U.S.
dollars.
WDI
NY.GDP.PCAP.KD
CPI
Consumer price index (2005 = 100).
Consumer price index reflects
changes in the cost to the average
consumer of acquiring a basket of
goods and services that may be fixed
or changed at specified intervals, such
as yearly. The Laspeyres formula is
generally used.
WDI
FP.CPI.TOTL
INFCPI
Inflation, consumer prices (annual
%).
Inflation is measured by the
consumer price index.
WDI, IFS,
WEO, SDBS
FP.CPI.TOTL.ZG
M2GDP
(FD)
Broad money (% of GDP); M2
Nominal GDP ratio.
Broad money is the sum of currency
outside banks; demand deposits other
than those of the central government;
the time, savings, and foreign
WDI
FM.LBL.BMNY.GD.ZS
153
currency deposits of resident sectors
other than the central government;
bank and traveller’s checks; and other
securities such as certificates of
deposit and commercial paper.
GOVCON
General government final
consumption expenditure (% of
GDP).
General government final
consumption expenditure (formerly
general government consumption)
includes all government current
expenditures for purchases of goods
and services (including compensation
of employees). It also includes most
expenditure on national defence and
security, but excludes government
military expenditures that are part of
government capital formation.
WDI
NE.CON.GOVT.ZS
HCONPC
Household final consumption
expenditure per capita (constant 2000
USD).
Household final consumption
expenditure per capita (private
consumption per capita) is calculated
using private consumption in constant
2000 prices and World Bank
population estimates. Household final
consumption expenditure is the
market value of all goods and
services, including durable products
(such as cars, washing machines, and
home computers), purchased by
households. It excludes purchases of
dwellings but includes imputed rent
for owner-occupied dwellings. It also
includes payments and fees to
governments to obtain permits and
licenses. Here, household
consumption expenditure includes the
expenditures of nonprofit institutions
serving households, even when
reported separately by the country.
Data are in constant 2000 U.S.
dollars.
WDI
NE.CON.PRVT.PC.KD
OPEN
Trade (% of GDP)
Trade is the sum of exports and
imports of goods and services
measured as a share of gross domestic
product.
WDI
NE.TRD.GNFS.ZS
154
AGR
OIL
COMPR
Agriculture value added as a % of
GDP
UK Brent crude oil index (2005=100)
WDI
Non-energy commodity price index
by the World Bank for low and
middle income countries (2005=100)
IFS
NV.AGR.TOTL.ZS
IFS
155
Chapter 6
The Relationship between Inflation and Growth: The
Bangladesh Experience
6.1 Introduction
This chapter investigates the research questions relating to growth-inflation nexus in
the context of Bangladesh. The purpose of this chapter is to find out if a countryspecific study provides similar evidence to that of cross-country panel study. The
panel study carried out in Chapter 5 includes 14 developing countries of Asia where
relative dissimilarity amongst the countries exists. Although panel estimation models
used in Chapter 5 are said to be efficient in taking care of the persistent unobserved
heterogeneity across countries, studies, such as Temple (2000), mention that the
impact of inflation might vary due to differences in the cross-country setting. In
addition, a country-specific time series analysis allows greater freedom in using
control variables relevant to that particular country. More importantly we can allow
for the specific historical and institutional characteristics of the country in our
analysis.
The threshold estimates of inflation in Chapter 5 vary approximately between 8 and
15 per cent, depending on variations in structural issues in the samples and different
modelling and estimation techniques used. We reiterate that none of the estimates of
threshold is as low as 5 per cent and it tends to increase for groups of countries with
lower levels of development. For estimations using subsamples comprised of
Bangladesh, the threshold figures appear to be within double digits. The task of this
chapter’s investigation is to provide a more specific estimate of inflation threshold
for one country, Bangladesh. Considering Bangladesh’s level of development, we
expect the threshold figure would be more than 10 per cent. This expected figure
substantially differs from two recent important studies on Bangladesh reviewed in
Chapter 4. The first one by Ahmed and Mortaza (2005) suggests that inflation
threshold for Bangladesh is at 6 per cent. The other study by Hayat and Kalirajan
(2009) does not confirm any threshold level, but suggests that increase in inflation
from any level would hurt economic growth in Bangladesh.
156
The chapter is organised as follows. Section 6.2 provides an overview of the countryspecific case. It attempts to provide a rationale for a close examination of Bangladesh
– an interesting country for development discourse.93 The stylised facts revealed
from trends in economic growth and inflation in the country is discussed in Section
6.3. The next two sections carry out an econometric exercise to determine the
growth-inflation nexus and the inflation threshold in Bangladesh, respectively.
Section 6.4 examines the output-price level relationship in a cointegration framework
using annual data in order to understand the short run dynamics, between economic
growth and inflation, and the long run equilibrium relationship, between output and
price level. Section 6.5 estimates the threshold level of inflation in a non-linear
framework using control variables pertinent to the Bangladesh economy. Finally,
Section 6.6 presents some concluding remarks.
6.2 An Overview of the Bangladesh Perspective
The country Bangladesh provides an interesting example of a country-specific case
study. The Economist concludes that Bangladesh is “one of the most intriguing
puzzles in development” because “it has done better than most countries in
improving the basic standard of living of its people.”94 Table 6.1 provides some of
the key demographic and geographic characteristics of Bangladesh. It is a small but
densely populated developing country in South Asia, with 31.5 per cent people living
93
During the first few years of its independence, Bangladesh experienced high inflation and low
growth. The then US Secretary of State Henry Kissinger described Bangladesh as an “international
basket case” and Kevin Rafferty of the Financial Times characterised it as “the end of the great
development dream”. Two World Bank economists, Just Faaland and Jack Parkinson (1976), termed
Bangladesh as “the test case of development” – meaning that if development could happen in
Bangladesh, it could happen anywhere. But in less than three decades, Bangladesh became an
example of success. One leading economic development textbook (Todaro & Smith 2006, p. 89)
observed, “And without question, from the viewpoint of the broader meaning of development,
Bangladesh seemed to be forging ahead in the early years of the twenty-first century. As a result, there
are good reasons to expect Bangladesh to soon move into the lead in income as well.” The UNDP
Human Development Report (2000) summarised Bangladesh’s achievements in the following words:
“Bangladesh’s case stood out as a potentially instructive story of development. This was,
indeed, seen as one of those rare cases of graduation on an international scale, from the status
of the poorest of the poor to the place of lead performer among LDCs, and in some respects,
even placing itself among the better performers in the entire developing world. It was like a
re-birth for Bangladesh, having moved from the status of being at the margin of history in the
whirlpool of history, from the status of a mere testing site to that of a learning site from
where even master development discourse can benefit.”
94
The Economist, Out of the Basket, 2 November 2012. Available at
http://www.economist.com/blogs/feastandfamine/2012/11/bangladesh
157
below the national poverty line.95 Although it is the 8th most populous country of the
world (see Table 6.1), it is expected to experience a demographic dividend in the
near future. This is because it is passing through the third phase of demographic
transition with declining birth and death rates, leading to a growing working age
population (see World Bank 2012, p. 2). This attribute is expected to payoff, for
instance, by allowing opportunities for greater remittances from abroad and domestic
demand-led growth.
Table 6.1: Key Demographic and Geographic Features of Bangladesh
Indicators
Facts and figures
Population
149 million (approximately)*
World ranking in terms of population
8th most populous nation
Density of population
800 people per square kilometre (approximately)
Percentage of young population
70% under the age of 25
Religious composition
88% Muslims and 11% Hindus (approximately)
Climate
Subtropical
Terrain
Mostly flat low-lying plains, hilly in the southeast
Key natural resources
Natural gas, arable land, timber, and coal
Source: Central Intelligence Agency, The United States, The World Fact Book, available at
https://www.cia.gov/library/publications/the-world-factbook/geos/bg.html; and Bangladesh Bank,
Bangladesh in brief, available at http://www.bangladesh-bank.org.
Note: * Figure reported in January 2011 by the Bangladesh Bureau of Statistics, a government agency
of the country. However the figure stands at 162 million, approximately, according to the World
Bank, World Development Indicators.
The country’s long border with its neighbour India has always been of political and
economic significance. On the economic side, trade with India affects some of the
major economic indicators such as trade deficits and inflation. In recent years,
several possible opportunities have put the country into a greater geographic and
strategic importance in the region. These include potential oil reserves and the
establishment of a deep sea port in the Bay of Bengal and the construction of the
Asian Highway which would connect several Asian countries to Bangladesh. Such
95
The figure 31.5 per cent is poverty headcount ratio at national poverty line (% of population) in
2010, according to the World Bank, available at http://data.worldbank.org/country/bangladesh.
158
prospects, among others, would better connect the country with the two emerging
economic powers, China and India, both of which would benefit from using
Bangladesh’s ports and infrastructure.
The country is prone to supply shocks such as flooding and cyclones.96 However, the
regular flooding, along with the country’s large rivers, makes the soil fertile
providing a natural ground for agricultural activities. This perhaps explains why
agriculture is considered the mainstay of the economy. Besides supply shocks
resulting from natural disasters, the country is also exposed to external shocks due to
its high dependence on imports as well as exports and remittances. For instance, in a
report by the UNDP (2007) Bangladesh is identified as one of the high oil price
vulnerable countries. However, one must also bear in mind that governments in
Bangladesh, using subsidy, do not always pass through international oil price
changes to the domestic economy immediately. In recent years, an additional
contributing factor by which the economy has become more likely to experience the
supply shocks is the adoption of a flexible exchange rate regime in 2003.
On the political side, a great part of the relatively modern political history of the
nation can be characterised as subjugation under different colonial rules and a
struggle for attaining political autonomy. After about 200 years of British colonial
rule and being a part of Pakistan for around 25 years, Bangladesh gained
independence in 1971. In recent decades, however, the nation seems to be
experiencing a struggle to put the self-governance into a smooth path and use the
political emancipation to achieve socio-economic development. Still it is interesting
that the detrimental force of political turmoil has not limited the country’s economic
progress. Studies on Bangladesh at different times record that the country has made
considerable economic progress particularly in alleviating poverty (ADB 2009;
Hossain, M & Sen 1992; Khan 1990; Osmani 1990; Rahman, HZ & Hossain 1995;
Sen 2003; World Bank 2012). Not only has the rate of growth risen steadily,
agencies such as the World Bank has given the country high marks for poverty
reduction (Khan 2007, p. 1). There seems to be a resilience developed by the nation
96
The average loss of rice production per annum due to normal flooding is roughly 4 per cent of total
rice production; it is higher during the years of severe floods (Paul and Rashid 1993 cited in Hayat
and Kalirajan 2009, p. 6).
159
amidst the political setbacks and natural disasters, helping the country moving
forward from its reputation of being ‘an international basket case’. This is echoed by
Shand (1996, p. ix) who states that the country’s “belief in its own capacity to do
better is firm” and it has made undeniable social and economic progress since its
independence.97 Nevertheless, Bangladesh still has large development deficits. It is a
least developed country with low level of food security and high exposure to external
shocks and climate risks. Infrastructure shortage is a critical obstacle to its growth.
The above discussion sets the background for the importance of policies to unlock
Bangladesh’s geopolitical and demographic potentials. Broad-based policies
targeting economic growth and developmental issues would help the country
overcome its key problems such as poverty, food security, and climate change
mitigation and adaptation. A recent report by the World Bank (2012, p. 1) comments
that “[y]et after 40 years of independence, Bangladesh remains a low income country
with…its economic growth potential under-exploited [emphasis added].” The report
also concludes that Bangladesh requires 8 per cent growth to reach the middle
income country threshold (ibid. p. 4). This appears to be a necessary, if not sufficient,
condition in the face of poverty still at 31.5 per cent with 50 million people still
impoverished.98 Failure to reach a higher growth path thereby generating more
income and reducing poverty may have dire consequences, for instance embracing
political extremism leading to conditions of a failed state.99
Despite the fact that Bangladesh needs policies with broader development
perspective, a greater emphasis on attaining higher economic growth, the IMF urges
the country to pursue much more narrowly-based macroeconomic policies mainly to
97
A number of events can be noted to record the initial plight of the country – the devastating 9month war in 1971 and the cyclone a year before, the difficulty in dealing with international politics at
the time of the Cold War, and the famine in 1974 which was aggravated due to food aid stopped by
the United States primarily in retaliation to the accord made by Bangladesh with Cuba. Several papers
state that the War of Independence in 1971 and its aftermath have dealt a severe blow to the economic
structure of Bangladesh (Islam 1974, p. 3, cited in Alauddin and Hasan 1996, p. xiii). In addition, after
the war as Robinson (1978, p. 370) states “[t]he new government had come to power with…no clearly
defined economic policies, beyond general aspiration towards socialism”. Despite the adversities,
Bangladesh managed to advance to a near self-sufficiency in food production by the end of 1990s (see
Talukder 2005, p. 38).
98
See World Bank (2012).
99
Rashid (2008, p. 1) states that although the State Department of the United States praised
Bangladesh as a ‘moderate Muslim democracy’, if the projected poverty and population growth
continues, the country will be a fertile ground for extremism.
160
control inflation. The idea rests on the belief that instead of paying attention to
multiple tasks to manage macroeconomic conditions, it is better to narrow down the
focus and put emphasis on maintaining price stability to achieve sustained economic
growth. This is evident from the conditions of a recent IMF loan, equivalent to US $
1 billion. Table 6.2 reveals that the key message of the conditions is to employ
contractionary monetary and fiscal policies.100 In line with the conditions, the central
bank increased the policy rates four times in 2011 and in early 2012 it increased the
repo rate from 7.25 per cent to 7.50 per cent and raised the reverse repo rate to 5.75
per cent from 5.25 per cent.101 Along with the rising interest rate, the other conditions
such as removal of interest rate ceiling and higher energy prices (see conditions 6
and 7 in Table 6.2) are expected to raise operational costs of business. This is
contradictory to the goal of achieving higher growth by encouraging investment. The
reason is that it may conflict with the need for credit in a low growth economy such
as Bangladesh.102 In fact the President of the Federation of Bangladesh Chambers of
Commerce and Industry (FBCCI) points out that the higher interest rate is one of the
key impediments for the domestic entrepreneurs to undertake the much needed
investment to achieve the 8 per cent GDP growth.103
Table 6.2: Key Conditions of IMF’s US $ 1 billion Loan to Bangladesh, 2010
1.
Pursuing a contractionary monetary policy in order to check inflationary pressure.
2.
Further liberalization of tariff level
3.
More liberal exchange regime by moving into floating exchange rate regime.
4.
Privatization of the loss making state owned enterprises (SOE’s) in order to create more
efficiency and more competencies.
5.
Placing new VAT and income tax in order to achieve revenue targets.
6.
Phasing out bank lending rate ceilings (for bringing in greater flexibility in the lending
100
In fact the set of conditions imposed by the IMF can be aptly summarised by “the triple
commandments” as coined by Rodrik (2004, p. 1) which are “stabilise, liberalise, and privatise.” The
government is asked to achieve macroeconomic “stability” by reducing inflation and fiscal deficits
(see conditions 1 and 8 in Table 6.2), “liberalise” trade by relaxing trade barriers (condition 2) and
entering into flexible exchange rate regime (condition 3), and “privatise” allowing greater ownership
of private sector on resources to gain efficiency (condition 4).
101
Source: The Daily Star, BB raises policy rates, 6 January 2012. The repo rate, equivalent to bank
rate in the United States, is an interest rate at which the commercial banks borrow money from the
central bank. The reverse repo rate is the return commercial banks earn on excess funds kept with the
central bank.
102
This is also the reason why setting the main aim of monetary policy to controlling inflation only is
imprudent.
103
Source: The Daily Star, 23 November 2012.
161
regime).
7.
Raising CNG and furnace oil prices.
8.
Introducing a debt management strategy to reduce budget deficit.
Source: Adapted from Unnayan Onneshan (2011, p. 3).104
It is also important to point out internal inconsistencies of the IMF’s conditions. One
major contributory factor for higher inflation is the removal of subsidies and the
upward adjustment of administrative prices, designed to reduce government’s budget
deficits and debt. Tighter monetary policy certainly cannot lower inflation coming
from this source. It reduces inflation by slowing down overall economic activities as
evident from the concerns expressed by the President of the FBCCI. The policy
becomes self-defeating as slower economic activities reduce government’s revenue
and hence puts more pressure on the government budget.
In sum, the importance of a higher and sustained growth requirement for Bangladesh
is recognised by the studies carried out both inside and outside the IMF and the
World Bank. Still policy prescriptions suggested by the IMF in practice appears to be
heavily tilted towards reining in inflation at a low single digit level in the belief that
it will spur investment and growth.105 The fear that inflation might accelerate drives
the government to pursue constractionary monetary policy even at the cost of hurting
growth. Not only is this self-defeating, there is no conclusive evidence that growth in
money supply alone causes inflation in Bangladesh. For instance, in an earlier study,
Ahmed (1984) concludes that the monetarist hypothesis that inflation is caused by an
excessive growth in money supply is “irrelevant for explaining Bangladesh’s
inflation.” The study also shows that the demand management policies would reduce
inflation but at the cost of a slowdown in income growth. He argues that supply
management policies help inflation to go down without adversely affecting output
growth. On the other hand, in a recent study, Hossain (2010) argues that supply
shocks are unlikely to be a “regular source of inflation” (p. 572) and “broad money
growth causes inflation in the short run” (p. 574). In contrast, CPD (2011, p. 24)
points out that growth in money supply and inflation moved along the same direction
104
The study by Unnayan Onneshan (translates ‘in search of development’, a multidisciplinary
research centre in Bangladesh), funded by the Christian Aid, attempt to evaluate IMF’s loan and its
implications on Bangladesh economy.
105
This is also evident from the discussion based on the IMF Article IV Consultation report on
Bangladesh in Chapter 3.
162
over the major part of the period between 2001 and 2010, and that no causal
relationship could be established between the two in the short run.
Given this setup, the next section looks at the time series data on growth and
inflation to reveal some stylised facts on their relationship.
6.3 Trends in Growth and Inflation in Bangladesh
The data on real GDP growth and inflation rates in Bangladesh for the period 19712009 provide some interesting observations into the relationship between the two
indicators. Figure 6.1 depicts growth and inflation rates between 1971 and 2009
while Table 6.3 provides decadal summary statistics. It shows that growth has never
reached a double digit figure during this period (Figure 6.1). Each decade has
experienced about one percentage point increase in growth since the 1980s (Table
6.3). Average inflation on the other hand shows a declining trend according to the
statistics. Another important fact to note, from Table 6.3, is that volatility in growth,
measured in terms of coefficient of variation (CV), is much less compared to its
inflation counterpart since the 1990s (Table 6.3). In short, the average growth rate
has steadily picked up pace and become less volatile after the transition to
democracy, with an associated declining trend but greater variability in inflation.106
This, however, does not provide us with the information relating to causality between
the two variables.
106
After about a 9-year military rule Bangladesh experienced a transition to democracy in the late
1990 (see Mahmud 2008, p. 93).
163
Figure 6.1: Real GDP Growth and CPI Inflation in Bangladesh, 1971 - 2009
60
50
40
30
20
10
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
-10
1970
0
-20
Real GDP Growth
CPI Inflation
Source: World Bank, World Development Indicators; and IMF, World Economic Outlook.
Table 6.3: Decadal Averages of Growth and Inflation in Bangladesh, 1971 – 2009
Real GDP growth rates
Inflation rates (CPI)
Average
SD
CV
Average
SD
CV
1970s
0.80
7.67
9.53
22.09
20.99
0.95
1980s
3.15
1.22
0.38
11.26
2.24
0.19
1990s
4.68
0.69
0.15
6.39
2.92
0.46
2000s
5.64
0.63
0.11
5.68
2.45
0.43
Source: Author’s calculations based on data available from World Bank, World Development
Indicators and IMF, World Economic Outlook.
Note: SD and CV stand for standard deviation and coefficient of variation (SD/Average) respectively.
The correlation statistics between growth and inflation rates also shows some
interesting stylised facts. For the entire period between 1971 and 2009, the
correlation (-0.27) shows a moderate negative relationship. However, if we divide
the period into halves, 1971-1989 and 1990-2009, what we notice is a negative
relationship (-0.13) for the former period but a positive relationship for the latter
(0.21). This perhaps reflects the changing pattern of growth-inflation dynamics over
time as the economy undergoes important structural changes.
164
The above descriptive analysis provides mixed experience about the growth-inflation
nexus over the sample period, 1971-2009. In order to employ policy to sustain
growth and manage inflation, an understanding of the sources of inflation is also
important. Before using policy instruments it is essential to identify whether inflation
is predominantly demand-driven or a supply-side phenomenon. This is because,
contractionary monetary policy attempting to stabilise inflation in the event of a
supply shock may cause further decline and greater variability in growth. 107 It is
particularly relevant for Bangladesh which is susceptible to supply shocks, discussed
in the previous section.
It is clear from Figure 6.1 that the incidence of inflation in the early period of 1970s
was discrete and it reached its highest in the 40-year history of Bangladesh.108 This is
no surprise as inflation typically shoots up after a crisis such as war (see Blanchard &
Sheen 2009, Chapter 24). Not only was it inevitable due to the war, the two
international oil price shocks of the 1970s also triggered the high bouts of inflation in
the economy. Therefore, studies (for example, Bose 1973; Rahim 1973; Siddique
1975) which claim that a prime cause of the inflation during this period is excess
monetary expansion to finance budget deficits in a war-ravaged economy miss the
point and fail to see the causes that triggered inflation in the first place. Mahmud and
Osmani (1980) identify remittances, a demand-side cause of inflation. They argue
that remittances are mostly used for consumption and unproductive investment such
as real estate thus exacerbating the already explosive inflationary situation. The
process of inflation in the economy is also examined by Taslim (1982) in the light of
structuralist-monetarist debate and he concludes that both structural bottlenecks and
monetary aggregates are relevant for the inflationary process in Bangladesh.
The above studies attempt to analyse inflationary situation during an unusual period
of the country – the 1970s which was dogged by a series of major international and
domestic problems as discussed earlier. Besides, these studies have some empirical
shortcomings in terms of incorporating the advances in time series analysis such as
107
As discussed in Chapter 3, the research by Selassie et al. (2006) carried out at the IMF also
recognise that procyclical monetary policy, when inflation is cause by a supply shock, would have
unintended consequence on growth in the developing countries.
108
As Chowdhury and Hossain (1996, p. 11) note, the annual inflation rate during 1972-1975 was the
highest since the 1943 Bengal Famine.
165
addressing the non-stationarity issue resulting in spurious relationship between
variables. Therefore, a look at recent studies is more appropriate. Mortaza (2006)
supports the IMF view and claims that money supply – a demand-driven cause of
inflation – and exchange rate have significant positive impact on inflation during the
fiscal period 1990-2006. His finding of negative relationship between deposit interest
rate and inflation also lends support to fighting inflation by raising interest rates.
Contrary to this, Rahman et al. (2008) find that external shocks such as the upsurge
in international commodity prices and structural issues such as supply-side
constraints and distortions in domestic supply chain are mainly responsible for
inflation in 2007-2008. Another study by Osmani (2007), around this time, argues
that demand-driven factors are not important in explaining inflation in recent years.
The author points out that the extra demand resulting from higher income and growth
should not exert pressure on inflation since higher national income also entails higher
national output.109 Therefore, additional demand should be matched by additional
output. His argument is also based on the fact that rising income leads to falling
relative price of food vis-à-vis luxury or manufactured products.110
The above discussion on growth-inflation relationship in Bangladesh based on
descriptive statistics and findings from existing literature does not provide a
convincing argument in favour of the IMF view. Fighting inflation without paying
attention to its causes and keeping it at a low single digit level at all times may not
ensure high long term sustained growth. The discussion paves the way for an
empirical exercise which is carried out in the following two sections to further
substantiate this view.
6.4 A Time Series Analysis of the Growth-Inflation Relationship
This section attempts to look at whether there exists a long run equilibrium
relationship between output and price level and if so, what kind of short run
109
In accordance with National Income Accounting Identity.
Income elasticity of demand for food, according to Engel’s Law, is said to be inelastic and
therefore as income rises, even if expenditure on food rises, the proportion of income spent on food
decreases. This is expected to lower the relative price of food. However, the behaviour of the relative
price of food as incomes and hence the demand for food increase will also depend on how fast the
supply of food grows. Structuralists have long argued that if the agricultural sector lags behind other
sectors in the process of economic growth, it may lead to an increase in the relative price of food,
thereby triggering an inflationary spiral.
110
166
dynamics exists between growth and inflation. The annual data for Bangladesh is
gathered from the World Development Indicators of the World Bank; and
International Financial Statistics and World Economic Outlook of the IMF for
econometric analysis.111 Considering the turbulent phase of the early half of the
1970s in Bangladesh, we feel a sample period between 1977 and 2009 is more
appropriate to carry out this empirical investigation.
Our first step, as is standard in any time series analysis, is to test for non-stationarity
in the variables to avoid any spurious relationship. Empirical studies on unit root
provide a whole battery of tests to identify nonstationarity. We rely on Augmented
Dickey Fuller (ADF) test (Dickey & Fuller 1979, 1981) and Phillips Perron (PP)
(Phillips & Perron 1988) test, most widely used in the literature. PP test performs
better in the event of low frequency data as suggested by Choi and Chung (1995).
The annual data used in this chapter fit into that category. Because PP test is
supposedly superior to ADF test, if differences arise in terms of the results from the
two unit root tests, we draw conclusion based on the PP test.
Table 6.4 presents the unit root test results on real GDP (output level), consumer
price index (price level), real GDP growth, and inflation (first difference of CPI).
The findings show expected order of integration of the variables. Both output and
price levels possess unit root and integrated of order one, in other words, they are
nonstationary. On the other hand, their first differences – growth and inflation
respectively – are found to be stationary. This is consistent with the idea that in a
finite sample first differenced variables are expected to be stationary (since mean
reversion process should take place in a small-finite sample).
111
The empirical work of this chapter started in 2010 when the latest information available was up to
2009.
167
Table 6.4: Unit Root tests with Real GDP, CPI, Growth, and Inflation, 1977–2009
Variables
Augmented Dickey Fuller (ADF)
Phillip Perron (PP) Tests
Process
Tests
Statistics
p-value
Unit root
Statistics
p-value
Unit root
Intercept
4.77 (8)
1.00
Yes
6.85
1.00
Yes
I (1)
Intercept
1.61 (8)
1.00
Yes
1.22
0.99
Yes
I (1)
Intercept
-3.19 (8)
0.02
No
-3.20
0.02
No
I (0)
Intercept
-1.66 (8)
0.74
Yes
-2.65
0.25
Yes
I (1)
Intercept
-1.12 (8)
0.69
Yes
-4.54
0.00
No
I (0)
Intercept
-4.57 (8)
0.00
No
-6.71
0.00
No
I (0)
Intercept
-2.80 (8)
0.06
Yes
-5.04
0.00
No
I (0)
Intercept
-2.25 (8)
0.44
Yes
-5.86
0.00
No
I (0)
Real GDP
with trend
CPI
with trend
Real GDP
growth
with trend
CPI
inflation
with trend
Notes:
1.
Both real GDP and CPI are in natural logarithm form.
2.
The null hypothesis of ADF and PP tests is that the series has a unit root (in other words nonstationary).
3.
Figures within parentheses in the ADF statistics indicate the number of lags taken to perform
the test.
4.
PP test is carried out by employing Bartlett Kernel estimation method with Newey-West
Bandwith selector.
5.
I(1), integrated of order one, and I(0), integrated of order zero, refer to non-stationary and
stationary variables respectively.
6.
Tests are carried out using EViews version 7.
Since both real GDP and price level possess unit roots and they are integrated of the
same order, I(0), it provides an opportunity to test for cointegration to find out if
there is a long run equilibrium relationship between real GDP and price level. We
employ Johansen Maximum Likelihood Cointegration Test (Johansen 1991) the most
168
widely used technique in recent literature in this regard.112 The bivariate
cointegration test also involves the use of a dummy, DUM92 as an exogenous
variable. The purpose of incorporating a dummy variable is to take into account the
structural break in the growth rate, since the economy’s transition to democracy in
the early 1990s.113 As discussed earlier, this transition is seen to have a significant
impact on the economy. The election took place in early 1991 and because policies
tend to affect the economy with lags we expect that the structural break takes place in
1992. Chow test (Chow 1960) for known dates confirms existence of a structural
break in real GDP growth in the year 1992 (see Table 6.5).114 In other words,
diagnostic test supports the structural break date based on historical evidence. So a
shift dummy, DUM92, with value ‘0’ before 1992 and ‘1’ since 1992, is constructed
and used as an exogenous variable in the cointegration analysis.
Table 6.5: Structural Breakpoint Test for Real GDP Growth in 1992
Variable
Test
F-statistics
P-value
Real GDP growth
Chow Test for known dates
8.347
0.001
Notes: The null hypothesis – no break in the specified breakpoint – is rejected at 5 per cent
significance level according to the p-value. Test is carried out using EViews version 7.
The cointegration test results are reported in Table 6.6. Based on Trace and
maximum eigenvalue tests, cointegration results indicate the presence of no
cointegrating vector at 5 per cent level of significance for the sample period 19772009. In both cases, the value of test statistics is less than the critical value at 5 per
cent significance level and therefore we cannot reject the null hypothesis of no
cointegrating vector. It means that we do not find a stable long run equilibrium
relationship between real GDP and price level in Bangladesh, once the structural
change in the economy is taken care of. It contradicts with the findings of Ahmed
and Mortaza (2005) which did not take the structural break issue into account. The
finding casts doubt about the notion advocated by the IMF that stable price will
112
Johansen approach performs better than Engle-Granger two-step approach (Engle & Granger 1987)
in identifying cointegration. For a detail discussion on the comparative advantage of the Johansen
approach see Asteriou and Hall (2007, Chapter 17).
113
Inference on tests of cointegration may be affected by structural change (Maddala & Kim 2000, p.
410). Out analysis is unique in this sense since most of the studies in the context of Bangladesh do not
take into account the issue of structural break.
114
Chow test is for stationary variables and a single break (Maddala & Kim 2000, p. 390).
169
ensure higher output and growth in the long run as they do not seem to move
together over a long period of time. The test of cointegration also helps us determine
the modelling issue whether to use a restricted model such as error correction model
(when variables are cointegrated) or an unrestricted model (in the absence of
cointegration) in the subsequent analyses.
Table 6.6: Cointegration Test Results
Null
Alternative
hypothesis
hypothesis
Test statistics
P-value
5 per cent
Conclusion
critical value
Trace test
r=0
r=1
18.92
0.28
25.87
No
r≤1
r=2
6.82
0.36
12.51
cointegrating
equation
Maximum eigenvalue test
r=0
r=1
12.09
0.40
19.38
No
r≤1
r=2
6.82
0.36
12.51
cointegrating
equation
Notes: Results reported above are based on the assumptions of a constant and a linear trend in the data
with lag length 3. According to AIC and SIC a lag length of 1 is sufficient. A dummy variable,
DUM92 explained in the text is used as an exogenous variable. MacKinnon-Haug-Michelis (1999) pvalues are used.
In short, the analysis of this section does not provide strong evidence of a long run
relationship between output and price level in Bangladesh. The apparent lack of a
long-run relationship between inflation and growth may be due to incorrect
modelling. That is, the actual relationship between the two variables may be nonlinear, while the cointegration analysis uses a linear equation. Therefore, the next
section examines the possibility of existence of a non-linear relationship and if it
does, at what level inflation might turn harmful for economic growth, assuming a
nonlinear relationship between the two.
6.5 Identifying the Threshold Level of Inflation in Bangladesh
In this section we try to estimate the threshold level of inflation using a nonlinear
model. It is reasonable to assume a nonlinear relationship between growth and
170
inflation since existing literature (see Chapter 4) and the descriptive statistics
(particularly correlation) on Bangladesh data provide support for this. Inflation may
have a positive or a negative association with growth. The previous chapter using a
panel study also essentially uses this nonlinear framework to estimate the threshold
levels. So, we model economic growth as a function of inflation in a quadratic
specification similar to Chowdhury and Siregar (2004). However, the bivariate
relationship used in their estimation poses serious limitations. This is because
growth-inflation relationship is conditioned upon other variables. So taking this into
account, we consider some other covariates, pertinent to the Bangladesh economy, in
determining the impact of inflation on growth. The specification of the model is
given below:
yt = α + β1 π + β2 π2 + ∑
i
Zt + εt
(6.1)
where, yt is economic growth measured by the first difference of natural logarithm of
real GDP (measured at constant 2000 US dollar); π is the inflation rate measured in
terms of first difference of natural logarithm of the consumer price index (CPI); Zt
includes the control variables; α is a constant term; and εt is the classical error term.
The squared term of inflation captures the nonlinearity into this relationship and
since we assume it to be inverted U shaped we expect β1 > 0 and β2 <0. Applying the
first order condition, the turning point is measured as -β1/2 β2.
To avoid any spurious relationship, the control variables (Z) include variables in their
first differenced form. Our unit root test results in the previous section already prove
that both growth and inflation are stationary variables. Z considers a number
variables, seen as appropriate to influence the growth-inflation relationship and some
of which are used in the panel study (Chapter 5) as well. The variables in their
growth form are real household consumption per capita (HCONPC), broad money
supply (M2), government consumption expenditure as a percentage of GDP
(GOVCON), trade openness (OPEN) which the summation of export and import as a
percentage of GDP; agriculture value added at constant 2000 US dollar (AGR), oil
price index (OILPR) (UK Dated Brent Crude Oil Index, 2005=100), commodity
price index (COMPR) (World Bank Non-Energy Commodities for Lower Middle
Income Countries Index, 2005=100), remittances as a percentage of GDP
171
(REMGDP)115, and a dummy variable DUM92 to take into account the structural
break in the dependent variable as discussed above. In addition a lagged dependent
variable is also considered as a regressor in the growth equation to allow for any long
term impacts.
We employ OLS technique to regress growth on inflation, conditioned upon other
covariates. Table 6.7 records the results of the OLS estimations using equation 6.1.
The estimation is carried out in two steps, following a general-to-specific approach.
First, growth is regressed on all the variables discussed above, findings of which are
presented in Model 1 in Table 6.7. Next, we identify the conditioned variables which
are significant at least at 10 per cent level in Model 1. We again regress growth on
inflation and these conditioned variables in Model 2. In other words, the insignificant
conditioned variables are omitted to create a more parsimonious model to determine
the impact of inflation on growth.
Table 6.7: Impact of Inflation on Growth, Conditioned upon Other Covariates, 19772009
Dependent variable is real GDP growth
Model 1
Model 2
Variable
Coefficient
SE
P-value
Coefficient
SE
P-value
VIF
Inflation
0.272
0.099
0.012
0.295
0.073
0.001
12.641
Inflation
-0.772
0.648
0.248
-0.934
0.482
0.064
14.269
Turning point
17.628
Growth (-1)
0.048
0.077
0.541
∆ ln HCONPC
0.113
0.039
0.009
0.129
0.032
0.000
1.655
∆ ln M2
0.017
0.013
0.197
∆ ln GOVCON
0.024
0.011
0.051
0.022
0.010
0.035
1.219
∆ ln OPEN
-0.001
0.010
0.934
∆ ln AGR
0.256
0.042
0.000
0.265
0.038
0.000
1.545
∆ ln OILPR
0.007
0.003
0.053
0.006
0.003
0.043
1.060
∆ ln COMPR
-0.005
0.008
0.557
∆ ln REMGDP
-0.007
0.006
0.272
DUM92
0.016
0.002
0.000
0.015
0.002
0.000
1.608
Constant
0.009
0.005
0.105
0.012
0.003
0.000
2
15.775
115
The remittance-variable, not considered in the growth regressions of Chapter 5, is particularly
important in the context of Bangladesh. Bangladesh is one of the leading remittance recipient
countries, with remittances equivalent to 12 per cent of the GDP (Chowdhury, MB 2011, p. 2600).
172
Sample period
1978-2009
1977-2009
No of observation
32
33
Estimation method
Ordinary Least Squares
Ordinary Least Squares
R-squared
0.943
0.928
Adjusted R-squared
0.907
0.907
S.E. of regression
0.004
0.004
Log likelihood
138.253
134.636
F-statistic
26.088
44.368
Prob(F-statistic)
0.000
0.000
Akaike criterion
-7.828
-7.915
Schwarz criterion
-7.233
-7.548
DW statistics
1.892
2.276
JB Normality test
0.581
0.503
p-value
BG Serial correlation
(1-4) LM test
0.747
0.777
4.927
7.322
p-value
BPG heteroscedasticity
test
0.294
0.119
6.695
9.116
p-value
0.877
0.244
ARCH (1-4) test
2.174
5.063
p-value
0.703
0.28
Stable
Stable
Diagnostic tests
Stability test
CUSUM Test
CUSUMSQ Test
Stable
Source: Author’s estimations using EViews version 7.
Stable
Notes:
1.
Estimations are performed using the model specified in equation 6.1.
2.
CPI inflation is used as a measure of inflation.
3.
Turning points of inflation are calculated by examining the partial derivatives of real GDP
growth with respect to inflation – the coefficient of the linear term of inflation divided by 2
times the coefficient of the squared term of inflation.
4.
Growth (-1) refers to real GDP growth lagged in one period.
5.
∆ and ln indicate first difference operator and natural logarithm of the variables respectively.
6.
The acronyms of the variables are explained in the text.
7.
SE stands for standard error of the coefficient and the respective p-value indicates the level
of significance. For instance a p-value less than 0.05 indicates that the coefficient is
significant at 5 per cent significance level.
173
8.
Null hypotheses of JB normality test, BG serial correlation LM test, and BPG
heteroscedasticity test are that the residuals are normally distributed, no residual
autocorrelation, and the residuals are homoscedastic respectively.
9.
Null hypothesis of ARCH (autoregressive conditional heteroscedasticity) test states no
ARCH effect in the residuals.
In Model 1, although the linear term of inflation is significant at 5 per cent
significance level, the squared term is not. Both terms show the expected signs,
positive and negative, respectively, confirming the assumption of an inverted U
shaped relationship. The turning point in this case is around 17 per cent. Amongst the
conditioned variables, growth rates in HCONPC, GOVCON, AGR, OILPR, and
dummy variable DUM92 are found to be significant at 10 per cent significance level.
On the other hand, growth lagged in one period and growth rates in M2, OPEN,
COMPR, and REMGDP are found to be insignificant.116 All the significant
conditioned variables (growth rates in HCONPC, GOVCON, AGR, and OILPR)
have a positive impact on growth. In a developing country such as Bangladesh,
household and government consumptions are likely to have a strong influence on
aggregate demand, thereby enhancing economic growth. The positive effect of
agriculture on growth is also no surprise since we know the sector is still the
mainstay of the Bangladesh economy. What is perhaps not expected is the positive
sign of the coefficient of growth in oil price index. Rise in Oil price is supposed to
have a negative shock on growth. However, we know that governments in
Bangladesh, through the use of subsidy do not always pass on the changes in oil
price into the domestic economy immediately. Therefore, economic growth may not
be affected by changes in oil prices. Moreover, because natural gas is in many
respects a substitute for oil, increases in oil prices lead to increases in the demand for
natural gas which could be expected to boost economic activity in Bangladesh.
We pay greater attention to the findings from Model 2 which is more parsimonious.
First, both linear and squared terms of inflation are significant at 10 per cent and
116
The coefficient of remittances is found to be negative and insignificant. It is at odds with the idea
that the flow of remittances is supposed to influence the growth of the economy positively. Perhaps
we should bear in mind that the flow of remittance in Bangladesh takes place irrespective of financial
development or higher investment opportunities of the country. Families of migrant workers, 90-95
per cent, are mostly poor living in villages (see Chowdhury, MB 2011, p. 2605). They are highly
dependent on the remittance income which may not have productive use and therefore having a
positive impact on growth.
174
have signs consistent with the assumption. The turning point calculated from the
coefficients is at 15 per cent, approximately. This result matches our expectation of a
double digit figure for the threshold level of inflation in Bangladesh. The figure is
higher than the single digit level of 6 per cent suggested by Ahmed and Mortaza
(2005). In a developing country such as Bangladesh, low productivity and structural
bottlenecks for example poor infrastructure and energy shortage are key impediments
for growth. Our finding suggests that inflation up to 15 per cent should not impose a
threat to economic growth. This is consistent with all the major studies done in the
context of developing countries – the threshold broadly remaining between 11 and 18
per cent.
The coefficients of other conditioned variables in Model 2, growth rates in
HCONPC, GOVCON, AGR, OILPR, and DUM92 provide a similar result to that of
Model 1. It is interesting to note that government consumption is not found to have a
detrimental effect on growth in any of the models. Again this contradicts the
conventional idea advocated by the IMF that government’s intervention essentially
creates more harm than good to the economy. It is also important to note that higher
household consumption, through reducing poverty and raising productivity and
aggregate demand, has a growth enhancing effect. The importance of agriculture, the
production side of the economy, is also evident from the findings. The overall
evidence suggests that broader issues such as higher domestic consumption leading
to poverty reduction, greater role of government in boosting aggregate demand, and
rising agricultural production to attain self-sufficiency in food production lead to a
higher growth rate. These issues, therefore, are more important for economic growth
than mere control of money supply growth in keeping inflation at a low single digit
level.
To check the reliability of the above estimates a number of diagnostic tests are
performed. Both models pass comfortably in terms of all diagnostic tests. The
adjusted R2 is high in both cases suggesting that the models have a good fit.
However, Model 2 has higher F statistics and has more significant explanatory
variables than Model 1. Values from information criteria, such as Akaike
Information Criterion (Akaike 1974) and Schwarz criterion (Schwarz 1978) reported
here, also indicate a preference towards Model 2 since it has lower values of all those
175
statistics (for model selection based on information criteria see Asteriou & Hall
2007, p. 66). The Durbin-Watson (DW) test statistic for Model 2 is close to the value
2 suggesting no residual autocorrelation in the regression model. We should be
cautious about interpreting the DW test statistic for Model 1 since this test statistic
should not be used when a lagged dependent variable is used as a regressor in the
model (see Vogelvang 2005, Chapter 6, p. 125).
In terms of the standard residual tests to determine normality, serial correlation, and
heteroscedasticity, both models perform well. P-values for these tests are greater than
0.05 and therefore we cannot reject the respective null hypotheses at 5 per cent
significance level (see notes 8 and 9 in Table 6.7). This means that the residuals are
normally distributed and do not suffer from problems such as autocorrelation and
heteroscedasticity. We also check the stability of the estimates over time using the
CUSUM and the CUSUM squares tests proposed by Brown Durbin and Evans
(1975). No significant break is observed in both models. The test statistics derived
from the regressions remain within the 5 per cent confidence bands. This indicates
that the estimates from the corresponding regressions are stable over time.117 Finally,
since the estimates of Model 2 are more important we check for the multicollinearity
problem in this case (reported in the last column of Table 6.7). We use the formal
procedure to detect multicollinearity variance inflation factors (VIFs) of the
coefficients. A rule of thumb is that a VIF of 10 and greater is a problem (see for
instance Verbeek 2012, Chapter 2, p. 45). The VIFs of all explanatory variables,
except inflation terms, in Model 2 are well below 10 suggesting that the estimates to
do not suffer from multicollinearity problem. We ignore the VIF values for inflation
terms as it is obvious that linear dependency would exist among them.118
Some of the post-estimation facts from Model 2 are illustrated in the following
figures. Figure 6.2 shows the residuals from the regressions while Figure 6.3 depicts
a scatter plot between residual growth and inflation controlled for the other
117
Since we are more interested in the results from Model 2 only diagrams of the parameter stability
tests for this model are shown in Figure 6.4 and 6.5.
118
Our variable transformation techniques also help ensure the remedies for problems such
heteroscadasticity and multicollinearity. These are standard procedures employed in empirical work.
For instance, in the case of time series data, log-transformation and taking first differences often take
care of heteroscadasticity and multicollinearity problems (see Maddala & Lahiri 2009, Chapter 5, p.
224 and Chapter 7, p. 300, respectively).
176
covariates. Observation from the scatter plot does not provide a clear evidence of a
negative relationship between growth and inflation. The parameter stability tests in
the case of Model 2 are shown in Figures 6.4 and 6.5, interpretations of which are
discussed above.
Figure 6.2: Growth Rate, Actual and Fitted, 1977 – 2009
.08
.06
.04
.008
.02
.004
.00
.000
-.004
-.008
78
80
82
84
86
88
90
Residual
92
94
96
Actual
98
00
02
04
06
08
Fitted
Note: The graph is drawn based on the results of Model 2 presented in Table 6.7.
177
Figure 6.3: Scatter Plot between Unexplained Growth and Inflation, 1977 – 2009
.008
.006
Residual of growth
.004
.002
.000
-.002
-.004
-.006
-.008
.00
.04
.08
.12
.16
.20
Inflation conditioned upon other covariates
Note: The scatter plot is drawn based on the results of Model 2 presented in Table 6.7.
Figure 6.4: Parameter Stability Test using CUSUM Test
12
8
4
0
-4
-8
-12
1994
1996
1998
2000
CUSUM
2002
2004
2006
2008
5% Significance
Note: Parameter stability test for Model 2 detailed results of which are presented in Table 6.7.
178
Figure 6.5: Parameter Stability Test using CUSUMSQ Test
1.6
1.2
0.8
0.4
0.0
-0.4
1994
1996
1998
2000
CUSUM of Squares
2002
2004
2006
2008
5% Significance
Note: Parameter stability test for Model 2, results of which are presented in Table 6.7.
In empirical time series analysis, it is customary to see the response of one variable
to an impulse (exogenous shock or innovation) in another variable in a system. Our
final task is to carry out an impulse response analysis between growth and inflation
in a vector autoregressive (VAR) framework. In this regard, Lutkepohl (2005, p. 62)
points out a major limitation that arises because of the “potential incompleteness” in
the system. This incompleteness may arise as a result of omitting important variables
from the system thus leading to major distortions in the responses. Since we realise
that the growth-inflation relationship is conditioned upon other important variables,
we use the control variables of Model 2 to avoid this problem. Table 6.6 illustrates
these impulse responses.
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Figure 6.6: Impulse Response Analysis for Growth and Inflation
Response to Cholesky One S.D. Innovations ± 2 S.E.
Response of growth to growth
Response of growth to inflation
.0100
.0100
.0075
.0075
.0050
.0050
.0025
.0025
.0000
.0000
-.0025
-.0025
-.0050
-.0050
1
2
3
4
5
6
7
8
9
10
1
2
Response of inflation to growth
3
4
5
6
7
8
9
10
9
10
Response of inflation to inflation
.04
.04
.03
.03
.02
.02
.01
.01
.00
.00
-.01
-.01
-.02
-.02
-.03
-.03
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
Notes:
1.
Impulse response between growth and inflation conditioned upon variables used in Model 2
in Table 6.7.
2.
A VAR lag length of 3 based on information criteria is used.
3.
The graphs are generated using EViews version 7.
In the four graphs of Figure 6.6 we are more interested to see the cross-responses
than own-responses. The upper right graph shows the response of growth for a shock
in inflation. The response of growth to an increase in inflation is insignificant as the
confidence band touches zero. The response is positive but very weak from year 1 to
about year 2. After that inflation seems to have a negative effect on growth which
starts to fade away after year 5. On the other hand, in the lower left graph, an
increase in growth positively affects inflation after one year but this effect becomes
insignificant after about 6 months as the confidence band touches zero.119
119
This also tells us that current growth does not seem to affect current inflation causing a possible
reverse causality problem in estimating equation 6.1. According to the responses, growth only starts to
affect inflation after 1 year and the effect continues for about 6 months.
180
These findings from the multiplier effects clearly find support from existing theories
explaining the growth-inflation relationship discussed in the opening chapters. The
initial positive influence of inflation on growth, albeit statistically insignificant and
weak, finds support from the Kalecki-Keynesian schools arguing in line with the
proposition of transferring resources through forced savings and inflation tax. One
can also explain the positive growth effect using Kaldor’s argument of transferring
income to profit earners with higher propensity to save and Tobin’s argument of
higher capital intensity as real return to financial investment declines. The negative
impact of inflation on growth after about 2 years, continued for the next 3 years
approximately, can be supported by the classical-mainstream view. This classical
view, in brief, brings in the idea that inflation retards growth through its distortionary
effects on investment.120 We must note that these dynamic influences of inflation on
growth are interesting – complex and surely not linear – but unfortunately the results
are not statistically significant. On the other hand, the positive effect of growth on
inflation, after 1 year continued to be significant for the next 6 months, shows that
inflation is an inevitable companion to growth. Again this is explained by the
Structuralist School which says that inflationary pressure is caused by the process of
growth due to various structural rigidities within the economy. Together the findings
clearly reject the views expressed by Hayat and Kalirajan (2009) who advocate that
growth-inflation relationship is unidirectional and linear and decline in inflation from
any level is beneficial for growth.
To summarise the findings of this section, we can point out two important facts.
First, there is no evidence that inflation beyond 5 per cent level will start to have a
detrimental effect on growth in Bangladesh. Inflation threshold is found at around 15
per cent for the country. Second, in an underdeveloped country such as Bangladesh,
inflation does not seem to be the key factor causing low economic growth. The
dynamic impulse response analysis shows that inflation starts to pick up when the
economic growth is taking place. This inevitable consequence should not alarm the
government immediately. The choice of anti-inflationary measure should be
120
A relatively older study by Mallik and Chowdhury (2001) comprising four south Asian countries
including Bangladesh provides some empirical support to our findings. According to the authors,
moderate inflation is found to be beneficial for growth. However, as discussed in Chapter 2, they did
not provide any estimate of this moderate level of inflation.
181
employed with caution as in doing so a low inflation target may be achieved but at
the cost of hurting growth.121
6.6 Conclusion
The key estimation result presented in this chapter provides strong evidence that the
inflation threshold for Bangladesh is not as low as 5 per cent. Based on annual data
between 1977 and 2009 we find the threshold level is around 15 per cent. This
evidence is consistent with the findings of major cross-country panel studies on
developing countries, discussed in Chapter 2 and Chapter 5, but differs from the two
recent country-specific studies on Bangladesh by Ahmed and Mortaza (2005) and
Hayat and Kalirajan (2009) advocating very low inflation thresholds.
Similar to the findings of panel study in Chapter 5, the threshold estimate of this
chapter in a country specific case also questions the conventional wisdom of keeping
inflation at a low single digit level to attain high economic growth. Bangladesh has
shown promising and steady growth since its transition to democracy in the early
1990s. This has taken place in spite of several bouts of inflation and greater inflation
volatility during this time. This steady growth performance, however, is not enough
in the face of poverty rate still around 31.5 per cent. The country needs at least a
growth rate of 8 per cent for further poverty reduction. Institutions such as the World
Bank have acknowledged it (see World Bank 2012). The World Bank also admits
that Bangladesh’s potentials are underutilised. Yet our discussion in this chapter
shows that the IMF imposes conditions, while sanctioning loans to Bangladesh, with
a view to fighting inflation first. This policy prescription is similar to what we have
seen in Chapter 3 in the content analysis of Article IV Country Consultation Report
by the IMF staff. That report, in the aftermath of the Great Recession, also gives
priority to rein in inflation instead of outlining strategies for economic growth and
rapid poverty reduction. The country has passed a couple of decades with a priority
to keep inflation at a low single digit level, but failed to achieve the required level of
growth. Perhaps growth fails to reach a higher trajectory because of strict anti-
121
As former World Bank economist Surjit Bhalla says “Let’s kill GDP, inflation will fall” (The
Financial Express, 15 October, 2011; available via the internet at
http://www.financialexpress.com/news/Column---Let-s-kill-GDP--inflation-will-fall/860148.
182
inflationary measures such as interest rate hikes. The domestic entrepreneurs feel
strongly that by raising operational costs this acts as a major obstacle to grow at 8 per
cent rate. On the other hand, the acceptance of a moderate inflation rate would have
widened the government’s fiscal and policy space, needed to tackle the country’s
infrastructure bottlenecks.
183
Chapter 7
Conclusion
This thesis provides an extensive study of the growth-inflation relationship in
selected developing countries of Asia. The study questions the conventional wisdom
of macroeconomic policies targeting low inflation in developing countries.
Following several bouts of high inflation together with growth stagnation during the
1970s and 1980s, macroeconomic policies in developing countries have started to
place too much emphasis on attaining price stability by keeping inflation low. The
IMF also strongly advises the developing countries to maintain inflation within 5 per
cent. Because of the conditions attached as part of the loan-agreement, developing
countries often do not have much option but to pursue this low inflation targeting
policy. This policy, as the conventional wisdom suggests, is expected to stop
acceleration in inflation and bring benefits in terms of sustained long term economic
growth. There is a sense of apprehension that inflation accelerates when it goes
beyond 5 per cent, thus leading to a crisis. It is also believed that once inflation
accelerates, it is quite difficult to control it and often becomes too costly in terms of
high unemployment and lost output. Therefore, even at the cost of immediate adverse
effects on growth, the policy of fighting inflation first, keeping it as low as 5 per cent,
is advised. Moreover, the IMF seems to believe that this one policy fits all works the
best. This is reflected in its policy prescription contained in the Article IV
consultation irrespective of country-specific circumstances.
There is little evidence that this perception has changed in the aftermath of global
crisis of 2007-2009. Leading economists, even within the Bretton Woods institutions,
have argued about the limitations of this conventional idea after the crisis. They have
also raised concerns about deteriorating condition of poverty throughout the
developing world despite the policy adherence towards low inflation. In spite of the
need for a change in this policy, suggested by the leading economists, the IMF seems
to continue with its pre-crisis policy prescription. Therefore, keeping a watchful eye
on inflation still receives priority in macroeconomic policy management in
developing economies.
184
A number of studies in recent years have argued against this wisdom of
macroeconomic policies targeting low inflation, both empirically and analytically.
They have revealed that too low an inflation is inimical to growth and how policies
aiming to achieve this can create an inflation trap, ultimately having an adverse
impact on poverty. However, a systematic empirical research on Asian developing
countries, from Asia-Pacific region in particular, is limited. In this thesis, we make
an attempt to fill this gap. This thesis investigates the nature of growth-inflation
relationship in developing countries of Asia, questioning the validity of the widely
held belief that low inflation is beneficial for economic growth. This research
demonstrates that inflation beyond 5 per cent is not necessarily detrimental for
economic growth in our sample of Asian developing countries. Moreover, the
inflation threshold is not fixed at a particular level and it varies according to levels of
economic development. The contribution of the thesis, as such, is twofold. First is to
provide a unique contribution to the literature pertaining to growth-inflation nexus.
Second, the findings of our study have profound implications for macroeconomic
policy making in countries that still follow low inflation targeting policies.
As mentioned above, despite the dominance of low inflation policy, there is much
evidence that the condition of poverty in the developing countries has not improved
significantly over the last few decades. In fact, it has deteriorated in certain cases.
There is also historical evidence that developing countries can grow under relatively
moderate inflationary environment. On the other hand, as mentioned above, very low
inflation can inhibit economic growth in developing countries. Attempts to keep
inflation at low single digit levels (for example, below 5 per cent) may lead to a
stabilisation trap – low inflation and inadequate growth for reducing poverty,
essential for developing countries. Motivated by these facts, we ask three important
questions: (a) is there a threshold level of inflation at 5 per cent for developing
countries of Asia beyond which inflation is harmful for economic growth?; (b) does
the threshold level vary depending on the level of development within the developing
countries of Asia with poorer countries tend to have higher threshold?; and (c) is
there a consistency between the need for a change in the low inflation policy
suggested by the leading economists and country policy reports by the IMF?
185
The thesis is organised in seven chapters. Chapter 1 introduces the issues and sets the
research agenda while Chapter 7 provides the concluding remarks. The rest of the
chapters are devoted to research investigation. Our investigation and analyses to
address the issues took place within two broad frameworks. In the first case, we
provided a critical review of existing literature, including IMF Article IV country
consultation reports, in Chapters 2, 3, and 4. Chapter 2 mainly reported an in-depth
content analysis on the IMF country consultation reports with a view to examining
whether there has been a change in the perception of policy advice by the IMF in the
wake of the global crisis of 2007-2009. Chapter 3 critically reviewed the recent
cross-country studies relating to inflation-growth nexus in developing countries to
find broad evidence on inflation threshold beyond which inflation is harmful for
economic growth. Chapter 4 sought to explain the nature of growth-inflation nexus
by reviewing country-specific literature on selected developing countries of Asia.
This review of existing studies revealed evidence from selected individual countries
of Asia-Pacific region in line with our research interests. In the second part of our
investigation, we provided an empirical analysis to find evidence on the research
questions. This has been dealt with in Chapters 5 and 6. Chapter 5 employed crosscountry panel estimation techniques to show empirical evidence from selected Asian
developing countries. Chapter 6, on the other hand, examined a country-specific case
in the context of Bangladesh.
Findings from both critical reviews and econometric analyses tell us that the
empirical justification to keep inflation as low as 5 per cent is rather weak. Our
empirical evidence suggests that inflation thresholds for these developing countries
range between 8 and 15 per cent, well above the level, 5 per cent, advocated by the
IMF. Besides, poorer countries tend to have a higher threshold, providing convincing
evidence against one size fits all policy and that country-specific circumstances
matter. We also find little evidence of a change in policy prescription by the IMF in
the post-crisis era. Our content analysis using the country reports provides strong
support on this. The results from our analyses broadly support earlier findings that
threshold level of inflation is well above 5 per cent for developing countries and the
level also differs with higher inflation tolerance observed for poorer countries. In the
following paragraphs, we summarise the issues discussed in each chapter.
186
In Chapter 1, we introduced the issues relating to our investigation. We provided an
overview of the IMF policy supporting low inflationary environment in the
developing countries and the likely consequent danger these countries might face.
The argument put forward by the IMF, in short, is that inflation acts as a tax for the
poor and also raises uncertainty which, in turn, is bad for investment and growth.
This persuades the IMF to advocate for keeping inflation at 5 per cent or below in
developing countries. An inflation rate above this is believed to be bad for growth
and hence poverty reduction. Maintaining this nominal target is believed to be safe in
terms of preventing the inflation rate from accelerating. In order to achieve this, the
countries need to rely heavily on tight monetary policy and reining in fiscal deficits.
The likely adverse consequence of pursuing such tight policies is that they restrict the
development prospects of these countries. High interest rates raise the cost of
borrowing for business and thus are not beneficial for private sector growth. This is
an important consideration given the fact that World Bank’s Enterprise Surveys show
access to finance is among the top-5 business impediments for 93 per cent of the
countries in Asia and the Pacific. Access to finance is critical for small and medium
size enterprises (SMEs) as well as for agriculture, which depend solely on the
banking sector for external financing. Policies aiming at containing inflation at a very
low level also reduce the ability of fiscal policy to perform its developmental role. In
many cases, governments reduced fiscal deficits and public debt by cutting vital
infrastructure investment, especially in agriculture as noted in the United Nations
Economic and Social Survey of Asia and the Pacific 2013. In addition to its direct
adverse impact on productivity, insufficient infrastructure adds to the cost of
business.
As a result, insufficient private sector investment for development is a common trait
in the developing countries. Reduced government spending coupled with insufficient
investment often resulted in a stabilisation trap, especially in countries that were
under IMF’s support programmes. This was particularly evident in the wake of the
Asian financial crisis in 1997-98. Malaysia and Thailand recovered quickly by
following policies contrary to the IMF advice while Indonesia’s recession worsened
due to contractionary policies of the IMF.122 Interestingly, one study (Chowdhury
122
For a review of Indonesia’s policy dilemma after the crisis, see Chowdhury and Siregar (2004).
Chowdhury (2004) provides an assessment of monetary policy in selected Asian countries in the wake
187
1999) traces the seed of the Asian crisis that originated in Thailand to its stabilisation
programme with the IMF in the late 1980s. Thailand achieved programme
conditionality by drastically reducing public infrastructure investment, which
affected adversely its international competitiveness as manifested in the rise in
current account deficits, making its currency ideal for speculative attacks.
The classic example of severe development cost of over-zealous restrictive policies
aimed at stabilisation is Argentina in the 1990s. In order to combat against the
hyperinflation of the 1980s, Argentina had to undergo the IMF stabilisation program
in the 1990s. The policies were so stringent that inflation came down to a very low
single digit level, at 1.5 per cent annually. But the pursuit of low inflation target had
a severe cost in terms of growth, unemployment, and poverty. The tight
macroeconomic policies that the country continued to implement led to a
“deflationary spiral”. It led the economy enter into a recession, resulting in
unemployment rate to reach at a staggering rate of around 17 per cent by the mid1990s. Poverty rate (head-count ratio) showed a 13 percentage point rise, reaching at
34.3 per cent in 2002.
Restrictive macroeconomic policies also have negative magnified impact on growth
in the event of a supply shock. This is particularly true in the case of developing
countries which are prone to adverse supply shocks such as social unrests and natural
disasters. As a negative supply shock results in high inflation, the IMF usually
advises to pursue a contractionary monetary and fiscal policy or not to accommodate
inflation. Such a policy stance is believed to help tame inflation expectations and
thus acceleration in inflation. However, the strict adherence to a fixed nominal target
in all circumstances makes macroeconomic policies pro-cyclical and leads to a
contraction of aggregate demand causing output to fall even further. Therefore, tight
macroeconomic policies to achieve low inflation can have inadvertent consequences
on economic growth in developing countries in a number of ways. Moreover, this
perception on inflation by the IMF does not seem to be in agreement with its own
mandate. According to the agreement stated in the IMF’s Article IV, member
of Asian financial crisis of 1997-98 and finds that monetary policy in most of these countries were
restrictive and caused a stabilisation trap.
188
countries are supposed to aim at policies to foster orderly economic growth with
reasonable price stability, considering the country-specific circumstances.
Chapter 1 also provided some empirical evidence, both in broad and country-specific
contexts. A glimpse on growth-inflation relationship from 150 developing countries,
using a scatter plot, revealed that the relationship is nonlinear, showing a plateau
rather than a sharp cliff edge between 5 and 15 per cent of inflation. This general
overview shows that the fear of accelerating inflation and a sharp decline in growth
when inflation reaches above 5 per cent is unsubstantiated. Country-specific
examples from two countries in the Asia-Pacific region, South Korea and Indonesia,
provided significant evidence that they grew rapidly amidst high inflation
particularly during their early stage of development. The experience of South Korea,
which is no longer a developing country now, tells us that in the 1960s and 1970s
South Korea was more interested in growth rather than attaining price stability in a
narrow sense. Inflation at that time was high, above 20 per cent. But a strong growth
rate of 8 per cent, at the same time, encouraged South Korea to adhere to growth
promoting policies by allowing both monetary and fiscal policies to play their
developmental role, supported by other policies dealing with exchange rate, foreign
direct investment, and industry policy. The consequence was that its growth was
durable and inflation did not accelerate. A similar story from Indonesia in the 1970s
is also evident. The economy grew at around 7.7 per cent even though inflation was
around 17 per cent. In the initial phase of development of these countries, inflation
appeared to be an efficient way to mobilise resources for capital accumulation and
investment needed for rapid economic progress.
The theoretical debate surrounding the growth-inflation relationship and broad
empirical evidence from cross-country studies were also discussed in Chapter 1. It
recounted the Kalecki-Kaldor-Keynesian perspective that moderate inflation may be
beneficial for growth and structural transformation for developing economies.
Inflation helps redistribute income conducive for raising savings propensity needed
for higher investment; it also transfers resources to the government to allow
necessary public investments. The chapter also revisited the neoclassical theories
which show that inflation is harmful for growth. This is because both consumption
and investment decline as a result of fall in real money balances and increased
189
uncertainty, respectively. In an open economy, inflation also leads to real
appreciation of domestic currency, thus making exports less competitive.
The issue of Phillips curve in explaining the debate over inflation and employment
(or growth) was also discussed in the chapter. It explained the two opposing views
(originating in the context of Indian economy) of why expansionary policies may
cause inflation in the developing economies. One view is that because the supply in
developing countries is inelastic due to structural bottlenecks, an increase in
aggregate demand as a result of expansionary policies will only cause inflationary
pressure. The opposing view argues that it is not the supply rigidities but the low
subsistence real wages of workers that cause inflation as a result of the expansionary
policies. Since, real wages in developing countries are already at a very low level and
cannot go down any further, increases in prices as a result of expansionary policies
have to be compensated by raising the nominal wages. Because real wages do not
change, i.e. due to real wage resistance, employment level determined by it does not
change either.
On the empirical side, a brief discussion tells us that most studies on developing
countries find a threshold level of inflation above 5 per cent. These empirical works
are carried out both inside and outside the IMF. The chapter also outlined the
influential structuralist-monetarist debate, originating in the 1950s in the context of
Latin American countries. The empirical studies based on the structuralist argument
show that causality between inflation and growth is bidirectional. Theoretically
aligned mainly towards Keynesianism, they argue that inflation promotes economic
growth and is an inevitable companion to it. The latter fact is because of the
structural rigidities in developing economies for which supply cannot keep pace with
rising demand (resulting from growth of real incomes). Besides, inflation that results
directly from economic expansion may not create any significant barrier to
expansion. On the other hand, empirical literature, supporting the monetarist view,
show that inflation causes economic growth negatively. Their theoretical argument
behind this empirical finding is predicated on neoclassical theories stated above.
Finally, Chapter 1 concluded with the discussion on the research questions and
outline of the way in which we examined the issues in this thesis.
190
Against the backdrop of global economic crisis of 2008-2009, leading economists,
both inside and outside the IMF, called for a need to revisit the traditional
macroeconomic tenets, particularly the wisdom of low inflation policies. We wanted
to understand the nature of policy advice by the IMF and to what extent it reflected
the need for a change in the aftermath of the crisis. To achieve this objective, in
Chapter 2, we selected IMF Article IV country consultation reports and provided an
in-depth content analysis. Our intention was to reveal the experiences from some of
the growing developing countries of Asia-Pacific region. To this end, we selected 12
countries mostly from South and East Asia depending on the availability of the IMF
reports issued around the time of the crisis. These countries are Bangladesh, Bhutan,
Cambodia, China, India, Indonesia, Lao PDR, Malaysia, Maldives, Nepal, Pakistan,
and The Philippines. We noticed enough variations in the levels of economic and
social developments amongst these countries. For instance, Bangladesh, a small
country, initially followed a socialist path but quickly moved into a more market
oriented system which resulted into a rising middle class. On the other hand, Nepal,
also a small country, but is land-locked geographically and is still emerging out of its
social conflicts.
Despite these differences in the country characteristics, policy advice from the
reports shows that containing inflation at a low single digit level receives priority in
general. In other words, there is little evidence that country-specific circumstances
have been taken into consideration by these reports. For example, in Bangladesh,
although inflation was below 6 per cent in 2009, the IMF wanted the government to
become cautious about an increase in inflation. The policies were considered too
accommodative in view of the domestic conditions. This suggestion was made when
economic growth was around 5 per cent, well below 8 per cent that is required for the
country’s rapid development. The example from Nepal shows that the IMF pays
similar attention to inflation situation, giving less priority to economic growth. Nepal
is also one of the poorest countries of the world like Bangladesh but its
socioeconomic characteristics are quite different from that of Bangladesh as noted
above. Inflation in Nepal was around 11 per cent in 2009 and the IMF report stated
that loose monetary policy was responsible for this double digit inflation. This
cautionary note came when the country was still struggling with a low growth
191
performance at around 4 per cent. In both cases, the perception of keeping inflation
below 5 per cent is evident, despite the differences in country-specific characteristics.
In addition, historical experience from these countries shows that inflation, in most
cases, remains well above 5 per cent without affecting their growth performance.
Given the findings from the analysis, we have provided a critique on the continued
policy advice by the IMF from three directions. We found inconsistency at all three
levels – (a) with the need for a change suggested by the IMF’s own senior
economists, (b) with the historical data on inflation and growth, and (c) findings from
the literature in general. Our content analysis showed that the IMF policy still tends
to follow a pre-set view with predictable conclusions that do not allow for alternative
perspectives. The analysis, in this chapter, reaffirmed the need for a change in the
narrow policy advice by the IMF and put it firmly on its already stated principle of
fostering economic growth with reasonable price stability.
To examine if there is strong empirical evidence of an inflation-threshold at 5 per
cent for developing countries we looked at the existing literature based on crosscountry panel studies. Chapter 3 provided a critical review of some of these
important studies. Here, we also found evidence that the inflation-threshold
according to recent research lies well above 5 per cent. Broadly, findings from
majority of these studies suggest that the threshold varies between 7 and 19 per cent.
Interestingly, even studies carried out inside the IMF support a threshold above 5 per
cent for developing countries in general. Some of these results are sufficiently robust
as they take into account advances in dynamic panel estimation techniques.
Therefore, we can reasonably conclude from the cross-country panel evidence based
on the literature that policy advice to keep inflation at 5 per cent is not well founded.
We have also identified that there is no panel study using dynamic analysis
emphasising particularly on developing countries of Asia. Chapter 5 of this thesis
filled this gap.
We examined the country-specific literature in Chapter 4 as cross-country studies
cannot capture country-specific circumstance. Thus we believe that country-specific
analysis provides a better understanding about the growth-inflation nexus in a
particular country. We provided a critical review of the literature from the growing
192
developing countries of South and East Asia. We noticed a number of interesting
findings from the review. First, inflation and growth may move together in
developing countries. The reasons behind this are structural causes such as inevitable
fiscal deficits due to the need to finance the effort to close large physical and social
structural deficits with low tax base, subsistence agriculture, and various other supply
rigidities and bottlenecks. Second, studies which find very low threshold level of
inflation do not seem to be consistent with the country’s historical inflation-growth
experience. Third, studies which find a relatively high inflation threshold seem to be
in line with the historical experience but suffer from methodological problems. We
filled this gap in Chapter 6 where we performed our country-specific empirical
analysis.
The review of country-specific literature also revealed that countries trying to keep
inflation at a very low level have to sacrifice economic growth. This is evident from
the higher volatility in growth. Both Indonesia and Thailand showed this
characteristic when we compared these economies between pre and post Inflation
Targeting (IT) regimes. The discussion also showed that monetary policy faces a
challenge of controlling inflation and maintaining export-led growth at the same
time. Higher domestic price level causes loss in competitiveness in international
markets. But so does the tight monetary policy to curb inflation. Tight monetary
policy using higher interest rate to fight inflation causes domestic currency to
appreciate (as higher interest rate attracts more capital inflow) and the country loses
its competitiveness in the international markets.
The critical review of the existing literature motivated us to examine the relationship
between growth and inflation empirically. We provided our empirical analyses in
two chapters. Chapter 5 dealt with cross-country panel study using different panel
estimation techniques while Chapter 6 investigated the case of Bangladesh using
time series analysis. Our selection of developing countries of Asia for panel study in
Chapter 5 was influenced by the availability of data on variables considered in the
models estimated. The 14 countries used in the analysis are Bangladesh, Cambodia,
India, Indonesia, Lao PDR, Malaysia, Pakistan, The Philippines, Thailand, Vietnam,
Kazakhstan, Kyrgyz Republic, Papua New Guinea, and Tajikistan. We have
excluded China in this case because we believe it is an outlier considering its size,
193
economic structure, and political-economic institutions. Our analysis includes both
static models, such as Fixed Effects and Random Effects models, and dynamic panel
estimation models.
The key strength of our analysis in Chapter 5 is the estimations using dynamic
System Generalised Method of Moments (SGMM) as well as robustness checks
using a number of subsamples. The SGMM is regarded as a superior instrumentation
technique amongst its counterparts in tackling the endogeneity problem. The results
are robust since they pass all the essential post diagnostic tests, confirming that the
underlying assumptions of the models hold. The findings from the analyses using 14
countries for the period 1961-2010 revealed that the empirical basis for keeping
inflation at 5 per cent or below is rather weak. We found that the threshold level
ranges between 8 and 15 per cent. In particular, an important finding is that the
threshold levels vary according to the levels of development. There is much evidence
that for poorer groups of countries thresholds tend to be higher. In short, these
findings substantiate the issues we address in our research questions. First, the
inflation threshold in developing countries of Asia is much higher than 5 per cent.
Second, poorer countries have higher threshold levels of inflation.
The time series analysis on Bangladesh, carried out in Chapter 6, provided strong
evidence that inflation-threshold is not as low as 5 per cent. Based on annual
observations between 1977 and 2009 the threshold is found around 15 per cent.
Evidence also revealed that inflation does not appear to be a main reason behind low
economic growth in an underdeveloped country such as Bangladesh. Our analysis
also showed that inflation starts to pick up when economic growth is taking place.
Since inflation appears to be an inevitable consequence of growth, government
should not immediately take up anti-inflationary measure which might hurt growth.
The analysis of this thesis provides convincing evidence that the wisdom of
macroeconomic policies targeting low inflation in developing countries has serious
limitations, causing more harm than good. This particular tenet of mainstream
economics which continues to influence IMF’s policy advice should be revised. In
the context of developing countries of Asia, this study shows that developing
countries tend to have higher inflation tolerance and therefore IMF’s policy
194
suggestions are too narrow and seriously flawed. We have successfully addressed our
research questions as well. We draw the following conclusions from our
investigation: (a) there is no empirical justification for keeping inflation as low as 5
per cent, (b) the threshold level of inflation varies with the level of development and
targeting inflation should be done after carefully considering the country-specific
circumstances, and (c) policy suggestions by the IMF in developing countries should
incorporate the rethinking about macroeconomics. Macroeconomic policies should
be seen from a broader perspective and require a balance between the need for
stabilisation and development. Stabilisation is required but not sufficient for
development. This research suggests poverty reduction and employment creation
should be given priority over targeting a low inflation regime.
Our study raises some additional intriguing questions which can be pursued as future
research. An unresolved question relating to inflation threshold in both developing
and developed countries is whether the threshold is a cliff or a plateau in nature. If
the threshold is not too kinked and does not have a sharp cliff-edge, there would be
some room for accommodative policies and fiscal space, essential for rapid
development. It would also assure policy makers that macroeconomic policies need
not be overly cautious about inflation and therefore to keep it at a low single digit
level. Additionally, research can be carried out to determine the threshold level of
debt-GDP ratio or fiscal deficits to find out how they affect economic growth,
especially in light of the debate on fiscal austerity in the wake of the Great Recession
of 2008-2009 and the IMF’s recent admission that “there is no single threshold for
debt ratios that can delineate the “bad” from the “good.””123 The issue is vitally
important because public investment in infrastructure, education, health, and social
security leads to a positive impact on economic growth.
The findings about the threshold levels of inflation and debt-GDP ratio would also
have important implications for exchange rate policy because balance of payments,
fiscal deficits, and monetary policy stance are all closely intertwined. Therefore,
further investigation can be done to find out the implications on exchange rate policy
which is an important instrument for structural change as well as stabilisation. In our
123
IMF (2008, p. 109).
195
research, we have shown the importance of country-specific circumstances and how
they influence the growth-inflation dynamics. Similarly, the choice of an exchange
rate regime might be determined by specific characteristics of a country. This
therefore, would help raise questions about the validity of prescribing a more flexible
exchange rate regime and open capital account in developing countries. Moreover, a
similar research can be carried out to find the implications of the above issues on
wage policy and other aspects of labour markets in developing countries. Finally, out
of Asia; that is, to do similar studies for other developing regions in Africa and Latin
America.
196
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