A CONTRIBUTION TO THE ANALYSIS OF THE ECONOMIC GROWTH OF QATAR EL-MEFLEH, Muhannad A.*
SHOTAR, Manhal M.
Abstract
This paper delineates the theoretical structure of the factors that determine economic growth in Qatar. The focal point of this paper is identifying the role of major macroeconomic variables that determine growth, namely; government spending, institutional settings, money supply, investment, inflation, education and the degree of economic openness. The major findings of this paper are that the empirical evidence indicates that the (1) various shocks explain different proportions of GDP movements over time, (2) GDP seems to be more susceptible to government spending and economic risk shocks than to other variables, and (3) education, investment, and monetary policy (general price level) shocks seem to have a moderate impact on GDP movements over the entire time horizon. Also, there was little evidence that the rest of the variables have an impact on economic growth.
JEL Classification: F41, F43, E52
Key Words: Economic Growth, Economic Openness, Government Spending.
1. Introduction
Qatar is a small, open, well monetized economy with no interest rate ceilings on deposits, and where market forces determine the interest rates. It does not have a demographic trap, poverty trap, or a savings trap like some of the other developing countries. Since the mid 1990s, the continuous efforts by policy makers to diversify revenues, control public expenditures, and privatization have led to the improvement of productivity and enhanced long-term economic growth. Qatar's real Gross Domestic Product (GDP) has been growing at high rates of almost 6% during the last 10 years. The inflation rate is relatively low even when compared to the average rate of inflation for the industrialized countries1. In recent years, some developments have taken place which have led to more effective fiscal policy, created a more favorable business and economic environment, and enhanced the role of the private sector2. Despite the increase in oil prices and revenues, economic reforms have continued to be top priority for the decision- makers. Meanwhile, other measures have taken place to build up a comprehensive legal and economic system which is attractive to foreign investment and consistent with a free market and outward-oriented Qatar economy. In 1990s, the government of Qatar started to amend the legislative and bureaucratic framework to ensure easy and adequate inflow of foreign capital. Law No. 25 of 1990 allowed non-Qatari capital to participate in a wide range of economic activities that were Qatari exclusive. In 2000, the Qatari government amended the laws that govern the legal and economic environment, thus allowing foreign
* Muhannad A. El-Mefleh, Ph.D, American River College, Sacramento, CA, USA, e-mail:
[email protected], Manhal M. Shotar, Ph.D, Senior Finance Economist. Advisor to Financial Management Reform/Ministry of Finance, German Technical Cooperation (GTZ), Amman, Jordan.
investors to exercise 100% ownership in any project. The exception to this is banking, insurance, and general trading where 51% Qatari partnership is still required. Also, the government introduced intellectual property right laws and reduced tariffs to comply with the World Trade Organization (WTO) standards. The rest of the paper is structured as follows: Section one provides a theoretical background and a review of the relevant literature. Section two provides the sources of the data set. Section three discusses the methodology and the empirical approach which is based on Vector Autoregressive (VAR) techniques. Section four reports test results and analysis. Section five concludes the paper.
2. Theoretical framework
There are two types of economic growth models. One type is based on the Solow (1956) growth model and the other type is based on the Romer (1986) growth model.
Solow type models rely on capital accumulation where population growth and technological progress are exogenous. Therefore, if population growth and technological progress are identical in different market economies, then in the long run under Solow type models these economies will reach the same rate of growth. So long-term growth according to Solow type models is not influenced by policy; policy makers have no influence on the outcome. A steady state, where the change in capital-labor ratio is zero and the level of output and capital stock are increasing at the same rate as population growth, would produce the same level of per capita income per worker. Therefore, the long run growth rate of the economy would be equal to the combined growth rate of labor force and technological progress.
Growth rate is impacted by savings rate where high savings lead to accumulation of capital, an increase in the productivity of workers, and an increase in the level of GDP.
Solow’s model implies that the rate of growth varies between countries due to the distance of each country from the steady state. Thus, underdeveloped economies would grow faster than developed economies and the per capita income will eventually converge. The Romer model (1986) emphasizes that policies and incentives can explain the difference in long-run growth rates across countries. Inventions are not exogenous and have positive externalities which reduce the cost of future innovations.
Thus, education plays an important role not only for innovation but also in determining long-term growth. Schumpeter (1950) and Romer (1990) argued that motivation for profit, and not intellectual inquiry, is the major reason for innovations. So, technological changes are endogenous factors and not exogenous. Therefore, growth is related to the policies and the institutional setting of a given economy rather than on natural endowment. If one accepts the endogenous factors as the reason for growth, then growth is not correlated to per capita income per worker. Every innovation and new product adds to human knowledge.
Also, the faster the technological progress is, the larger the accumulation of human knowledge and the lower the cost of innovation. Thus, the law of diminishing returns on capital given labor as a constant is not an acceptable assumption. Based on the endogenous growth type models, per capita income per worker would grow faster in
countries with relatively educated populations that have more capital stock per worker and have institutional settings that favor accumulation of human knowledge. Knowledge applications may be excludable without the permission of the inventor, but knowledge itself is not excludable. In addition, knowledge outlives any individual while human capital vanishes with the death of the individual. Institutional settings include the competitive structure of the economy, political stability, government efficiency, and the degree of economic openness, all of which influence innovation and growth. Endogenous growth type models show that a country with plenty of physical capital and even more so human capital would continue to grow faster than a country with less of these resources.
Long-term economic growth is a function of investment in human capital, political stability, well-defined property rights, physical investment, low trade barriers, and low government spending on consumption. Empirical estimations of a positive relationship between growth and an educated labor force were provided by Barro (1991), Mankiw, Romer, and Weil (1992). Political stability, well-defined property rights, and a stable government policy toward private investment would increase investment and economic growth. Ruhashynkiko (2005) showed that the higher the government spending on consumption as a percentage of GDP, the lower the growth rate. Gould and Ruffin (1993) assert that an economy that is more open to international trade and has high human capital would experience faster economic growth than a less open economy.
Physical capital in the form of equipment would continue to be essential for economic growth. Machinery increases marginal productivity of labor, transforms production modes of society, and consequently increases the GDP and the growth rate. Romer (1986) presented his endogenous growth model where human capital as a factor of input led to an increase in the marginal productivity of labor and an increased growth rate over time.
Also, he demonstrated that large countries could achieve higher growth rates than small countries. However, under the Romer type model, long-term growth is essentially dependent on the endogenous accumulation of knowledge and an increased return assumption. Accumulation of human knowledge is dependent on the amount of investment in research. Therefore, there is no reason to believe that per capita income across countries will converge rather than diverge over time. Lack of human capital development may lead to no growth or low rates of growth in the long run.
Romer (1990) showed that market size, and not population size, had a positive effect on research and consequently growth. Growth is dependent on human capital and not population. Romer made three basic assumptions in developing his model. These assumptions are positive externalities of new knowledge, decreasing return in producing new knowledge at a given time, increasing return on human capital and decreasing return on physical capital. A positive outcome of combined increasing return on human capital and decreasing return on physical capital leads to an increasing marginal productivity of capital-labor ratio. Government can create the incentives for the private sector to become an engine of economic growth. These incentives include reasonable regulations, friendly policies toward capital, streamlining the rules that govern the establishment of new business, providing useful and more accurate data to make better investment decisions, promoting responsible corporate governance, open dialog with the private sector, and
targeting support for small and medium sized enterprises. Economic capacities are built, acquired and endowed. They are built in the form of institutional settings, physical capital, and social capital. Economic capacities are acquired by investing in research and human capital to generate knowledge and new ideas. Economic capacities are endowed with accessible natural resources, arable land, and labor. These economic capacities are seldom fully utilized, if ever, in any economy. For the purpose of this study, the following model is used:
GDP= f (MM, P, I, OPEN, S, G, R)
Where: GDP is real Gross Domestic Product growth rate, MM: M2/GDP ratio, P:
inflation rate, I: Gross growth of capital formation measures investment, S: Percentage of government spending on education, OPEN is the ratio of exports and imports to GDP, G:
(Government consumption)/GDP reflects government size (See final note 1)1, R:
Institutional quality as reflected in the International Country Risk Guide (final note 2)2, The ratio of money supply to GDP is a measure of financial depth. Inflation rate reflects macroeconomic instability and the kind of monetary policy the monetary authority is using. The gross growth of capital formation measures investment. The ratio of exports and imports to GDP is an indicator of economic openness. Government spending/GDP reflects government size. Institutional quality is reflected in the International Country Risk Guide (ICRG) of Political Risk Group (PRG) index that evaluates a country’s policy and institutional framework.
The economic growth of a given economy is impacted by its institutional settings.
Long-term democracy increases government incentives to implement sound economic policies and increase economic growth (see El-Mefleh 2005). However, democracy may increase the tendency to divert public resources toward consumption and away from investment. Empirical research does not help in settling the above two contradictory views. Both views lack support of a strong theoretical and empirical foundation to support either view. Plumper and Martin (2003) argued that high growth may not be achieved under a system where political participation is very limited. An autocratic government tends to choose tax structure, spending choices, and transfer payments programs to ensure political support of the majority of the elite in that society. A high growth rate could be achieved under a political system that is characterized by wider political participation where providing public goods is the only viable option for ensuring political survival. With wide political participation, the transfer payments programs, tax structure, and the government spending would target an increase in the public investment in collective goods.
2. Data
The sample period corresponds to the years 1984-2004. Data on GDP, P, G, S, I and OPEN are expressed in million dollars and were obtained from the Gulf Organization and Industrial Cooperation (GOIC) and the United Nations’ Statistics Division. While data on MM were obtained from the Department of Research and Statistics, Qatari Monetary Agency, various issues of the Quarterly Statistical Bulletin, as well as the Department of Economic Policies, the Qatar Central Bank, and various issues of Quarterly Statistical
Bulletin. Finally, data on R were obtained from the CountryData.com by the PRS Group.
Figure 1 shows the rate of growth and risk rating (data in table A1 in the Annex)
Figure 1. Rate of growth of real Gdp and Economic Risk Rating in Qatar, 1984-2004
-10 0 10 20 30 40 50
84 86 88 90 92 94 96 98 00 02 04 Rate of growth of Gdp
Economic Risk Rating
3. Methodology and empirical results
3.1- VAR Analysis :
The Granger causality test allows us to examine two variables at a time. While, the use of vector autoregressive (VAR) technique which enables us to handle more than a pair of variables. We tested for unit roots and stationarity. Results are presented in Table (1). The Augmented Dickey Fuller (ADF) test statistics indicates that the presence of a unit root in gross domestic product, government spending, money supply, the degree of openness and economic risk cannot be rejected at the conventional level of significance.
Table 1. The ADF test statistics in level and in first difference Variables ADF
Level
ADF First Diff
CV 5% Variables ADF Level
ADF First Diff
CV 5%
GDP -2.98 -5.42 -3.03 G -0.14 -3.83 -3.03
MM -2.58 -3.12 -1.96 S -2.46 -4.35 -3.03
I -20.6 - -3.03 Open -1.99 -3.23 -3.03
P -4.0 - -3.03 R -1.37 -2.45 -1.993
3.2- Variance Decomposition:
As the results of the ADF test suggest, we model the variables in their first difference.
Before determining the dynamic specification of our model, the lag length should be set.
A simple procedure is followed. Since the error terms should be uncorrelated, k should be long enough to guarantee that. But in this case, we need to in vestigate the VAR model, i.e., interpret the short run dynamics and the speed of adjustment. Thus we can not allow for a large k that would exhaust the degrees of freedom and the economic interpretation would be fruitless. The diagnostic tests indicate that one lag is appropriate for the
residuals to approximate white noise. Table (2) reports the variance decomposition for the GDP.
The results of the variance decomposition of the GDP indicate that various shocks explain different proportions of GDP movements over time. That is, GDP seems to be more susceptible to government spending and economic risk shocks than to other variables. Moreover, there is a negligible impact of investment on growth, especially in the first two years. Investment, the general price level, as well as education shocks seem to have a moderate impact on GDP movements over the entire time horizon. An interesting aspect of these results is that economic openness (OPEN) has a little effect on gross domestic product. This could be attributed to some extent to the economic diversifications that the country is embarking on which have the country insolated from fluctuations in the oil prices.
Table 2: VDC test results
Horizon GDP G P OPEN R I S MM
1 100 00 00 00 00 00 00 00
4 83.3 8.77 1.92 0.25 1.97 1.23 1.12 1.35 8 79.8 8.3 2.12 0.73 4.4 1.37 1.31 1.37 3.3- Impulse Response Function:
Figure A1 in the Annex shows the response of the GDP to one standard deviation shock to investment, itself, government spending, education spendin g, the general price level, economic risk, money supply and the degree of openness. A positive shock in the GDP increases the GDP until it reaches its maximum after three years, beyond which the effect starts to die out. Moreover, a positive shock in OPEN increases GDP until it reaches its maximum after two years, and then the effect turns negative in the fourth period.
Thereafter, the effect decreases the GDP but, it seems that the shock impact dies out. The impact of education is very similar to that of the degree of openness, the only difference is the fourth period where OPEN is negative. On the other hand, a positive shock in government spending decreases the GDP starting with the first period. It reaches its maximum after two years, beyond which the impact turns positive and then the effect starts to die out. After that, G reaches its long-run level. A positive shock in investment decreases the GDP until it reaches its maximum after three years, and then the effect turns positive at period four. Thereafter, the effect increases the GDP up to the ninth period.
The impact of the shock does not seem to diminish over time. While a positive shock in economic risk decreases the GDP until it reaches its maximum after two years, the shock impact continues to be negative for a long time. Thus, the effect decreases the GDP up to the fifth period and dies out after that. Money supply shock has the strongest negative impact but it weakens immediately after the second period. Finally, the general price level shock decreases the GDP at first but in the third period the shock impact dies out.
4. Conclusion
The growth rate of the Qatari economy is influenced strongly and negatively by government consumption, but only moderately and negatively by expansionary monetary
policy shocks. Investment has a positive impact on the long-run growth rate while institutional setting seems to have a negligible impact on growth. Finally, spending on education has a positive impact on growth rate. Other aspects of the economic growth of Qatar would be worth investigating in depth in terms of their impact on women, industrial clustering, environmental regulations, and financial instability. Also, building a forecasting model for growth would be helpful for decision-makers.
References
Barro, Robert J. (1991). “Economic Growth in a Cross section of Countries.” The Quarterly Journal of Economics 106, May 1991, Pp.407-443.
Chatterjee, S., and Ali S. Hadi (1988) Sensitivity Analysis in Linear Regression (New York: John Wiley and Sons).
El-Mefleh, Muhannad (May 2005). “The Impact of Corruption on Investment in Jordan.” Global Trends, International Business Association Conference Proceedings, Pp.34-40.
Gould, David M. and Roy J. Ruffin (1993). “What Determines Economic Growth?” Economic Review – Federal Reserve Bank of Dallas; Second quarter 1993; ABI/INFORM Global, Pp. 25-40.
Mankiw, N. Gregory, David Romer, and David N. Weil (1992). “A Contribution to the Empirics of Economic Growth.” The Quarterly Journal of Economics 107, May 1992, Pp. 407-437.
Pindyck, R.S. and D.C. Rubinfeld (1981) Econometric Models and Economic Forecasts, Second ed. (New York: McGraw-Hill).
Plumper, Thomas and Christian W. Martin (2003). “Democracy, Government Spending, and Economic Growth: A Political-Economic Explanation of the Barro-effect.” Political choice;
October 2003; 117, 1-2; ABI/INFORM Global, Pp. 27-50.
Romer, Paul M. (1990). “Endogenous Technological Change.” Journal of Political Economy, 1990, Vol. 98, No.5, Pp. S71-S102.
Romer, Paul M. (1986). “Increasing returns and Long-Run Growth.” Journal of Political Economy, 1986, Vol. 94, No.5, Pp. 1002-1037.
Ruhashyankiko, Jean-Francois (2005). “Why Do Some Countries Manage to Extract Growth from Foreign Aid?” International Monetary Fund Working paper, WP/05/53, March 2005.
Schumpeter, Joseph A. (1950). “Capitalism, Socialism, and Democracy.” Third edition. (New York: Harper and Brothers).
Shotar, Manhal (2005). “The Attractiveness of Qatar to Foreign Direct Investment.” Journal of Applied Econometrics and International Development. Vol. 5 No. 3, Pp. 117-132.
Solow, Robert M. (1956). “A Contribution to the Theory of Economic Growth.” Quarterly Journal of Economics, LXX (1956), Pp. 65-94.
Summers, Robert, and Alan Heston (1988). “A New set of international Comparisons of Real Product and Price Levels Estimates for 130 Countries, 1950-1985.” Review of Income and Wealth, XXXIV (1988), Pp. 1-26.
1 Spending on education is not included.
2 Economic Risk Rating: A means of assessing a country's current economic strengths and weaknesses. In general, where strengths outweigh weaknesses, a country will show low risk and where weaknesses outweigh strengths, the economic risk will be high. To ensure comparability between countries, risk components are based on accepted ratios between the measured data within the national economic/financial structure, and then the ratios are compared, not the data. Risk points are assessed for each of the component factors of GDP per head of population, real annual GDP growth, annual inflation rate, budget balance as a percentage of GDP, and current account balance as a percentage of GDP. Risk ratings range from a high of 50 (least risk) to a low of 0 (highest risk), though lowest de facto ratings are generally near 15.
3 No trend no intercepts.
Appendix
Table A1. Real GDP growh and Risk rating Year Real GDP Growth Economic Risk Rating
1984 -0.0357 35.5
1985 -0.0032 35.0
1986 0.0283 32.5
1987 -0.0224 35.0
1988 0.0366 38.0
1989 0.0468 36.5
1990 0.0526 35.9
1991 0.0267 41.7
1992 -0.0079 41.1
1993 0.0970 41.8
1994 -0.0006 39.7
1995 0.0235 34.4
1996 0.0294 36.1
1997 0.0482 34.8
1998 0.2404 29.2
1999 0.0841 28.2
2000 0.0319 34.5
2001 0.0732 36.5
2002 0.0630 43.0
2003 0.0734 47.5
2004 0.0330 47.5
-0.02 0.00 0.02 0.04 0.06
1 2 3 4 5 6 7 8 9 10
GDP S G
R I MM
OPEN P
Figure (1): Response of GDP to One S.D. Innovations
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