A. Introduction

8. Since its independence, Pakistan has experienced economic growth rates of about 5 percent per year on average. While growth has been considerably stronger in Pakistan than in many other low- and middle-income countries and has been comparable to that of other South Asian countries, it has been significantly below the growth rates experienced by countries in South-East Asia, such as Malaysia, Singapore, and Thailand. This chapter tries to explain these differences by investigating which factors determine growth. More specifically, this chapter explores whether investing in human capital can help to achieve higher rates of economic growth. Besides more traditional factors, such as investment levels, differences in the quality of human capital may be a factor that can help to explain the differences in growth rates between Pakistan and the countries in South-East Asia.

9. Finding a link between investing in human capital and economic growth matters for an additional reason. A large part of the world’s population continues to live in poverty, and the focus of economic researchers and policy makers, including in institutions such as the Fund, has increasingly shifted toward finding policies that benefit the poor. It is generally agreed that economic growth is necessary to help reduce poverty, but that growth by itself is not sufficient. Pakistan may be a good example of this, as despite the relatively high growth rates, its social development is weak and poverty remains widespread, with about an estimated 30 percent of the population regarded as poor. Investing in human capital may lead to higher future growth and incomes, by creating a more productive work force. But higher social spending can also benefit the poor directly, by improving their current living conditions through better health care and education.

10. Section B of this chapter reviews selectively the recent literature on economic growth, including findings regarding the importance of the quality of human capital. Section C presents the results of an econometric analysis of growth in a group of low- and middle-income countries during 1980-2002, adding a number of health and education indicators to more conventional factors explaining growth, such as macroeconomic policies, initial income levels, and institutional quality. Section D describes how Pakistan performed relative to the overall sample, and to countries in South and South-East Asia, in particular. Based on the results, it also offers suggestions as to how Pakistan could achieve higher rates of economic growth. Finally, Section E concludes.

B. A Review of Recent Growth Literature

11. A vast and growing body of literature attempts to answer the question of how to promote growth. But for almost any study that finds a particular factor important for growth, another study can be found that reaches an opposite conclusion. Still, there appears to be a broad consensus regarding a number of “stylized facts.” Sala-i-Martin, 2004, offers a broad summary of the literature on cross-country growth analysis. He notes that (a) there is no simple determinant of growth; (b) the initial level of income is the most important and robust variable (and thus conditional convergence is the most robust empirical fact); (c) the size of the government does not appear to matter much, but what is important is the quality of government and its policies; (d) the relationship between human capital and growth is weak, although some measures of health (such as life expectancy) are robustly correlated with growth; (e) more open economies tend to grow faster; and (f) institutions are important for growth.

12. Similarly, studies that use a growth accounting approach in analyzing cross-country differences in economic growth, for example Bosworth and Collins, 2003, and Abed and Davoodi, 2004, find that the increase in production factors alone cannot explain economic growth. Or, as Easterly, 2001a, and Easterly and Levine, 2001, put it, it’s the “A” in the standard production function Y_t = A_t f (K_t, L_t) that is key to growth, where Y is output, K the capital stock, and L the quantity of labor. A is generally defined as total factor productivity. A substantial part of the differences in growth is accounted for by differences in total factor productivity. An increase in total factor productivity can be thought of as an outward shift in the production function, that is, growth results from dynamically increasing returns to scale.

13. The question that follows is what drives changes in total factor productivity? Total factor productivity in effect provides a measure of gains in economic efficiency: the quantity of output that can be produced with a given quantity of inputs. Changes in total factor productivity reflect a myriad of determinants that influence growth, but which the measured increases in factor inputs do not account for. Total factor productivity should not be taken as a mere indicator of technical progress. Policies and institutions, for example, also affect the efficiency of an economy in much of the same way as technology does. An economy with stable economic conditions or good institutions is more efficient in the sense that it takes less input to produce the same amount of output. Macroeconomic instability or weak institutions on the other hand lower incentives to invest (in physical and human capital, as well as technology), to work, and to produce. Empirically, it is becoming increasingly clear that good policies and institutions are important determinants of growth.

14. Beaugrand, 2004, follows Schumpeter in emphasizing the entrepreneur as the mainspring of economic evolution. Entrepreneurship is the prime force behind outward shifts of the production function. While no poor country has a large class of successful entrepreneurs, most countries are likely to have a large pool of potential entrepreneurs, who may be precluded from fulfilling their function because of unfavorable conditions. The issue then becomes how governments in poor countries can unleash entrepreneurial spirits and thus promote economic development.

15. Beaugrand lists seven key steps to promote entrepreneurship and growth. These include (a) peace and stability: establish a credible political system that ensures legitimacy and continuity; (b) governance and the rule of law: maintain law and order, enforce property rights, promote accountability, weed out corruption, and set up a credible judiciary system; (c) mentality: muster support for economic and social reforms; (d) economic incentives: adopt sound economic policies, including hard budget constraints, allowing competition, while creating a level playing field; (e) basic infrastructure: ensure the provision of basic public services; (f) access to capital: develop an efficient financial intermediation system, mobilize external savings; and (g) education: build up human capital, raise literacy, and gain access to up-to-date knowledge. Beaugrand notes that no single step is likely to prove sufficient and not all may be necessary, but minimum standards and a critical mass are required to spur a genuine economic takeoff. The international financial institutions typically focus on only three out of these seven elements (the fourth, fifth, and sixth). Yet, as noted above, it has become empirically clear that sound economic policies and increased investment are far from sufficient to achieve economic growth and that one of the most important steps toward economic growth is to ensure good governance and to establish the rule of law.

16. Empirical studies aiming to find a link between increases in the level of education—or more broadly, increases in the quality of human capital—and economic growth are relatively recent. Higher educational attainment could have an impact on economic growth by improving the productivity of workers. An educated workforce is better able to implement new technologies and generate ideas for improving efficiency. But while at the microeconomic level studies have typically found a strong relationship between income and educational attainment, macroeconomic studies so far have found conflicting results. Early studies, including those of Mankiw, Romer, and Weil, 1992, and Barro and Sala-i-Martin, 1995, found a significant positive association between cross-country differences in the initial level of education and subsequent rates of growth. However, later studies,² including those of Bils and Klenow, 2000, Pritchett, 2001, Easterly and Levine, 2001, and Temple, 2001, that examined the relationship between years of schooling and changes in economic growth failed to find a significant association. Bosworth and Collins, 2003, also fail to find a robust link between educational quality and growth and particularly cannot distinguish educational quality from more general concepts of the quality of government institutions. Some researchers suggest that the link between education and growth may be weak because the benefits of education are not fully realized due to a failure to integrate improvements in education with other important elements of the growth process. That is, the creation of skills offers no benefits if the infrastructure and institutions do not make use of them.

C. Empirical Analysis

17. The use of an empirical model can help to determine the factors that are important for growth. But it should be stressed that growth regressions clearly have their limitations, particularly as often the parameter estimates have proven unstable. Examining the characteristics and determinants of economic growth therefore requires an empirical framework that can be applied to large groups of countries over a sufficiently long period. Still, as a great many researchers have regressed various indicators of output on a vast array of potential determinants, a core set of explanatory variables has emerged that has been shown to be consistently associated with economic growth. The importance of other variables should be examined conditional on inclusion of this core set in the specification.

18. The basis for the analysis in this paper is a production function of the form:

where Y is the level of output, K is capital input, L is labor input, H is a measure of educational attainment or, more generally, the quality of human capital used to adjust the work force for quality change. This can be rewritten in a form that decomposes output per worker into the contributions of increases in capital per worker, increases in education per worker, and improvements in total factor productivity:

By assuming a steady-state constant value y for the inverse of the capital-output ratio and with 8 representing the rate of depreciation, the investment rate i = I/Y can be used instead of the change in the capital stock:

The use of the investment ratio has the obvious advantage in that it avoids measurement problems associated with constructing a series for (changes in) the capital stock. With this, economic growth is a function of investment, the quality of human capital, and a set of determinants driving total factor productivity.

19. A number of different measures are used here to represent the quality of human capital. These include literacy rates, average years of schooling, gross secondary school enrollment, the share of the population that has completed secondary schooling, life expectancy, and per capita health expenditure. Variables that determine total factor productivity include the rate of inflation as a proxy for sound economic policies, and the overall quality of institutions. In addition, given the importance of convergence (that is, whether incomes of developing countries are converging toward those of higher-income countries) the initial level of income has been included. Thus, the basic regression takes the form:

20. Data for real per capita GDP growth, gross fixed capital formation, CPI inflation, and per capita income in 1980 were obtained from the Fund’s World Economic Outlook database. Data for gross secondary school enrollment, adult literacy rate, life expectancy, and per capita health expenditure were obtained from the World Bank’s World Development Indicators database. Data for average years of schooling were taken from Barro and Lee, 2000. Representing institutional quality, the average of four indicators compiled by the International Country Risk Guide was used. These indicators were rescaled to range from 1–12, and covered bureaucratic quality, corruption, rule of law, and government stability.

21. Table II.1 presents the results of the estimation of a cross-section regression of equation (4) for a sample of 72 low- and middle-income countries, using ordinary least squares (OLS).³ The dependent variable is average real per capita GDP growth over the 1980-2002 period. The explanatory variables are also averages over the 1980-2002 period, except for the initial income variable, which reflects income levels in 1980.

Table II.1.

Regression Results

Notes: Estimation is by OLS. T-statistics in parentheses. A * denotes significance at the 10 percent level and ** denotes significance at the 5 percent level.

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

Table II.1.

Regression Results

	(1)		(2)		(3)		(4)		(5)		(6)		(7)
Dependent variable: average growth of real per capita GDP, 1980-2002
Investment ratio (percent of GDP)	0.16		0.17		0.19		0.14		0.14		0.19		0.16
	(4.71)	**	(4.52)	**	(4.53)	**	(3.60)	**	(4.10)	**	(5.17)	**	(4.70)	**
Initial income (1980 U.S. dollars, logs)	-1.16		-1.07		-1.03		-1.51		-1.47		-1.31		-1.3
	(-7.54)	**	(-7.33)	**	(-6.22)	**	(-8.39)	**	(-7.84)	**	(-7.13)	**	(-7.14)	**
Inflation (percent)	-0.002		-0.002		-0.002		-0.002		-0.002		-0.002		-0.002
	(-3.94)	**	(-3.77)	**	(-3.56)	**	(-3.20)	**	(-3.93)	**	(-3.68)	**	(-4.54)	**
Institutional quality 1/	0.64		0.55		0.49		0.55		0.63		0.49		0.58
	(4.27)	**	(3.53)	**	(2.79)	**	(3.72)	**	(4.22)	**	(3.29)	**	(3.85)	**
Average years of schooling	0.37								0.26				0.24
	(3.83)	**							(2.39)	**			(2.03)	**
School enrollment, secondary			0.03
(percent gross)			(3.48)	**
Literacy rate					0.02
(adult total, percent of people ages 15 and above)					(2.12)	**
Life expectancy at birth (years)							0.09		0.05
							(4.02)	**	(2.34)	**
Health expenditure per capita											0.72		0.45
(current U.S. dolalrs, logs)											(4.13)	**	(1.95)	*
R-squared	0.65		0.63		0.63		0.65		0.68		0.65		0.68
Adjusted R-squared	0.62		0.61		0.60		0.63		0.65		0.63		0.65
No. observations	64		67		59		67		64		66		63

Notes: Estimation is by OLS. T-statistics in parentheses. A * denotes significance at the 10 percent level and ** denotes significance at the 5 percent level.

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

View Table

Table II.1.

Regression Results

	(1)		(2)		(3)		(4)		(5)		(6)		(7)
Dependent variable: average growth of real per capita GDP, 1980-2002
Investment ratio (percent of GDP)	0.16		0.17		0.19		0.14		0.14		0.19		0.16
	(4.71)	**	(4.52)	**	(4.53)	**	(3.60)	**	(4.10)	**	(5.17)	**	(4.70)	**
Initial income (1980 U.S. dollars, logs)	-1.16		-1.07		-1.03		-1.51		-1.47		-1.31		-1.3
	(-7.54)	**	(-7.33)	**	(-6.22)	**	(-8.39)	**	(-7.84)	**	(-7.13)	**	(-7.14)	**
Inflation (percent)	-0.002		-0.002		-0.002		-0.002		-0.002		-0.002		-0.002
	(-3.94)	**	(-3.77)	**	(-3.56)	**	(-3.20)	**	(-3.93)	**	(-3.68)	**	(-4.54)	**
Institutional quality 1/	0.64		0.55		0.49		0.55		0.63		0.49		0.58
	(4.27)	**	(3.53)	**	(2.79)	**	(3.72)	**	(4.22)	**	(3.29)	**	(3.85)	**
Average years of schooling	0.37								0.26				0.24
	(3.83)	**							(2.39)	**			(2.03)	**
School enrollment, secondary			0.03
(percent gross)			(3.48)	**
Literacy rate					0.02
(adult total, percent of people ages 15 and above)					(2.12)	**
Life expectancy at birth (years)							0.09		0.05
							(4.02)	**	(2.34)	**
Health expenditure per capita											0.72		0.45
(current U.S. dolalrs, logs)											(4.13)	**	(1.95)	*
R-squared	0.65		0.63		0.63		0.65		0.68		0.65		0.68
Adjusted R-squared	0.62		0.61		0.60		0.63		0.65		0.63		0.65
No. observations	64		67		59		67		64		66		63

Notes: Estimation is by OLS. T-statistics in parentheses. A * denotes significance at the 10 percent level and ** denotes significance at the 5 percent level.

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

22. Table II.1 shows that the variables used to describe economic growth account for almost two-thirds of the cross-country variation in growth over the period 1980-2002. Inclusion of the investment rate results in a statistically significant coefficient, supporting the idea that it is a good proxy for the capital contribution. All of the conditioning variables—initial income, the rate of inflation, and the quality of institutions—have the expected signs and are highly significant. Multicollinearity does not seem to pose a problem, given the significance of each of the explanatory variables. The finding of a strong negative association between initial income and subsequent growth provides a robust support for a process of conditional convergence. There is also a strong correlation between growth and sound economic policies and between growth and the quality of governing institutions, such as law and order, protection of property rights, and the absence of corruption. Moreover, the results in Table II.1 confirm that a higher quality of human capital—that is, higher levels of educational attainment or better health indicators—is indeed associated with higher real per capita growth rates. The coefficients for each of the education and health indicators used have the expected sign and are highly significant. Interestingly, the relevance of the human capital indicators is independent of the overall institutional quality. Equations 5 and 7 in Table II.1 furthermore indicate that both education and health indicators influence growth independently of each other.

23. To gauge the relative importance of the various determinants of growth, Table II.2 shows the standardized coefficients of the equations shown in Table II.1.⁴ These standardized coefficients suggest that raising investment has the biggest impact on growth, but that improving a populations health also has a considerable effect. Improving institutions and levels of educational attainment have a somewhat smaller, but still significant impact on growth.

Table II.2.

Standardized Coefficients

Notes: Standardized coefficients calculated by standardizing timeseries as follows: (Y-MEAN(Y))/STDEV(Y).

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

Table II.2.

Standardized Coefficients

(1)	(2)	(3)	(4)	(5)	(6)	(7)
Dependent variable: average growth of real per capita GDP, 1980-2002
Investment ratio (percent of GDP)	0.49	0.46	0.54	0.44	0.43	0.49	0.44
Initial income (1980 U.S. dollars, logs)	-0.59	-0.61	-0.54	-0.64	-0.66	-0.90	-0.88
Inflation (percent)	-0.21	-0.23	-0.21	-0.23	-0.23	-0.24	-0.24
Institutional quality 1/	0.42	0.35	0.32	0.37	0.41	0.31	0.36
Average years of schooling	0.37				0.17		0.26
School enrollment, secondary (percent gross)		0.42
Literacy rate (adult total, percent of people ages 15 and above)			0.22
Life expectancy at birth (years)				0.49	0.34
Health expenditures per capita (current U.S. dollars, logs)						0.70	0.48

Notes: Standardized coefficients calculated by standardizing timeseries as follows: (Y-MEAN(Y))/STDEV(Y).

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

View Table

Table II.2.

Standardized Coefficients

(1)	(2)	(3)	(4)	(5)	(6)	(7)
Dependent variable: average growth of real per capita GDP, 1980-2002
Investment ratio (percent of GDP)	0.49	0.46	0.54	0.44	0.43	0.49	0.44
Initial income (1980 U.S. dollars, logs)	-0.59	-0.61	-0.54	-0.64	-0.66	-0.90	-0.88
Inflation (percent)	-0.21	-0.23	-0.21	-0.23	-0.23	-0.24	-0.24
Institutional quality 1/	0.42	0.35	0.32	0.37	0.41	0.31	0.36
Average years of schooling	0.37				0.17		0.26
School enrollment, secondary (percent gross)		0.42
Literacy rate (adult total, percent of people ages 15 and above)			0.22
Life expectancy at birth (years)				0.49	0.34
Health expenditures per capita (current U.S. dollars, logs)						0.70	0.48

Notes: Standardized coefficients calculated by standardizing timeseries as follows: (Y-MEAN(Y))/STDEV(Y).

^1/Average of four indicators, rescaled to range from 1-12, including bureaucratic quality, corruption, rule of law, and government stability.

D. Implications for Pakistan

24. What do the above regression results imply for Pakistan? Currently, government spending in Pakistan on health and education—both as a ratio to GDP and per capita⁵—is among the lowest levels in the world, although there has been a significant increase over the past few years. Not surprisingly, social indicators are also relatively weak. Pakistan ranked 142^nd out of 177 countries covered by the United Nations Development Programs 2004 Human Development Index. Pakistan ranked particularly poorly in terms of educational attainment, but ranked somewhat better in terms of life expectancy.

25. Pakistan’s poor social indicators, however, do not appear to have had a major negative impact on its growth performance. During the sample period, Pakistan’s rate of economic growth was almost 5 percent, or slightly over 2 percent per capita. This is significantly better than the average performance of the countries included in the sample, which was an annual per capita growth rate of 0.8 percent, despite health and education indicators in Pakistan being lower than the sample averages (see Table II.3 and Figure II.1). But could Pakistan have achieved even higher growth rates if it had invested more in its human capital? Recent studies byHusain, 1999, and Easterly, 2001b, argue that Pakistan systematically underperforms on most social indicators for its levels of income and that it could indeed have achieved higher growth rates, if it had focused more on human capital accumulation. Easterly attributes this growth without development to domination by an elite and ethnic division, which both contributed to low levels of spending on health and education.

Table II.3.

Country Values of Factors Contributing to Growth

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

Table II.3.

Country Values of Factors Contributing to Growth

	Real GDP	Per Capita	Investment	Inflation	Institutional	Life	Average	Health
	Growth	Real GDP	Ratio		Quality	Expectancy	Years of	Expenditure
		Growth					Schooling	Per Capita
Pakistan	4.9	2.2	18.6	7.8	5.6	59.5	3.2	18
Bangladesh	4.2	2.0	18.9	8.0	3.4	55.5	2.2	11
India	5.5	3.4	22.9	8.6	6.6	59.3	4.1	23
Sri Lanka	4.5	3.0	25.3	11.8	5.4	70.5	6.2	30
Malaysia	6.3	3.5	32.6	3.4	7.9	70.9	6.3	122
Singapore	6.9	4.2	36.8	2.1	10.0	75.5	6.0	866
Thailand	6.0	4.6	30.9	4.9	7.5	67.5	5.6	77
South Korea	6.8	5.6	32.7	6.5	7.7	70.5	9.6	493
China	9.5	8.2	37.1	6.6	7.1	69.0	5.0	41
Sample average	3.1	0.8	21.3	62.8	5.9	58.5	4.0	122

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

View Table

Table II.3.

Country Values of Factors Contributing to Growth

	Real GDP	Per Capita	Investment	Inflation	Institutional	Life	Average	Health
	Growth	Real GDP	Ratio		Quality	Expectancy	Years of	Expenditure
		Growth					Schooling	Per Capita
Pakistan	4.9	2.2	18.6	7.8	5.6	59.5	3.2	18
Bangladesh	4.2	2.0	18.9	8.0	3.4	55.5	2.2	11
India	5.5	3.4	22.9	8.6	6.6	59.3	4.1	23
Sri Lanka	4.5	3.0	25.3	11.8	5.4	70.5	6.2	30
Malaysia	6.3	3.5	32.6	3.4	7.9	70.9	6.3	122
Singapore	6.9	4.2	36.8	2.1	10.0	75.5	6.0	866
Thailand	6.0	4.6	30.9	4.9	7.5	67.5	5.6	77
South Korea	6.8	5.6	32.7	6.5	7.7	70.5	9.6	493
China	9.5	8.2	37.1	6.6	7.1	69.0	5.0	41
Sample average	3.1	0.8	21.3	62.8	5.9	58.5	4.0	122

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

Figure Economic Growth and Education

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and Barro and Lee (2000)

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Figure Economic Growth and Education

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and Barro and Lee (2000)

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Figure Economic Growth and Education

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and Barro and Lee (2000)

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26. Table II.3 shows that Pakistan’s economic growth rates were broadly similar to those elsewhere in South Asia, although India has been growing at a slightly faster pace, as has Sri Lanka on a per capita basis. But Pakistan’s performance was significantly weaker than Malaysia, Singapore, Thailand, South Korea, or China. These countries recorded real per capita growth rates of 3½-8 percent on average per year over the period 1980-2002. Could Pakistan have achieved similar growth rates if it would have invested more in its human capital? Table II.3 also shows the values of the variables included in the regression equations for a number of Asian countries, as well as the sample averages. Table II.4 shows the contributions to growth, calculated using one of the equations presented in Table II.1 (equation (5)).

Table II.4.

Contributions to Growth

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

^1/Comprising 64 countries out of the total sample of 72 countries.

Table II.4.

Contributions to Growth

	Per Capita	Investment	Initial	Inflation	Institutional	Life	Average	Residual
	Real GDP	Ratio	Income		Quality	Expectancy	Years of
	Growth						Schooling
Based on equation (5) of Table 1
Pakistan	2.2	2.5	-8.6	-0.02	3.5	3.2	0.8	0.6
Bangladesh	2.0	2.6	-7.6	-0.02	2.1	3.0	0.6	1.3
India	3.4	3.1	-8.2	-0.02	4.1	3.2	1.1	0.0
Sri Lanka	3.0	3.5	-8.2	-0.03	3.4	3.8	1.6	-1.0
Malaysia	3.5	4.5	-11.0	-0.01	5.0	3.9	1.6	-0.4
Singapore	4.2	5.0	-12.5	-0.01	6.2	4.1	1.5	-0.2
Thailand	4.6	4.2	-9.6	-0.01	4.7	3.7	1.4	0.2
South Korea	5.6	4.5	-11.0	-0.02	4.8	3.8	2.5	1.0
China	8.2	5.1	-8.4	-0.02	4.5	3.8	1.3	2.0
Sample average 1/	0.9	3.0	-9.9	-0.17	3.7	3.2	1.1	0.0

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

^1/Comprising 64 countries out of the total sample of 72 countries.

View Table

Table II.4.

Contributions to Growth

	Per Capita	Investment	Initial	Inflation	Institutional	Life	Average	Residual
	Real GDP	Ratio	Income		Quality	Expectancy	Years of
	Growth						Schooling
Based on equation (5) of Table 1
Pakistan	2.2	2.5	-8.6	-0.02	3.5	3.2	0.8	0.6
Bangladesh	2.0	2.6	-7.6	-0.02	2.1	3.0	0.6	1.3
India	3.4	3.1	-8.2	-0.02	4.1	3.2	1.1	0.0
Sri Lanka	3.0	3.5	-8.2	-0.03	3.4	3.8	1.6	-1.0
Malaysia	3.5	4.5	-11.0	-0.01	5.0	3.9	1.6	-0.4
Singapore	4.2	5.0	-12.5	-0.01	6.2	4.1	1.5	-0.2
Thailand	4.6	4.2	-9.6	-0.01	4.7	3.7	1.4	0.2
South Korea	5.6	4.5	-11.0	-0.02	4.8	3.8	2.5	1.0
China	8.2	5.1	-8.4	-0.02	4.5	3.8	1.3	2.0
Sample average 1/	0.9	3.0	-9.9	-0.17	3.7	3.2	1.1	0.0

Sources: IMF World Economic Outlook; World Bank World Development Indicators; ICRG; and Barro and Lee (2000).

^1/Comprising 64 countries out of the total sample of 72 countries.

27. The regression results and the data in Table II.3 and Table II.4 indicate that the best way to achieve higher rates of economic growth is to raise investment and to improve the quality of institutions (see also Figure II.2). In the sample period, investment ratios were significantly higher in South-East Asian countries and China, than they were in South Asian countries, including Pakistan. This supports the Pakistani authorities emphasis on increasing private and public investment to achieve their growth targets. An increase in Pakistan’s investment ratio by 5-6 percentage points, as the authorities aim to achieve over the next 4-5 years—to a level comparable to that of Sri Lanka—could result in an increase in the countrys annual real per capita GDP growth rate of about 1 percentage point. Similarly, the countries in South-East Asia scored considerably better in terms of institutional quality. The results here suggest that the pace of economic growth in Pakistan can be raised further by improving the quality of its institutions. On a scale from 1-12, with a higher value representing better institutions, Pakistan rated 5.6 on average during 1980-2002. By increasing this score by 1 point—to a level similar to that of a country such as Egypt—Pakistan could raise its real per capita growth rate by about another ½ percentage point per year.

Economic Growth, Investment, and Institutions

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and International Country Risk Guide.

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Economic Growth, Investment, and Institutions

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and International Country Risk Guide.

• Download Figure
• Download figure as PowerPoint slide

Economic Growth, Investment, and Institutions

Citation: IMF Staff Country Reports 2004, 415; 10.5089/9781451830644.002.A002

Sources: IMF World Economic Outlook; World Bank World Development Indicators; and International Country Risk Guide.

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• Download figure as PowerPoint slide

28. The regression results and the data in Table II.3 and Table II.4 also suggest that lower investment in health and education in Pakistan at least partly accounted for the growth differences vis-a-vis South-East Asian countries. Pakistan could increase its pace of economic growth by investing more in human capital, as planned. While the impact this would have on growth would be somewhat smaller than that of raising investment or improving the overall quality of institutions, the effects would still be significant. For example, the average years of schooling received by Pakistan’s population 15 years and older was 3¼ years. Raising this by 1½-2 years—to the levels of countries such as Thailand or Venezuela—would be a major achievement, but could raise the real per capita growth rate also by about ½ percentage point per year. Improving health care to achieve an increase in the life expectancy of Pakistan’s population by five years—to levels comparable to that of countries such as Morocco or the Philippines—would add another ½ percentage point to its annual real per capita growth rate. Within the region, Sri Lanka is also a good example of a country that has better social indicators and has achieved somewhat stronger per capita growth rates than Pakistan, despite its prolonged ethnic strife.

29. Just as importantly, for a low-income country such as Pakistan, investing in human capital through better education and health care benefits the poor directly by improving the current living conditions, besides fostering economic growth. The majority of people in low-and middle-income countries do not posses many assets, other than their own human capital. The possibility to improve their living conditions, therefore, depends to a considerable extent on how productive they can be. This in turn depends, among other things, on the educational possibilities and health care that are available to them.

30. A few caveats. First, higher spending on health care and education should be well-targeted to specifically include the poor. This implies an emphasis on primary and secondary levels of education and basic health care, as opposed to more spending on higher education and more specialized health care. The richer segments of the population can be expected to benefit more from the latter, which would perpetuate the divide between the poor and the rich. Second, given the poor quality and/or limited availability of government financed education and health care, a growing number of people relies on private service providers. The data used in this study may not fully capture this, due to a lack of reporting. Private health care and education, however, is generally not accessible to the poor, thus also continuing the divide between the haves and have-nots. Third, care should be taken that higher (government) spending on health and education is used effectively. The quality of public services in Pakistan, as well as in other low- and middle-income countries, has often been poor, due to weak institutional capacity, corruption, or other factors. There have been frequent examples of teachers failing to show up for work, or not necessarily being more knowledgeable than the students they are supposed to teach. Higher social spending will, therefore, need to be accompanied by improvements in institutional capacity—to ensure that the funds are used efficiently and effectively—if it is to have the desired positive effect on future economic growth and poverty reduction.

E. Conclusion

31. The empirical results presented in this paper support the traditional view that raising investment and improving institutions are key to achieving higher rates of economic growth. But the results also confirm that countries that invest more in their human capital do better in terms of economic growth. Higher levels of education and better health care result in a more productive work force, increasing total factor productivity and pushing a country’s production function outward.

32. Compared to a large group of low- and middle-income countries, Pakistan’s performance in terms of per capita economic growth has been better than average during 1980-2002, and broadly similar to that of other countries in South Asia. But several countries in South-East Asia, such as Malaysia, Singapore, and Thailand achieved considerably higher rates of economic growth. Besides having higher rates of investment and a better quality of institutions, the quality of human capital in these countries was significantly better than in Pakistan, widening the growth differentials vis-a-vis Pakistan. This implies that Pakistan could have achieved even higher growth rates, had it invested more in its human capital. The Pakistani authorities are, therefore, correct in emphasizing the need for higher social spending in their development strategy, in addition to the need to attract more investment and further improve the overall quality of the country’s institutional framework.