Download A Sluggish Trend of National Savings and its Causes: The Case of

2016 Cambridge Business & Economics Conference
ISBN : 9780974211428
A Sluggish Trend of National Savings and its
Causes: The Case of Pakistan
Rukhsana Kalim
Professor of Economics
Department of Economics
School of Business and Economics
University of Management and Technology
C-11, Johar Town Lahore Pakistan
Email: [email protected]
Cell: 03054440614
and
Mohammad Shahid Hassan
Assistant Professor
Department of Economics
School of Business and Economics
University of Management and Technology
C-11, Johar Town Lahore Pakistan
Email: [email protected]
Abstract
Savings play a pivotal role for the development of the economy. Higher rate of savings
and their channelization to investment not only ensures the economic growth but also generates
employment opportunities. Aggregate savings are necessary for the growth of capital stock. In
order to achieve sustainable growth efficient utilization and the mobilization of domestic
resources, a decent rate of national savings is imperative (Khan, 1993). The objectives of steady
economic growth and development are knitted closely with the mobilization of domestic savings
and investment. The objective of the present study is to investigate the internal and external
factors determining national savings in Pakistan. After employing ARDL bounds testing
cointegration approach on the data series from 1976 to 2014, this study confirms the presence of
long run relationship between national savings and its determinants in Pakistan. The study finds
that depreciation of domestic currency, increase in exports and remittances significantly elevate
national savings in Pakistan whereas increase in interest payments against external debt and
imports significantly discourage national savings in Pakistan. These results are robust to different
controls and diagnostics. The study suggests that the government can play effective role in
controlling the internal as well as external factors determining national savings in Pakistan.
Keywords: Pakistan, Sluggish National Savings, Internal Factors and External Factors
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1. Introduction
Saving has been always considered as one of the important determinants of growth.
Developing countries can sustain the path of development on the basis of the higher rate of
savings in their economies. Higher rate of savings and their channelization to investment not
only boosts the income of the economy but also generates employment opportunities. Aggregate
savings are necessary for the growth of capital stock. In order to achieve sustainable growth
efficient utilization and the mobilization of domestic resources is much required (Khan, 1993).
The objectives of steady economic growth and development are closely knitted with the
mobilization of domestic savings and investment.
It is generally believed that national savings are a major source of investments in the
economy and contribute to the future economic development. On the basis of the high rate of
savings developed countries have achieved a decent economic growth. The high rate of domestic
savings can lessen the State dependency on foreign investments. It can also bring better stability
to the economy. The other socio economic problems like poverty and unemployment can also be
curbed. Therefore for policy making the analysis of saving behavior and its determinants are
essential (Nasir and Khalid 2004).
The growth models in the economic literature consider savings as an engine of growth.
The earlier Harrod- Domar (1939) growth model emphasized on the savings and capital output
ratio for the growth of the economy. Later Solow (1956) in his model highlighted that for steady
state of equilibrium of the economy saving is a key determinant. The classical school of thought
discussed the rate of interest as a major factor determining saving behavior. While the Keynesian
school of thought emphasized on the role of income in determining saving behavior. Different
models were developed to express the behavior of saving along the lines of various hypotheses.
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For example, Modigliani and Brumburg (1954) presume that by allocating lifetime discounted
income to consumption in various periods of the life cycle individuals maximizes their lifetime
utility and in each period equalize the discounted marginal utility of consumption in each period.
The permanent income hypothesis by Friedman’s (1957) offers varieties of common features,
underscoring additionally softening of utilization from "transitory disparity in realized income”.
Browning and Annamaria (1996) portray both approaches inside of a typical conviction
uniformity model, since they both are dependent on inter-temporally elemental utility function
and capital market, from which expectations are inferred for short-run and long-run utilization
smoothing conduct.
There are many arguments which emphasize on the positive role of the savings in the
economic prosperity of the economy. It is imperative to identify the pressing factors affecting the
saving rate in the economy. As far as Pakistan’s economy is concerned the saving rate has been
showing a sluggish trend for many years. The growth rate of saving was 13.23 as a percentage of
GDP in 1997 which declined to 7.51 in 2004 (Table-1). After reaching at peak in 2004 (17.6%),
the saving rate started declining. (See Table 1 and Figure 1):
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Table – 1: Trends of Gross Saving Rate as Percentage of GDP
Year
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Source: Pakistan Economic Survey 2014-15
Saving Rate as % of GDP
13.23
16.67
13.95
15.98
15.94
16.49
17.35
17.61
15.21
11.92
12.23
8.38
10.27
9.97
9.11
7.06
7.86
7.51
Figure – 1: Gross Saving Rate as Percentage of GDP
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If we compare the saving rate of Pakistan with other South Asian countries it is evident
that Pakistan has been experiencing the lowest gross saving as a percentage of GDP (Table -2).
Table – 2: Comparison of Gross Domestic Savings (% of GDP)
Year
Sri Lanka
Bangladesh
17.32
14.70
1997
19.13
16.68
1998
19.51
16.73
1999
17.43
17.78
2000
15.77
16.97
2001
16.01
18.38
2002
15.99
17.58
2003
15.91
18.67
2004
17.90
18.06
2005
16.98
20.74
2006
16.93
20.23
2007
13.41
18.90
2008
17.80
19.99
2009
18.94
20.49
2010
14.83
19.84
2011
16.63
20.47
2012
19.98
21.17
2013
20.8
22
2014
Source World Development Report (2014)
India
23.30
21.88
24.95
23.22
24.71
24.01
25.45
30.70
31.53
32.71
34.02
30.46
30.92
32.16
30.04
27.96
27.83
29.3
Pakistan
13.23
16.67
13.95
15.98
15.94
16.49
17.35
17.61
15.21
11.92
12.23
8.38
10.27
9.97
9.11
7.06
7.86
7.51
On the basis of the analysis of the low growth rate of saving in Pakistan, it is imperative
to explore the factors determining the rate of saving in the economy. There is no single factor
identified in economic literature as mainly responsible for determining domestic savings.
Numerous factors have been figured out affecting the rate of domestic savings in different
countries. The present study aims to examine the determinants of national savings in Pakistan.
For this purpose the study categorizes the determinants of savings in to two; internal factors and
external factors. An attempt is made to examine the impact of these factors empirically on the
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rate of savings in Pakistan. The study employs ARDL bound testing cointegration approach on
the data series from 1976 to 2014.
The rest of the paper is organized into different sections. Section 2 is a compendium of
different studies on the relationship of savings with other factors. Section 3 is devoted to the
methodology and models utilized for the analysis. Section 4 consists of results. Lastly section 5
concludes the major findings of the study along with some policy implications.
2. Literature Review
Economic literature is full of empirical findings on the behavior of savings. Based on the
Keynesian model, GDP has been considered one of the important factors behind savings and a
positive relationship is expected to exist between these two. Many empirical studies suggest a
strong relationship between savings and growth especially in the case of developing countries
(See for example, Agarwal 2001; Jilani et al. 2013). As far as causality is concerned there is
mixed evidence. In some studies causal relationship goes from growth to savings (Agarwal 2001)
and in some studies this is other way round (Caroll and David,1994).
Depreciation of the domestic currency may also impact the savings. Depreciation is
considered a cure to trade deficit through the boost of exports. The effectiveness of depreciation
on correcting the balance of payments of a country however depends on the elasticity of exports
of the country. Generally speaking, if there is an improvement in exports, depreciation can have
positive impact on savings through the channel of income. Montiel and Luis (2008) in their
report, based on analytical models established a positive link between the depreciation of the real
exchange rate and savings. Recently attention has been paid to the positive contribution of
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remittances on savings and investment of the economy. Mishra (2005) in his study found that 1
% increase in remittances will mount investment by 0.6% of Gross Domestic Product in thirteen
Caribbean countries. Balde (2010) investigated the macroeconomic impact of remittances on
savings and investment in Sub-Saharan Africa during the period 1980 – 2004 and found the
strong impact of remittances on savings. Another point of view discussed in literature was the
crowding out impact of remittances on domestic savings. A study by Hossain (2011) examined
the role of foreign capital inflows and remittances in the domestic savings of developing
countries by taking the 63 developing countries in the panel for a period of 1971 – 2010. The
findings suggest that remittances flows have significant but negative impact on domestic savings
because the remittances displace the domestic savings.
The impact of real interest on savings is theoretically ambiguous because of the fact that
real interest rate is conflicting associated with substitution and income effects. An increase in
real interest rates cut the current price of future financial gain flows and thus encompasses
a negative impact on savings (income effect). However, at constant time it will increase net come
back on savings and makes savings additional enticing these days and ends up in a delay of
consumption and includes a positive impact on savings (substitution effect). The study by Nasir
and Khalid (2004) found that fiscal deficit negatively influence savings whereas real interest
rate and remittances positively influence savings in Pakistan. Matur et al. (2012) found the
income influence strong in case of Turkey and there was negative relationship between real
interest rate and savings there. Agarwal (2001) dissected the saving prototype of seven Asian
nations and recommends that there is variety in relationship between loan fee and reserve funds
from nation to nation. In the event of Malaysia, Taiwan and India a positive but statistically
insignificant relationship exists between interest rate and saving. Aleemi et al. (2015) made an
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effort to examine the relationship between national saving and important determinants in case of
Pakistan. They applied dynamic regression with ARMA specification for the period of 1980 –
2010 and found that inflation, interest rate and government expenditures were negatively
affecting the national saving rates. Samantaraya and Patra (2014) by applying ARDL approach
investigated the association among domestic savings and its determinants in case of India. The
findings of the study reveal that GDP, dependency ratio, interest rate and inflation exert
statistically significant impact on household savings both in long run and short run. A study by
Blanc et al. (2015) analyzed the role of household behavior within the perceived liquidity
constraints in 15 Euro countries. The findings of the study show that the household
characteristics and institutional macroeconomic variables are important determinants of
household saving preferences and credit constraints. Chaudhry et al. (2014) investigated the
fiscal and monetary determinants of national savings in Pakistan for the period of 1972-2010.
The results of ARDL approach reveal that deposit rate and government expenditure are
positively affecting national savings of Pakistan. M2 is highly significant and has negative
impact on national saving. Inflation rate is positively associated with national saving in the short
run.
Kwakwa (2013) examined the association between national savings and its related factors
in case of Ghana by employing Johanson cointegration technique and error correction model for
the period of 1975-2008. His empirical results showed that over the long period savings are
positively and significantly related with income and terms of trade while savings are negatively
related with dependency ratio, political instability and real interest rate. However, in short run
solely terms of trade affect savings positively. Loayza and Serven (2000) find in their study that
in comparison to domestic saving private savings are more positively sensitive to interest rate.
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The study of Jilani et al. (2013) is based on examining national savings and various
factors that impact national savings in Pakistan. By taking the data from 1973-2011, the study
used co integration and ECM for short run and long run analysis. Their results show that the role
of Gross Domestic Product, fiscal deficit and inflation is very vital in determining national
savings of Pakistan. Globalization is also discussed as an important factor determining saving
behavior of the economy. It is generally believed that globalization through increase in the
volume of trade influences the saving of a country as well. An investigation by Faridi and Asma
(2012) has been made to find out the impact of globalization along with other variables on
private, public and national saving of Pakistan for the period 1972-2010. The findings of the
study reveal that globalization, real interest rate, consumer price index and worker’s remittances
have significant and positive impact on national savings. Other variables like government deficit
and FDI also play a significant role on savings of Pakistan.
The objective of the study by Akpan et al. (2011) was to identify factors determining
household saving of rural agro-based labors in the south-south region of Nigeria. For the analysis
they used two-stage least squares method of concurrent equation model in the analysis. Crosssectional information was gathered from 250 haphazardly chosen laborers of five agro-based
firms in the study regions. The aftereffects of the investigation demonstrated that saving attitude
of the labors are being swayed by the size of the family, experience of the job, tax, income and
lastly the membership of a social group. The factors like CPI, remittance, rate of interest, public
loans, and government consumptions have been taken in the study by Imran et al. (2010) to
investigate their relationship with savings in Pakistan. They found a long run relationship of
these variables with national savings of Pakistan.
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Faridi et al. (2010) assessed the origin of the savings of the families dwell in Multan
region of Pakistan. In aggregate 293 respondents were selected for primary information. Field
survey was the source of data collection from 2009-10. Their results show that there is a
significant positive relationship between Participation of spouse, rate of total dependency,
overall income of the household and range of landholdings with household saving. Whereas
other way around significant negative relationship was observed with family size, education
family unit head, responsibility to be paid, marital status, expenditures on children’s education
and house’s value. The study upheld presence of Life cycle hypothesis.
Chaudhry et al. (2010) tried to investigate short run and long run determinants of national
saving in Pakistan. Time series data was applied from 1972 to 2008. To examine long run
relationship Johansson Co- integration approach was utilized and to observe short run directions
between variables VECM was used. The results reveal that in long run national saving of
Pakistan is positively impacted by Consumer Price Index, remittance of workers, interest rate,
exports and consumption by the government whereas public loans have negative impact in the
long run. In short run Remittance taken as % of Gross Domestic Product and rate of interest
were optimistically swaying National Saving. Horioka (2009) examined the pattern of saving of
the aged in Japan and China through the survey method by analyzing data from the year 1990 to
2008 at micro level. Thus, the income of the family and spending Survey were going to gather
data on saving rates by taking into account age gathering of the families head. The author also
concluded that dis-saving also occurs at three different ages, resigned age, functioning age and
prior ages as well. The study observed that dis-saving had been made at three different ages,
resigned ages, working ages and at early ages as well. The study suggested that the life cycle
model as exceedingly pertinent if there should arise an occurrence of Japan. Chaudhry et al.
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(2009) probed that how savings and investment efforts were influenced by overseas debt and
foreign debt servicing in Pakistan by using annual time series data from 1973 to 2006. The study
accomplished that savings have a very harmful relationship with interest rate and real Gross
Domestic Product. The regression coefficients were in line with the theory.
Some of the empirical studies have been also done to find out development of economic
rural households due to rural saving mobilization. For example, Fasoranti (2007) on the basis of
primary data from 5 villages of Nigeria found that there is a positive relationship between
income, Human Capital, Investments and assets with savings. The author also put forward that
household in rural areas should join co-operative societies to mobilize their saving. Agarwal
(2001) estimated co-integration on state saving rate with its preferred determinants incorporating
per capita income, real interest rate and foreign saving funds for three nations; Indonesia,
Thailand and Singapore and reasoned that the elected variables are co-integrated.
Hasnain et al. (2006) evaluated household’s saving in the progression of economics
advancement in Pakistan from the time 1972-2003.The finding reveal that per capita income, rate
of growth of per capita income, and interest rates exert positive impact on public savings while
both in short and long run inflation, ratio of young dependency, ratio of old dependency are
negatively swaying public saving. Demographic factors along the lines of life cycle hypothesis
have been also taken in some empirical studies of saving. Schultz (2005) suggested that there
was rise and fall between short run associations of saving with five year age degree of population
along with advancing ages as projected in the LC model. While determining the household
savings Callan and Christian (1997) took the data of 21 OECD countries for 1975-1995.
Structure of tax system, financing and kindness of the social security and welfare system were
found vital determinants of household savings. The private savings and its determinants have
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been investigated by Athukorala and Kunal (2001) in case of India for the period covering 19541998. The study found a positive and significant relationship between the level and growth of
disposable income. The real interest rate also depicted the positive relationship with the private
savings.
The literature review suggests that a number of factors influence the saving rate in
different countries. Contrary to the earlier studies, the present study categorizes the determinants
of savings into two; internal and external within the context of Pakistan and investigates their
impact on the saving rate in Pakistan. The study will be helpful in finding out the importance of
these factors on the basis of their category.
3. METHOD OF ESTIMATION
The methods to estimate results for this study will be discussed in the present part of the
study. In order to see the factors which determine the saving pattern in Pakistan; we have framed
three models given below:
lnSV t  AC  A ER lnER t  A INT lnINT t  A EXP lnEXP t  A IMP lnIMP t  A REM lnREM t  E1t
t
t
t
t
t
(1)
lnSV t  BC  BER lnER t  BINT lnINT t  BEXP lnEXP t  BIMP lnIMP t  BINF lnINFt  E 2t
t
t
t
t
t
(2)
lnSV t  CC  C ER lnER t  C INT lnINT t  C EXP lnEXP t  C IMP lnIMP t  C MD lnMD t  E3t
t
t
t
t
t
(3)
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Whereas:
Representation
lnSV t
lnER t
Composition of the Variables
ln [Savings / GNI]
External Factors
ln [Exchange Rate]
lnREM t
lnEXP t
Variable Names
Savings
Data Source
WDI [2014]
Period Range
1976 – 2014
Exchange Rate
WDI [2014]
1976 – 2014
Remittances
WDI [2014]
1976 – 2014
Exports
WDI [2014]
1976 – 2014
Interest Payments
WDI [2014]
1976 – 2014
Imports
WDI [2014]
1976 – 2014
Inflation
WDI [2014]
1976 – 2014
Demand for Money
WDI [2014]
1976 – 2014
ln [Remittances / Real GDP]
ln [Exports / Real GDP]
Internal Factors
ln [Interest Payments Against
External Debt]
ln [Imports / Real GDP]
lnINT t
lnIMP t
lnINF t
ln [CPI]
ln [Money Supply / GDP
Deflator]
lnMD t
For the estimation of the empirical results we would start testing unit root test for all the
variables in order to see the arrangement of integration of the data series. We will apply Ng –
Perron (2001) unit root test to fulfill our objective. The test is superior to traditionally developed
unit root tests such as ADF (1981) and Phillip – Perron (1988). One of the unique features of the
test is that it de-trends ERS and it allows the coefficient of φ to be one. The Null Hypothesis of
the test is that series has unit root, and if the estimated value of MZa falls in the critical region
then it rejects null hypothesis and it will conclude that data series has become independent of
unit root. The following equations will facilitate us to estimate unit root through Ng – Perron
[2001] test:
T


MZ  (T  1y d  λ̂ 2 )2T  2  y d 
a
T
t  1
t 1


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1
(4)
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ISBN : 9780974211428
1/2
 2 T d 
 yt 1 
T


t
1
MSB  

2
λ̂




MZ  MZ x MSB
t
a
(5)
(6)
After applying unit root test; we would like to probe the long run association among
savings and the factors affecting savings by utilizing ARDL bounds testing approach coined by
Pesaran et al. (2001). This approach will confirm the presence of long run association among
predicted varaibles and predictor variables only if the estimated value of F – Test will become
bigger in comparison to its corresponding higher critical bound. However; the approach further
states that if the estimated value of F – Test becomes less than the lower critical bound then there
will be no long run relationship between dependant and independent variables. Moreover; we
would not be able to extract any conclusion if the estimated value of F – Test will fall in among
lower and upper critical bounds. Furthermore; this approach is more robust for undersized data
series and for the data series which will become integrated at mixed order. The following
equations will help us to estimate F – Test and long run coefficients for our study:
ΔlnSV t  FC  F11lnSV t 1  F12 lnER t 1  F13lnINT t 1  F14 lnEXP t 1  F15lnIMP t 1 
11
p
p
p
p
F16 lnREM t 1  G11  ΔlnSV
 G12  ΔlnER
 G13  ΔlnINT
 G14  ΔlnEXP

t i
t i
t i
t i
i1
i0
i0
i0
p
p
G15  ΔlnIMP
 G16  ΔlnREM
γ
t i
t i 11
i0
i0
(7)
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ΔlnSV t  FC  F21lnSV t 1  F22 lnER t 1  F23lnINT t 1  F24 lnEXP t 1  F25lnIMP t 1 
21
p
p
p
p
F26 lnINF t 1  G 21  ΔlnSV
 G 22  ΔlnER
 G 23  ΔlnINT
 G 24  ΔlnEXP

t i
t i
t i
t i
i1
i0
i0
i0
p
p
G 25  ΔlnIMP
 G 26  ΔlnINF  γ 21
t i
t i
i0
i0
(8)
ΔlnSV t  FC  F31lnSV t 1  F32 lnER t 1  F33lnINT t 1  F34 lnEXP t 1  F35lnIMP t 1 
31
p
p
p
p
F36 lnINF t 1  G 31  ΔlnSV
 G 32  ΔlnER
 G 33  ΔlnINT
 G 34  ΔlnEXP

t i
t i
t i
t i
i1
i0
i0
i0
p
p
G 35  ΔlnIMP
 G 36  ΔlnMD
 γ 31
t i
t i
i0
i0
(9)
The above reported equations from (7) to (9) will facilitate us to test long run relationship
between savings and the factors which determine saving pattern in Pakistan and the same
equations will help us to compute long run coefficients of the determinants of savings. After
finding the long run coefficients of savings; we will see that whether savings follow convergence
hypothesis or do savings bounce back to stable equilibrium in response to any macroeconomic
shock to the economy? For this purpose; we will apply Error Correction Model and according to
Engle-Granger (1987), the equations of Error Correction Model will be found by accumulating
1st period lagged term of error term in the long run equations [6 – 9] of ARDL. The equations of
Error Correction Model are designed as:
p
p
p
ΔlnSV t  G C  G11  ΔlnSV
 G12  ΔlnER
 G13  ΔlnINT

t i
t i
t i
i1
i0
i0
10
(10)
p
p
p
G14  ΔlnEXP
 G15  ΔlnIMP
 G16  ΔlnREM
 α ecm
β
t i
t i
t i
11
t  1 11
i0
i0
i0
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p
p
p
ΔlnSV t  G C  G 21  ΔlnSV
 G 22  ΔlnER
 G 23  ΔlnINT

t i
t i
t i
i

1
i

0
i

0
20
(11)
p
p
p
G 24  ΔlnEXP
 G 25  ΔlnIMP
 G 26  ΔlnINF  α ecm
β
t i
t i
t i
21
t  1 21
i0
i0
i0
p
p
p
ΔlnSV t  G C  G 31  ΔlnSV
 G 32  ΔlnER
 G 33  ΔlnINT

t i
t i
t i
i1
i0
i0
30
(12)
p
p
p
G 34  ΔlnEXP
 G 35  ΔlnIMP
 G 36  ΔlnMD
 α ecm
β
t i
t i
t i
31
t  1 31
i0
i0
i0
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4. RESULTS AND DISCUSSION
In this part, results and their discussion are presented. The analysis part starts from the
discussion of descriptive statistics. From the results reported in Table – 3 represent that the
probability value of Jarque – Bera test is found to be insignificant for natural log of savings,
exchange rate, exports, imports, remittances, consumer price index and money demand which
concludes that all these variables are normally distributed. However, the probability value of
Jarque – Bera test for interest payments is witnessed to be significant. The results are reported in
the following Table – 3:
Table – 3: Descriptive Statistic
lnSV t
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
Jarque-Bera
Probability
Sum
Sum of Square Deviation
Observations
lnER t
lnINT t
2.5879
3.4471
0.1363
2.4337
3.4545
0.289
4.2821
4.6388
0.6903
0.5648
2.2925 -1.0303
1.0099
0.7861
0.5062
0.064
-0.1267 -0.8233
1.8994
1.6333
2.4726
1.995
3.1394
4.8582
0.3688
0.2081
0.0881
100.9279 134.4378 5.3146
38.7559
39
23.4825
39
9.7379
39
lnEXP t
lnIMP t
2.6326
2.9285
2.6734
2.9041
2.9594
3.507
2.1615
2.5853
0.2129
0.2284
-0.4403
0.6523
2.2131
2.8539
2.2663
2.8001
0.322
0.2466
102.6698 114.2106
1.7223
39
1.9829
39
lnREM t
1.5155
1.5923
2.327
0.3741
0.5057
-0.555
2.4757
2.4487
0.294
59.1048
9.7164
39
lnCPI t
3.9467
-0.3448
4.0043
-0.273
5.6435
1.1485
2.4536
-2.4993
0.9128
1.042
0.1202
-0.3827
1.9298
2.1173
1.955
2.2183
0.3762
0.3298
153.9228 -13.4469
31.6621
39
Afterwards, the order of integration of the data series is tested by using Ng – Perron unit
root test. The results of Ng – Perron reported in Table – 4 show that the variables of this study
are nonstationary at level whereas all the variables taken in this study are stationary at first
difference. This concludes that the order of integration of this study is same and it is one. The
results are presented in Table – 4 as below:
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lnMD t
41.2619
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Table – 4: Ng – Perron Unit Root Test
At Level
MZa
MZt
1.6782
1.8243
MSB
1.0870
MPT
91.7715
Variables
ΔlnSV t
lnER t
0.1422
0.0795
0.5589
22.7340
-9.3393
-2.1607
0.2314 2.6244
lnINT t
1.3957
0.9003
0.6450
35.1286
ΔlnER t
ΔlnINT t
-14.1145
-2.6433
0.1873 1.7863
lnEXP t
-2.9365
-1.1633
0.3962
8.2241
ΔlnEXP t
-8.8100
-2.0899
0.2372 2.8152
lnIMP t
-1.3056
-0.5838
0.4472
13.0570
ΔlnIMP t
-23.3356
-3.4157
0.1464 1.0504
lnREM t
lnCPI t
-4.9092
-1.4746
0.3004
5.1995
ΔlnREM t
-8.7055
-2.0644
0.2371 2.8981
-0.6649
-0.2641
0.3973
13.1220
ΔlnCPI t
-9.4249
-2.1530
0.2284 2.6684
lnMD t
0.8515
0.4080
Variables
lnSV t
Level of Significance
01 Percent
05 Percent
10 Percent
At First Difference
MZa
MZt
MSB MPT
-7.4599
-1.8775 0.2517 3.4782
0.4792 20.7375 ΔlnMD t
-21.8878
-3.2883 0.1502 1.1875
Asymptotic Critical Values of Ng – Perron Unit Root Test
MZa
MZt
MSB
MPT
–13.8000
–2.5800
0.1740
1.7800
–8.1000
–1.9800
0.2330
3.1700
–5.7000
–1.6200
0.2750
4.4500
After discussing the order of integration, now we would like to estimate long run
association between savings and its determinants by applying ARDL bounds testing approach.
The results are reported in Table – 5 whereas the corresponding critical values for F and W tests
are reported in Table – 6. In the below Table – 5; F – test is calculated for three models, and in
all the three models we see that the calculated F – test is larger as compared to its corresponding
upper critical bounds. For instance in the model no. 1: the estimated F – test is 4.7365 and it is
larger than its corresponding upper critical bound at 5 percent level of significance which is
4.3987. Similarly; in the model no. 2: the F – test has found to be 5.8102 and it is also greater
than its upper critical bound at 5 percent level of significance and the upper bound at 5 percent
significance level is 4.3987. Afterwards; in the model no. 3: we may also see that the calculated
value of F – test has become greater than the corresponding upper critical bound at 5 percent
significance level. Therefore; we conclude that savings and its determinants have long run
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relationship with each other. Besides finding long run association among savings and the factors
which affect savings; now we would like to check whether this finding is reliable or not? For this
purpose we have also reported diagnostics in the Table – 5 for our conceptualized models. The
diagnostics report that in all the three models there is no autocorrelation or serial correlation; all
the conceptualized models are correctly specified, the error term of all the models has found to
be normally distributed, and there is no evidence of heteroscedasticity in all these models.
Therefore; it is concluded that the findings are reliable.
Table – 5: ARDL Bounds Testing Approach
Estimated Models
Optimal lags
F – statistics
W – statistics
SVt  f(ER t , INTt , EXP t , IMPt , REM t )
R2
Adjusted - R2
F – Statistics
DW – Statistic
DH – Statistic
Serial Correlation
Functional Form
Normality
Heteroscedasticity
SVt  f(ER t , INTt , EXP t , IMPt , INFt )
(1,0,0,0,0,0)
4.7365**
28.4189**
(1,0,0,1,0,0)
5.8102**
34.8612**
DIAGNOSTIC TESTS
0.9924
0.99228
0.9910
0.99048
676.0133 [0.000]
551.2095 [0.000]
2.0465
2.3955
-0.1881 [0.851]
-1.5908 [0.112]
0.0767 [0.782]
2.2281 [0.136]
0.0016 [0.968]
0.3099 [0.578]
2.8335 [0.242]
2.4224 [0.298]
2.6162 [0.106]
2.7276 [0.104]
SVt  f(ER t , INTt , EXP t , IMPt , MD t )
(1,0,0,0,0,0)
4.6630**
27.9782**
0.9919
0.9904
635.3379 [0.000]
2.2595
-1.0270 [0.304]
1.1183 [0.290]
0.1354 [0.713]
0.8618 [0.650]
2.4459 [0.118]
*;**, and *** demonstrates significance level at 10%; 5% and 1% respectively.
Also the values within [] represents Probability Values.
Table – 6: Critical Values for ARDL
Significance
Level
5 per cent
10 per cent
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Critical Bounds For F – Statistics
Lower Critical
Upper Critical
Bound
Bound
2.9804
4.3987
2.5078
3.6997
19
Critical Bounds For W – Statistics
Lower Critical
Upper Critical
Bound
Bound
17.8826
26.3919
15.0471
22.1983
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After finding long run association among savings and the factors affecting savings; now
we are looking to examine that how savings respond to the changes in the factors of savings in
the long run. The results of long run estimates are presented in the Table – 7 and these results
have disclosed that exchange rate and exports have positive relationship with savings in all the
three models, whereas, interest payments on external debt and imports are discouraging savings
in the long run in Pakistan in all the three models. Besides this the results also disclose that in
Pakistan savings are significantly and positively influenced by remittances.
Mishra (2005) and Balde (2010) have also found similar results in case of Carribean and
Sub-sahran African countries respectively. Faridi and Asma (2012) have also found the positive
relationship between remittances and savings in Pakistan. The estimated results for long run
coefficients are offered in the following Table – 7
Table – 7: Estimated Long Term Coefficients using the ARDL Approach
Dependant Variable: lnSV t
Coefficients
Coefficients
0.8497 [0.000]
0.5626 [0.037]
Coefficients
0.5158 [0.020]
lnINT t
-0.3943 [0.001]
-0.5055 [0.000]
-0.4595 [0.001]
lnEXP t
0.5629 [0.004]
0.4635 [0.054]
0.6438 [0.003]
lnIMP t
-0.4306 [0.080]
-0.5312 [0.052]
-0.4759 [0.094]
lnREM t
lnINF t
0.1474 [0.071]
-
-
-
0.1724 [0.478]
-
lnMD t
-
-
-0.1824 [0.342]
Ct
-0.6643 [0.561]
0.4554 [0.701]
0.5913 [0.611]
Variable
lnER t
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The coefficient of exchange rate has found to be positive and significant in the three
models reported in the above Table – 7; this positive coefficient shows that with the increase in
exchange rate, the domestic currency depreciates, and the fall in the value of local currency will
also decrease the price of domestic products for the foreigners, and therefore, demand for
domestic goods will be encouraged. This will enhance overall exports and foreign exchange
earnings in the country. Hence overall income and per capita income of the people will increase
and savings will be encouraged in the country. Our results are in conformity with the report by
Montiel and Luis (2008) who established a positive link between the depreciation of the real
exchange rate and savings.
Besides exchange rate; we may see that the coefficient of exports has found to be positive
and significant in all the three models. This simply shows that due to increase in the overall
exports in the country, foreign exchange earnings will increase, which will enhance overall
income and thus savings in the country. The ground reality is that Pakistan’s exports have been
stagnant for the last few years, wavering around US$ 24-25 billion. According to a UN study
covering a 30-year period (1980-2011), India’s share of world exports improved from 0.43
percent to 1.7, Pakistan’s share, however, remained stagnant at 0.15 percent (Pakistan Economic
Survey 2014-15). There is need to address the issues related to low volume of exports.
The coefficients of interest payments on external debt and imports have found to be
negative and significant in all the three models. This shows that when we pay more interest
against our liabilities then it discourages savings and economic activities in the country. The
negative relationship between the real interest rate and savings shows that the income effect is
strong in case of Pakistan. Our results are in conformity with Chaudhary et al. (2010) and Matur
et al. (2012) who found negative relationship between the real interest rate and savings in case of
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Pakistan and Turkey respectively. The negative coefficient of imports on savings in Pakistan
shows that with the increase in imports capital outflow takes place, thus discouraging domestic
savings and investment in the country. The inflow of remittances has significant and positive
impact on savings in Pakistan in the long run (Table – 7). Our results are in conformity with the
findings by Faridi and Asma (2012) in case of Pakistan. The short-run estimates are presented in
Table–8.
Table – 8: Estimated Short Term Coefficients using
Error Correction Representation for the Selected ARDL Models
Variable
ΔlnER t
Dependant Variable: ΔlnSV t
Coefficients
Coefficients
0.5689 [0.000]
0.3404 [0.037]
Coefficients
0.3188 [0.028]
ΔlnINT t
-0.2640 [0.001]
-0.3058 [0.000]
-0.2840 [0.001]
ΔlnEXP t
0.3768 [0.012]
0.5114 [0.007]
0.3980 [0.013]
ΔlnIMP t
-0.2883 [0.062]
-0.3214 [0.040]
-0.2942 [0.073]
ΔlnREM t
0.0987 [0.099]
-
-
ΔlnINFt
-
0.1043 [0.495]
-
ΔlnMD t
-
-
-0.1127 [0.361]
ecm t-1
-0.6695 [0.000]
-0.6050 [0.000]
-0.6181 [0.000]
R2
Adjusted - R2
F – Statistics
Akaike Information Criterion
Schwarz Bayesian Criterion
DW – Statistic
Diagnostics
0.6170
0.5428
8.3225 [0.000]
33.6362
27.9047
2.0465
0.6104
0.51949
7.8337 [0.000]
32.3127
25.7624
2.3955
0.5927
0.5138
7.5170 [0.000]
32.4664
26.7348
2.2595
From the above Table – 8 we may see that exchange rate and exports have positive and
robust impact on savings whereas interest payments on external debt and imports have negative
and significant impact on savings in all the three models in the short run in Pakistan. Besides
this; inflow of remittances has found to have significant but appreciating impact on savings in
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the short run in Pakistan. Afterwards; the negative and significant coefficient of error term
confirms the existence of convergence hypothesis in all the three models in this study; meaning
that we would be able to restore long run and stable equilibrium if we come across any unlikely
event or shock into our economy. Furthermore; the diagnostics of short run estimates are also
reliable.
Besides long run and short run coefficients; we have also tested that whether the error
term is normally distributed or not, for this purpose, we have plotted the histogram of the error
term and we have also plotted the error term within the upper and lower bounds. From the Figure
– 2 we may see that error terms are normally distributed for all the three models and the error
term fall within their bounds, therefore, error term fulfills the properties of white noise, so, we
have found white noise error term. The stable error term shows stable model. Therefore, the
findings of the study are reliable. The findings are reported in the below Figure-2:
Figure – 2
Models
Histogram of the Residuals
Plot of the Residuals within the Bounds
Plot of Residuals and Two Standard Error Bands
Histogram of Residuals and the Normal Density
7
6
0.1
5
4
0.0
1
3
-0.1
2
1
0
-0.4
-0.2
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
Sample from 1977 to 2014
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-0.3
1977
1987
1997
2007
2014
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Histogram of Residuals and the Normal Density
Plot of Residuals and Two Standard Error Bands
7
6
0.1
5
4
0.0
2
3
-0.1
2
-0.2
1
0
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
-0.3
1977
1987
1997
2007
2014
Sample from 1977 to 2014
Histogram of Residuals and the Normal Density
Plot of Residuals and Two Standard Error Bands
6
5
0.1
4
3
0.0
3
-0.1
2
1
0
-0.4
-0.2
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
-0.3
1977
1987
1997
2007
2014
Sample from 1977 to 2014
5. Conclusion and Policy Implications
This study was designed to examine the possible factors affecting national savings in
Pakistan. The study applies ARDL bounds testing approach for the data series from 1976 – 2014.
All three models explain the importance of the external factors like exchange rate, remittances
and exports in determining the saving rate in Pakistan. Among internal factors, the real interest
rate and imports have significant impact on national savings while inflation and demand for
money did not show the strong impact on the national savings in all the three models estimated.
Our results are supported by the earlier studies conducted by Chaudhary et al. (2010); Matur et
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al. (2012); Faridi and Asma (2012); Imran et al. (2010); Mishra (2005); and Adams et al. (2008).
The findings of the study suggest that government can target some of the external factors in order
to have their positive impact on national savings. For example, Pakistan's exports base and
markets are extremely narrow. Over 55 percent of its exports earning are contributed by the cotton
group alone. The other three items namely leather, synthetic made ups and rice contribute about
14 percent of total exports (Pakistan Economic Survey 2014-15). These four items are relatively
low value added product. There is need to make progress in increasing the number of products.
In addition to diversification of products, new markets needs to be explored for exports in
African countries, Central Asia, South America, ASEAN region, Russia, Eastern Europe etc.
Like exports, Pakistan’s imports are also highly concentrated in few countries. Based on
the data in 2014, around 50 percent of Pakistan imports originate from just few countries like
China, Kuwait, Saudi Arabia, UAE, India, Indonesia, etc. (Pakistan Economic Survey 2014-15).
The imports bills comprise of Petroleum group, food group, transport group and textiles group. A
careful scrutiny is required to import only those products which are of necessity type, rest to be
restricted. The positive impact of remittance on savings necessitates encouraging the inflow of
remittances by giving more incentives to expatriate, and providing secure investment
opportunities at home.
Pakistan bears the huge external debt servicing liability. It was US$ 1,282 million in first
nine months of 2014-15. Out of this total, principal repayments were US$ 3,291 million and
interest payments were US$ 812 million, whereas an amount of US$ 1,200 million was rolled
over (Pakistan Economic Survey 2014-15). Such a heavy external debt liability affects the
national savings of Pakistan that needs to be taken care of.
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References
1. Agarwal, P. (2001). The relation between savings and growth: Cointegration and
Causality Evidence from Asia,Bombay. Indira Gandhi Institute of Development
Research.
2. Akpan Sunday B., Edet J. U. and Ebirigor A.A. (2011), Analysis of Savings
Determinants among Agro-based firm Workers in Nigeria: a Simultaneous Equation
Approach, Research on Humanities and Social Sciences 1(3), 1-11.
3. Aleemi Abdur R., ShuaibA. And Tariq M., (2015), The Determinants Of Savings:
Empirical Evidence From Pakistan, International Journal of Management Sciences and
Business Research, 4 (1), 63-71.
4. Athukorala Prema C., and Kunal S., (2001), The Determinats of Private Saving in India,
https://ideas.repec.org/p/pas/papers/2001-12.html.
5. BaldeYero (2010), The Impact of Remittances and Foreign Aid on Savings/Investment in
Sub-Saharan Africa (SSA), African Development Review, 23, (2), 247-262.
6. Blanc Julia L., Alessandro P., Federica T., Junia Z., and Michael Z., (2015), Househol;d
Saving Behavior and Credit Constraints in the Euro Area, Working Paper Series No.
1790, European Central Bank, Euro System.
7. Browning M., and Annamaria L., (1996), Household Saving: Micro Theories and Micro
Facts, Journal of Economic Literature, (34)4, pp. 1797-1855.
8. Callan T. and Christian T. (1997), Empirical Determinants of Household Saving:
Evidence From OECD Countries, International Monetary Fund No. WP/97/181.
July 1-2, 2016
Cambridge, UK
26
2016 Cambridge Business & Economics Conference
ISBN : 9780974211428
9. Caroll Chris H., and David N. W., (1994), Saving and Growth: A Reinterpretation,
Carnegie-Rochester Conference Series on Public Policy, 40, 133-192.
10. Chaudhry I.S., Malik S., and RamzanM., (2009), Impact of Foreign Debt on Savings and
Investment in Pakistan, Journal of Quality and Technology Management, (5) 2, 101-115.
11. Chaudhry, I.S., Faridi, M.Z., Abbas M., and Bashir F., (2010), Short Run and Long Run
Saving Behavior in Pakistan: An Empirical Investigation, Journal of Money Investment
and Banking, 16, 57-166.
12. Chaudhry I.S., Umber R., Fatima F., and Salyha Z., (2014), The Monetary and Fiscal
Determinants of National Savings in Pakistan: An Empirical Evidence from ARDL
approach to Co-integration, Pakistan Journal of Commerce and Social Sciences 8 (2),
521- 539.
13. Faridi, M. Z. and Asma A. (2012), Globalization and Saving Behavior of Pakistan:An
Empirical Analysis, Pakistan Journal of Social Sciences (PJSS), 32(1), 77-93.
14. Fasoranti, M. M. (2007). The influence of rural Saving on Development of the rural
areas: A Study of Akoko Region in Ondo state in Nigeria,
International Business
Management, 1(2), 20-23.
15. Friedman, M., (1957), A Theory of the Consumption Function, Princeton NJ: Princeton
University Press.
16. Harrod, R.F., and Domar (1939), An Essay in Dynamic Theory , Economic Journal 14–
33, Retrieved from http://en.wikipedia.org/w/index.php?title=Harrod–
Domar_model&oldid=486441007.
July 1-2, 2016
Cambridge, UK
27
2016 Cambridge Business & Economics Conference
ISBN : 9780974211428
17. Hasnain, M., Atiq, Z., Alam, S. and Butt. M. S. (2006). The impact of Demography,
Growth and Public policy on Household Savings: A case study of Pakistan. Asia Pacific
Development Journal, 13(2), 57-71.
18. Hossain Delwar ( 2011 ) Differential Impacts of Foreign Capital and Remittance Inflows
on the Domestic Savings in the Developing Countries– A Dynamic Heterogeneous Panel
Analysis, Economic Record, Vol. 90, issue supplement, 102-126.
19. Horioko, C.Y. (2009), The (DIS) Saving Behavior of the Aged in Japan, National Bureau
of Economic Research, Working Paper No. 15601.
20. Imran, Z. M., Abbas, M., & Bashir, F. (2010). Short run and long run saving behavior in
Pakistan: An Empirical investigation. Eurojournals
21. Jilani S., Salman A.Sheikh, Farooq-E-Azam C & Ahsan-ul-Haq S. (2013), Determinants
of National Savings in Pakistan: An Exploratory Study, Asian Social Science, 9 (5), 254262.
22. Khan, M.S. (1993). Domestic Resource Mobilization: A Structural Approach. The
Pakistan Development Review, 32(4), 1067-1078.
23. Kwakwa Paul A., (2013), Determinants of National Savings: A Short and Long Run
Investigation in Ghana, KJBM, 5 (1), 1-15.
24. Loayza, S. K., & Serven, L. (2000). What Drives Private Saving Across the World.
Review of Economics and Statistics, 82, (2), 165-181.
25. Matur Pirgan E., Ali S., and Bahcei S., (2012), Determinants of Private savings and
Interaction between Public and Private Savings in Turkey, Topics in Middle Eastern and
African Economies Vol. 14, September, 102- 125.
July 1-2, 2016
Cambridge, UK
28
2016 Cambridge Business & Economics Conference
ISBN : 9780974211428
26. Mishra, P. (2005), Macroeconomic Impact of Remittances in the Caribbean”,
Unpublished paper, International Monetary Fund, Washington.
27. Modigliani, F. and R. Brumburg, (1954), AUtility Analysis and the Consumption
Function,@ Chapter 15, in Post Keynesian Economics, K.K. Kurihara (ed), New
Brunswick, NJ:Rutgers University Press, 388-436.
28. Montiel Peter J., and Luis Servén (2008), Real Exchange Rates, Saving and Growth: Is
there a Link? World Bank Policy Research Paper No. 4636, World Bank.
29. Nasir, S. and Khalid, M. (2004). Saving-Investment Behavior in Pakistan: An Empirical
Investigation. The Pakistan Development Review, 43(4), 665-682.
30. Samantaraya A. and Suresh K.Patra (2014), Determinants of Households Savings in
India: An empirical Analysis using ARDL Approach, Hindawi Publishing Corporation
Economics
Research
International
Volume
2014,
Article
ID
454675,
http://dx.doi.org/10.1155/2014/454675.
31. Schultz T. Paul (2005), Demographic Determinants of Savings: Estimating and
Interpreting the Aggregate Association in Asia, IZA Discussion Paper No. 1479,
Germany.
32. Solow M. R., (1956), A Contribution to the Theory of Economic Growth, The Quarterly
Journal of Economics, 70), 65-94.
July 1-2, 2016
Cambridge, UK
29