Download Estimating The Optimal Level of Inflation (Inflation Threshold) in the Kingdom of Saudi Arabia

Estimating the Optimal Level of Inflation (Inflation Threshold)
In the Kingdom Of Saudi Arabia
Safar AlQahtani1, Ahmed Elhendy and Adel khalifa
The objective of this study is to derive a threshold or optimal level
of inflation in the Saudi economy, where this level of inflation is the
boundary between the positive impact and negative impact of
inflation on the rate of economic growth. The results of this study
are of particular interest to policy makers that govern the
relationship between inflation and economic growth. The method
Hasanov
( 2011) was applied to estimate the optimal rate of
inflation (Inflation Threshold). The optimal rate of inflation (Inflation
Threshold) was ranged from 3% to 4%.Therefore policies makers
should determine the optimal level of inflation, by fiscal and
monetary policies to not exceed the level of inflation of 4% to avoid
the negative impact on the rate of growth of real gross national
income.
Key words: optimal level of inflation (Inflation Threshold), economic growth rate.
Introduction
It should be noted that the ultimate goal of economic policies is to achieve economic
growth while maintaining this growth, and taking into account the stability of the general
price level. To achieve this goal; fiscal policies is used to achieve the desired economic
growth, and monetary policy is used to achieve price stability. The achievement of both
objectives is a burden on policy makers, where there are economic concepts, contrary
to Keynesian point of view, that the presence of a moderate level of inflation contributes
to the promotion of economic growth (Mubarik 2005). At the continued increase in
inflation and thereby increase the general level of prices, reflected negatively on the rate
of economic growth (Feldstein 1982, Ocran 2007, Khan and Senhadji 2001), as the
arrival of the level of inflation to zero would be a negative effect on the rate of economic
growth, which loses producers the incentive to increase their production.
Therefore the relationship between the level of inflation and economic growth in the long
run will have a negative impact on economic growth in the case of increasing inflation
for a given level, which is defined as an inflation threshold or optimal Inflation Rate .
For studying the relationship between inflation and economic growth in the Kingdom of
Saudi Arabia, the goal is to derive a threshold or optimal level of inflation in the Saudi
economy, where this level of inflation is the boundary between the positive impact and
negative impact of inflation on the rate of economic growth. The results of this study are
of particular interest to policy makers that govern the relationship between inflation and
1
Safar AlQahtani , Ahmed Elhendy, Adel khalifa, King Saud University,College of Food and Agricultural
Sciences, Agriculture Economics Department
1
Corresponding author. [email protected]
economic growth. Thus achieved the goal to maintain the level of inflation rate for
maximum economic growth, and to avoid an increase in inflation from its best level to
avoid the negative impact of inflation on economic growth due to increased prices of
goods and services in the Saudi economy. This represents a target within the objectives
of studying the effects of inflation in the Kingdom of Saudi Arabia.
Previous studies
There are many studies on the relationship between inflation and economic growth in
developed and developing countries, however the review of reference in this study will
be limited on the concept of the level of the optimal inflation ( Inflation Threshold ) and
its impact on the level of economic growth, as assumed in many studies of non- linear
relationship to allow a maximum of inflation separates the positive and negative effect
on the rate of economic growth.
The (Sarel 1996) studied the relationship between the rate of inflation and economic
growth, plus the number of explanatory variables include the population , the degree of
economic openness , government spending , currency exchange rate, and investment
rate. Study was conducted on 87 countries in the period 1970 to 1990 m. The results of
the study illustrated the optimal level of inflation at a level of 8% on average for the
countries
under
study.
Christoffersen and Doyle (1998) studied the relationship between the level of non-linear
rate of inflation and economic growth in the number of 22 countries in central and
eastern Europe for the period 1990 to 1997 . The findings suggest that the optimal
inflation rate of 13%.
The World Bank study provided the basis for many of studies to estimate the optimal
level of inflation (Inflation Threshold). The study did not separate the effect of inflation
on the low and high rate of economic growth, it has been optimized to determine the
level of inflation in both industrial countries and developing countries for 140 countries
over the period 1960-1998 , where the results of the study indicated that the optimal
rate of inflation in industrial countries ranged between 1-3%, while this rate ranged
between 7-11% in developing countries (Khan and Senhadji, 2001).
The optimal rate of inflation in the economy of Armenian was estimated at 9% (
Mubarik, 2005) and 4.5% over the period 2000-2008 (Sargyan, 2005).
Shamim and Mortaza ( 2005) applied cointegration and error correction models to test
the relationship between the level of inflation and economic growth. Using GDP as
dependent variable and the consumer price index (CPI) as an indicator of the level of
inflation for the period 1980-2001. The results of the study inducated the presence of a
negative impact of inflation on the rate of growth in the long run, as much as the optimal
inflation
rate
by
about
6%.
estimate the optimal inflation rate in Nigeria was estimated at 6% using data from 19702003 (Fabayo and Ajilore, 2006) . The results of the study showed that inflation rates
less than 6% accompanied an increase in economic growth, while increasing the rate of
inflation of 6% accompanied by a decrease in economic growth.
In a study of 63 countries, industrial and non-industrial, the optimal rate of inflation was
estimated at 2% in industrialized countries and 12% in non-industrialized countries
(Kremer et al., 2009).
Munir and Mansur( 2009) studied the relationship between the level of inflation and
economic growth in Malaysia over the period 1970-2005. It confirmed the non- linear
relationship. The findings suggest that the level of the optimal inflation in Malaysia is
3.89%.
In the former Soviet Union countries, The relationship between the level of inflation and
economic growth rate for the period 2001-2008 was 8% (Sergi, 2009).
According to a study (Espinoza et al. 2010) contrast the relationship between the level
of inflation and the growth rate in 165 countries, including the oil-exporting countries,
using data for the period 1960-2007. An average level of optimal inflation in these
countries is 10%, with the exception of countries developed where the rate dropped
significantly from previous average. Possible separation between exporting and non-oil
exporter, where it became clear that increasing the level of inflation in oil-exporting
countries by 3% would lead to a decrease in real non-oil GDP by 2.7% per annum. In
general Li (2006) indicated that the relationship between the level of inflation and the
growth rate relationship is linear, and that there is a point at the level of inflation coup
optimization, separating the impact of positive and negative impact of the level of
inflation in the long-term on economic growth . The tipping point can be defined as the
level of optimal inflation or (Inflation Threshold).
Method
of
study
To formulate a model estimating the optimal rate of inflation (Inflation Threshold), will be
applied to model (Hasanov F., 2011), which adopted the method of estimating the
optimal level of inflation by (Khan and Sendhadji, 2001). The same method was
appliedas in Jordan by (Sweidan 2004), in Pakistan (Hussain 2005, Mubarik 2005, and
Nasir and Nawaz 2010), in Bangladesh (Shamim and Mortaza, 2005) in Malaysia
(Munir
and
Mansur,
2004).
The formulation of the mathematical model of the relationship between the level of
inflation and economic growth rate is as follows:
(
_
=
=
K
=
the
)
represents
a
growth
rate
of
real
GDP,
represents
the
rate
of
inflation,
optimal rate of inflation (Threshold level of Inflation),
Zt
= number of explanatory variables (population, investments, other),
Ut
=
error
term.
The dummy variable, its value vary as follows
Dt=1
Dt = 0
when
when
Based on the definition of (Mubarik 2005) and (Frimpong and Oteng-Abayie, 2010) the
K variable represents the optimal level of inflation (Threshold Inflation) with the property
that the relationship between the level of inflation and economic growth rate that takes
into
account:
A
the
level
of
low
inflation
=
α1.
B - the level of high inflation = α1 + α2.
Therefore the high level of inflation means that you need to add α1 + α2 in the model to
demonstrate the impact of inflation on the rate of economic growth. Representing an
optimal level of inflation (Inflation Threshold). Previous studies have indicated how the
last value of K, after which directly convert the value of α1 + α2 of positive value to
negative
value,
K
becomes
the
optimal
rate
of
inflation.
Estimating the regression coefficients for the variable K in the form when the value of
the various that are used in the order (1, 2, 3,….., 10), the optimum value of the variable
K is determined according to the maximum value for the coefficient of determination
(R2), or the lowest value for the sum of squared error (SSR), associated with the
regression
coefficients
at
different
values
of
the
variable
K.
Due to the acceptance of this method in the estimate on a large scale in practice, So
this method has been adopted in this study to achieve the goal of the study.
Stability
of
the
variables
Before estimating the regression coefficients in the previous model is required to assess
the stability of the variables of the study is done using the Unit Root Test, where
necessary provide 20 value at least (Gujarati and Porter, 2009) to get acceptable
results. Dickey – Fuller test was used to demonstrate the stability of the time series
under
study.
Study
data
Covering the variables of the study time period 1980 – 2010. the variables of the study
include both the level of inflation (INF) expressed by the Consumer Price Index ( CPI),
rate of growth of real national income (GDP), and in addition to other explanatory
variables, which include the number of population (POP.) and the rate of investment
(INV). The study variables on an annual basis due to the need for monetary and fiscal
policy makers to link the annual inflation rate target with annual economic growth rate.
In addition to avoid the need for re-calculated seasonal changes.
Table (1) shows the indicators of descriptive statistics for the variables of the study,
which included the GDP, INV, POP. Figure (1) illustrate the relationship between the
rate of growth of real Gross Domestic Product (GDP) and the rate of inflation (INF) in
the Kingdom for the period 1980-2010. It is clear from this figure how to change (GDP)
as dependent variable versus the change in the rate of inflation (INF) as an independent
variable to meet the goal of the study which was to examine the relationship between
both variables and determine the optimal rate of inflation. It is clear that there is a
relationship between inflation rate and growth rate of real GDP in the Kingdom, where
the study is based on the concept of the impact of the inflation rate (INF) as an
independent variable on the rate of growth of gross domestic product (GDP).
Table (1): Descriptive Statistics Indicators (1980-2010)
INV
20.59355
19.85400
27.62100
15.06900
2.488103
0.661609
3.953696
POP
17.91058
18.13600
27.56300
9.320000
5.306383
0.038931
1.953585
INF
1.254968
0.646000
9.871000
-3.173000
2.813621
0.975541
4.117690
GDP
2.018000
2.835000
9.104000
-11.09800
4.682804
-0.886200
3.716112
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
3.436407
0.179388
1.422186
0.491107
6.530599
0.038185
4.720031
0.094419
Jarque-Bera
Probability
638.4000
185.7197
555.2280
844.7309
38.90400
237.4940
62.55800
657.8596
Sum
Sum Sq. Dev.
31
31
31
31
Observations
Figure (1): The Relationship between the Inflation and Gross Domestic Product
20
15
10
31 29 27 25 23 21 19 17 15 13 11
9
7
5
3
5
inf
0
GDP
1
-5
-10
-15
Results
and
Discussions
I: test the stability of the variables of the study (Dickey - Fullar Test):
Dickey and Fuller ( 1981) test has been used for stability of time-series The results
ascertained of the stability of these time series for the variables of the study, Table (2).
II: Determination of the optimal inflation rate ( Inflation Threshold):
Regression coefficients was estimated in the model for the relationship between the
variables of the study. The use of estimated values for the variable rate of inflation
(Inflation Threshold) when K = 1, K = 2, ....., K = 9 in order to reach a minimum value for
the sum of squared coefficient of error (SSR) and the maximum value for the coefficient
of determination (R2) . Based on a study (Mubarik, 2005) and (Frimpong and Abayie,
2010) where the equation of the regression model was estimated using the least
squares method (OLS). The inclusion of the results in table (2). Results of the study
showed that the optimal level of inflation of 4%, where he has achieved the lowest
estimate of the error sum of squares (SSR) and the highest value for the coefficient of
determination (R2). It is clear that estimating the optimal level of inflation in the Kingdom
of Saudi Arabia is less than (Espinoza, 2010) of 13% for the countries of Central and
Eastern Europe, including the oil-exporting countries such as Kozrbijan. There is also a
13% estimation in developing countries (Christoffersen and Doyle, 1998). The inflation
rate optimization in the Kingdom is still less than the transition countries of the socialist
to the capitalist system, amounting to 8% (Sergii, 2009), 11% in developing countries
(Khan and Sendhaji, 2001), and 17% in the non-industrial (Kremer et al., 2009). With
reference to the results of the study table (2) can estimate the value of α1 =0.59 and α2
=0.63 at the optimal rate of inflation of 4%, thus to demonstrate the effect of increasing
the rate of inflation on the optimal rate of change in real gross national income is
required to estimate α1 + α2, which means that an increase in inflation rate 1% increase
on the rate of inflation will be accompanied by a lack of optimal growth rate of real GDP
by 0.04% as:
α1 + α2 = 0.590229 - 0.634469 = -0.04424
Of the table indicates that when an optimal inflation rate of 3%, we find that
α1 + α2 = 0.659454 - 0.619435 = -0.04002
Which means that there is an opportunity to increase the rate of growth of real gross
national income by 0.04% in the case of increasing the optimal rate of inflation of 3% to
4%.
Therefore policies makers should determine the optimal level of inflation, by fiscal and
monetary policies, work to not exceed the level of inflation of 4% to avoid the negative
impact on the rate of growth of real gross national income. It should be noted that
(Kemer et al., 2009) has acknowledged that the rate of optimal inflation in a country is
an indicator for this country without the other countries, and may not disseminate the
results of determining the optimal size of inflation (Inflation Threshold) to other countries
due to the characteristics of the architecture and associated economic activity in the
country. Therefore recommended that the identification of the target to be achieved the
country of inflation is linked to a growth rate of real gross national of that State to allow
for the identification of long-accepted or allowed inflation in the short term and long
term.
Table (2): Regression Equations at Different Optimal Inflation levels (K)
Gdp = b0 +b1 inf + b2 D1( inf – 1) + b3 pop + b4 inv
where d1=1 if inf-1>0 , and D1=0 if inf-1 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.178246
R-squared 0.3477
0.956382
8.178167
7.821449
C
540.5986
SSR
0.6246
0.495203
0.787762
0.390102
INF
0.9518
0.060973
1.103848
0.067305
D1(INF-1)
0.2818
1.099132
0.171349
0.188335
POP
0.2168
-1.265741
0.373799
-0.473133 INV
Gdp = b0 +b1 inf + b2 D2( inf – 2) + b3 pop + b4 inv
Prob.
t-Statistic
0.181523
R-squared 0.4478
0.770808
where d2=1 if inf-2>0 , and D2=0 if inf-2 ≤0
Std. Error
Coefficient
8.464459
6.524473
C
538.4429
SSR
0.3592
0.7453
0.2679
0.2929
0.933383
-0.328368
1.132155
-1.073490
Gdp = b0 +b1 inf + b2 D3( inf – 3) + b3 pop + b4 inv
0.668697
1.166330
0.171800
0.382559
0.624150
-0.382985
0.194504
-0.410673
INF
D2(INF-2)
POP
INV
where d3=1 if inf-3>0 , and D1=0 if inf-3 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.186543
R-squared
0.4867
0.705654
8.396874
5.925285
C
535.1405
SSR
0.2390
1.205082
0.547228
0.659454
INF
0.6084
-0.518597
1.194444
-0.619435
D3(INF-3)
0.2506
1.175063
0.172482
0.202678
POP
0.3073
-1.041430
0.373826
-0.389314
INV
Gdp = b0 +b1 inf + b2 D4( inf – 4) + b3 pop + b4 inv
where d4=1 if inf-4>0 , and D4=0 if inf-4 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.186975
R-squared
0.4559
0.757006
8.179481
6.191916
C
534.8562
SSR
0.1945
1.331616
0.443242
0.590229
INF
0.5993
-0.531888
1.192863
-0.634469
D4(INF4-4)
0.2510
1.174168
0.172196
0.202187
POP
0.2753
-1.114425
0.362665
-0.404163
INV
Gdp = b0 +b1 inf + b2 D5( inf – 5) + b3 pop + b4 inv
where d5=1 if inf-5>0 , and D5=0 if inf-5 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.180685
R-squared
0.3939
0.866955
8.071740
6.997833
C
538.9944
SSR
0.2149
1.271369
0.384111
0.488347
INF
0.7781
-0.284801
1.231159
-0.350636
D5(INF5-5)
0.2701
1.126967
0.171872
0.193694
POP
0.2342
-1.217772
0.358940
-0.437107
INV
Gdp = b0 +b1 inf + b2 D6( inf – 6) + b3 pop + b4 inv
where d6=1 if inf-6>0 , and D6=0 if inf-6 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.179985
R-squared 0.3812
0.890719
8.020281
7.143820
C
539.4545
SSR
0.2188
1.260287
0.379002
0.477651
INF
0.8102
-0.242630
1.505751
-0.365341 D6(INF6-6)
0.2737
1.118158
0.171522
0.191788
POP
0.2268
-1.237872
0.357548
-0.442599 INV
Gdp = b0 +b1 inf + b2 D7( inf – 7) + b3 pop + b4 inv
where d7=1 if inf-7>0 , and D7=0 if inf-7 ≤0
0.179985
539.4545
R-squared
SSR
Prob.
0.3812
0.2188
0.8102
0.2737
0.2268
t-Statistic
0.890719
1.260287
-0.242630
1.118158
-1.237872
Std. Error
8.020281
0.379002
2.030221
0.171522
0.357548
Coefficient
7.143820
0.477651
-0.492593
0.191788
-0.442599
C
INF
D7(INF7-7)
POP
INV
Gdp = b0 +b1 inf + b2 D8( inf – 8) + b3 pop + b4 inv
where d8=1 if inf-8>0 , and D8=0 if inf-8 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.179985
R-squared 0.3812
0.890719
8.020281
7.143820
C
539.4545
SSR
0.2188
1.260287
0.379002
0.477651
INF
0.8102
-0.242630
3.115320
-0.755871 D8(INF8-8)
0.2737
1.118158
0.171522
0.191788
POP
0.2268
-1.237872
0.357548
-0.442599 INV
Gdp = b0 +b1 inf + b2 D9( inf – 9) + b3 pop + b4 inv
where d9=1 if inf-9>0 , and D9=0 if inf-1 ≤0
Prob.
t-Statistic
Std. Error
Coefficient
0.179985
R-squared 0.3812
0.890719
8.020281
7.143820
C
539.4545
SSR
0.2188
1.260287
0.379002
0.477651
INF
0.8102
-0.242630
6.692036
-1.623690 D9(INF9-9)
0.2737
1.118158
0.171522
0.191788
POP
0.2268
-1.237872
0.357548
-0.442599 INV
Figure (2):The Relationship Between the Sum square Error (SSR) and Inflation Levels
(K)
Figure (3):The Relationship Between the coefficient of determination (R2) and Inflation
Levels (K)
R-squared
0.188
0.186
0.184
0.182
0.18
R-squared
0.178
0.176
0.174
0.172
1
2
3
4
5
6
7
8
9
Acknowledgements
Thanks and appreciation is given to King Abulaziz City for Science and Technology for
funding this research as part of the project No SS-11-3 titled “The Phenomenon Study
High Prices of Essential Goods in Saudi Arabia”.
References
Christoffersen, P. and Doyle, P., (1998), “From Inflation to Growth. Eight Years of
Transition”, IMF Working Paper No. WP/98/100
Dickey, D. and W. Fuller, (1981), “Likelihood Ratio Statistics for Autoregressive Time
Series with a Unit Root,” Econometrica, Vol. 49
Drukker, D., Gomis-Porqueras, P. and Hernandez-Verme, P., (2005), “Threshold effects
in the relationship between inflation and growth: A new panel-data approach”.
Proceedings of the 11th International Conference on Panel Data, Feb. 9.
http://www.uh.edu/~cmurray/TCE/papers/Drukker.pdf
Espinoza Raphael, Leon Hyginus and Prasad Ananthakrishnan, (2010), “Estimating The
Inflation-Growth Nexus-A Smooth Transition Model” IMF Working Paper, WP/10/76
Fabayo, J.A. and Ajilore O.T., (2006), “Inflation-how much is too much for economic
growth
in
Nigeria”.
Ind.
Econ.
Rev.,
41:
129-148.
http://ideas.repec.org/a/dse/indecr/v41y2006i2p129 -147.html
Feldstein, M., (1982), “Inflation tax rules and investment: Some econometric evidence”.
Econometrica, 50: 825-62. http://www.jstor.org/pss/1912766
Frimpong Joseph Magnus and Oteng-Abayie Eric Fosu, (2010), “When is Inflation
Harmful? Estimating the Threshold Effect for Ghana” American Journal of Economics
and Business Administration 2 (3): 225-232
Gujarati N. Domador, and Porter C. Dawn, (2009), “Basic Econometrics”, The McGrawHill, New York, USA
Hussain, M., (2005), “Inflation and Growth: Estimation of Threshold Point for
Pakistan”.Pakistan Business Review, October, pp. 1-15
Khan, M. and Senhadji A., (2001), “Threshold effects in the relationship between
inflation
and
growth”.
IMF
Staff
Papers,
48:
1-21.
http://ideas.repec.org/a/pal/imfstp/v48y2001i1p1.html
Kremer S., A. Bick and D. Nautz, (2009), “Inflation and Growth: New Evidence From a
Dynamic Panel. Threshold Analysis”. SFB 649 Discussion Paper. 2009-036.
http://sfb649.wiwi.hu-berlin.de/papers/
Li Min (2006), “Inflation and Economic Growth: Threshold Effects and Transmission
Mechanisms” Department of Economics, University of Alberta, 8-14, HM Tory Building,
Edmonton, Alberta, Canada, T6G 2H4
Mubarik Ali Yasir, (2005), “Inflation and Growth: An Estimate of the Threshold Level of
Inflation in Pakistan” SBP-Research Bulletin. Volume 1, Number 1
Munir Qaiser and Mansur Kasim, (2009), “Non-Linearity between Inflation Rate and
GDP Growth in Malaysia” Economics Bulletin, Volume 29, Issue 3
Nasir Iqbal and Nawaz Saima, (2010), “Investment, Inflation and Economic Growth
Nexus” Pakistan Institute of Development Economics Islamabad, Pakistan. 21
Ocran, M.K., (2007), “A Modeling of Ghana’s Inflation Experience: 1960-2003”. AERC
Research Paper No. 169. African Economic Research Consortium, Nairobi;
www.aercafrica.org/documents/rp169.pdf
Sarel, M., (1996), “Nonlinear effects of inflation on economic growth”. IMF Staff Papers,
43: 199-215. http://papers.ssrn.com/sol3/papers.cfm?abstract_id =883204
Sargsyan, G.R., (2005), “Inflation and output in Armenia: The threshold effect revisited”.
Preceding of the 3rd International AIPRG conference on Armenia, Jan. 15-16, World
Bank, Washington, DC. http://www.aiprg.net/UserFiles/File/jan-2005/grigorsargsyan.pdf
Sergii Pypko, (2009), “Inflation and economic growth: The non-linear relationship.
Evidence from CIS countries” Kyiv School of Economics
Shamim Ahmed and Mortaza Golam, (2005), “Inflation and Economic Growth in
Bangladesh: 1981-2005”, Policy Analysis Unit, Research Department, Bangladesh
Bank, Working Paper Series: WP 0604
Sidrauski, M., (1967), “Inflation and economic growth”. J. Political Econ., 75: 796-810.
http://www.jstor.org/stable/1829572
Stockman, Alan, (1981), “Anticipated Inflation and Capital Stock in A Cash-in-Advance
Economy.” Journal of Monetary Economics 8:387–93
Sweidan, Osama D., (2004), “Does inflation harm economic growth in Jordan? An
econometric analysis for the Period 1970-2000“. International Journal of Applied
Econometrics and Quantitative Studies. Vol.1-2