International Handbook of Development Economics

International Handbook of Development Economics Volume One

Edited by

Amitava Krishna Dutt University of Notre Dame, USA

and

Jaime Ros University of Notre Dame, USA

Edward Elgar Cheltenham, UK • Northampton, MA, USA

© Amitava Krishna Dutt and Jaime Ros 2008 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library

Library of Congress Control Number: 2008927966

ISBN 978 1 84542 327 8 (2 volume set) Printed and bound in Great Britain by MPG Books Ltd, Bodmin, Cornwall

24 Education and human capital George Psacharopoulos and Harry Anthony Patrinos

History ‘A man educated at the expense of much labor and time . . . may be compared to one . . . expensive machine . . . The work which he learns to perform . . . over and above the usual wages of common labor will replace the whole expense of his education’ (Adam Smith, 1904 [1776], p. 101). Thus began the interest in education as an investment in economics. Articles on education as investment appeared sporadically in the first half of this century (for example Strumilin, 1929; Walsh, 1935). In the modern era, education and human capital entered economics in the late 1950s. The focus of the early writings was on the ‘unexplained’ residual in economic growth (Abramovitz, 1962). Schultz (1961) introduced the concept of human capital to explain Solow’s technological change (1956). From the theoretical literature two waves can be identified. The first, roughly corresponding to the period from 1960 to the 1980s, treated education as an exogenous factor (Becker, 1964). Then, from the late 1980s to the present, education was seen as endogenous, especially in the ‘new growth’ theory literature. From the voluminous empirical literature there are two avenues: micro – largely focused on the microeconomic returns to education; and macro – with early roots in growth accounting. There are essentially two classes of estimation methods: one that uses the internal-rate-of-return procedure, and another that approximates this procedure by means of fitting an earnings function to individual data sets (Mincer, 1974). Each of these classes is subdivided into the elaborate and short-cut methods, and the basic and extended-earnings function methods (Psacharopoulos and Mattson, 1998). The advantage of the Mincerian estimation is that it can smooth out and handle incomplete cells in an age–earnings profile matrix by level of education. Micro estimates The average returns to schooling are presented in Table 24.1. Clearly, the returns are higher in lower-income areas, and the global average is 10 percent. The same diminishing returns apply across countries: the more developed the country, the lower the returns to education at all levels. The high returns to education in low-income countries must be attributed to the 341

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International handbook of development economics, 1

Table 24.1 Mean returns to investment in education by world region (Mincerian rate of return)

Region

Per capita income level

Mean years of schooling

Rate of return (%)a

$25 000 $6 000 $5 000 $3 000 $1 000 $9 000

9.0 8.8 8.4 8.2 7.3 8.3

7.5 7.1 9.9 12.0 11.7 9.7

OECD Europe/Middle East/North Africa Asia Latin America/Caribbean Sub-Saharan Africa World average Note: a. Coefficient on years of schooling.

Source: Psacharopoulos and Patrinos (2004).

relative scarcity of human capital. Private returns are higher than social returns at all levels – a result of the public subsidization of education in most countries. The discrepancy between private and social returns is greatest at the university level – which raises issues of equity and finance. Although the concept of the rate of return to investment in education is unassailable, empirical applications have been attacked on a number of grounds. The most important issue is that of differential ability between those who complete different levels of schooling. To put it in the extreme (Arrow, 1973), a higher education degree might be nothing else than a filter; that is, selecting the more able. There has been a stream of research on this issue. Originally, an arbitrary ‘alpha’ (for ability) coefficient equal to twothirds was applied, in effect to reduce by one-third the earnings differentials of the more educated for unmeasured differences (Denison, 1967; Blaug, 1970). Later work by Griliches (1970, 1977; Griliches and Mason, 1972) indicated that including an IQ measure in the Mincerian earnings function reduced the rate of return to investment in education by only 10 percent. Perhaps the ultimate test for accepting that there are returns to education is to observe directly the productivity of workers with different levels of schooling. Beyond econometric shadow pricing, or observation shadow pricing, there is an immense line of work relating education to physical farm productivity. For example, in an early review of the literature, Jamison and Lau (1982) found that, on average, the difference between zero and four years of schooling among farmers results in a 10 percent increment in production. Rosenzweig (1995) and Foster and Rosenzweig (1996) have shown that primary education has an impact on farmers adopting new high-yield varieties. In India, for example, high-yield variety use had an 18 percent

Education and human capital

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greater effect on the per-area profitability for farmers with primary schooling, compared with farmers with no schooling (Rosenzweig, 1995). Macro estimates The importance of education in the growth process re-emerged in the 1980s with the influential writings of Romer (1986, 1990, 1992) and Lucas (1988). Romer and Lucas start with a Solow-type (Solow, 1956, 1957) aggregate production function, augmented in two ways. First, beyond some measure of human capital that is actually used by different firms in the economy, total output also depends upon the average level of human capital. Second, human capital is endogenous, rather than exogenous, in the system; that is, human capital is produced by using resources. The dramatic theoretical implications of this formulation is that output is no longer constrained by the constant-returns-to-scale property of the production function, and that ‘knowledge’ becomes a kind of public good that spills over the economy as an externality, allowing output to grow beyond the measurable inputs. The empirical implication of this formulation is that different countries need not converge to a common steady-state path, as predicted by neoclassical economics. The level of per capita income between countries can diverge forever, rather than converge. Another, equally important implication of this model is that, by virtue of the average stock of human capital being available to all, there might be social underinvestment in human capital formation. The returns to education using the macro approach are estimated either by: (1) an aggregate production function explaining GDP; or (2) an aggregate ‘macro-Mincerian’ earnings function where the units of observation are individual countries (Heckman and Klenow, 1998; Krueger and Lindahl, 2001). The literature on macro-level benefits is vast, complicated and controversial, leading to many different kinds of empirical estimates (Table 24.2). Equity Since education has such a strong bearing on individual earnings, it must also affect the distribution of income. The net effect of the expansion of schooling has been a reduction in the dispersion of earnings and hence a more equal distribution. This equitable effect, however, strongly depends on which level of schooling is expanded. The equity impact is highest for basic education, since the low earnings of otherwise illiterate workers are raised nearer to the overall mean. But if university education is expanded (and especially postgraduate education), the equity effect may be negative, in the sense that a group of workers with earnings above the mean are raised even further away from it. Taking Mexico as an example, Marin and

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Table 24.2

Examples of the contribution of education to economic growth

Database

Main findings

Study source

Cross-section of 32 countries, 1940–85

Early literacy is threshold countries must pass to grow

Azariadis and Drazen (1990)

98 countries, 1960–85, education proxied by primary and secondary enrollments

Increase of 1% point of respective initial 1960 enrollment ratio raises 1960–85 growth rate by 0.025% points for primary and 0.035 for secondary

Barro (1991)

Cross-section/panel of 121 countries, 1960–85, education measured by % of working age population in secondary school

Coefficient of log(education) on log(GDP/worker) is 0.70; coefficient of log(education) on log(difference GDP per worker 1960–85) is 0.23

Mankiw et al. (1992)

Cross-section panel of 111 countries, 1960–90

1 year increase in average years of schooling of labor force raises output per worker by 5–15%

Topel (1999)

Panel cross-section of 110 countries, education variable is average years of schooling, fitted macro-earnings function across countries

Return to schooling equals 18–30%

Krueger and Lindahl (2001)

Psacharopoulos (1976) report that providing primary education to 10 percent of those without it would make income distribution more equal by nearly 5 percent compared with the present level of an inequality index. Giving higher education to 5 percent of those with secondary education, however, would worsen the inequality index by 2 percent. Since most university students come from the higher-income groups in any society, state subsidies for their education will boost their future earnings at the expense of the general taxpayers, who are less likely to enroll their children in higher education. A large literature examines the benefits of education investments across the income distribution. Overall, public education expenditures are regressive, with a higher share of public spending going to groups from the highest family income categories. However, this has a lot to do with the fact that mostly individuals from high-income families enter university, which


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Table 24.3 Distribution of public education subsidy by expenditure quintiles, selected countries (%) Quintile Country

Year

Education level

1

2

3

4

5

Indonesia

1998

Primary Junior secondary Senior secondary

25 16 10

24 20 14

21 22 19

18 22 24

13 21 34

Malawi

1990/91

Primary Secondary Tertiary

20 9 1

23 10 7

21 16 13

20 25 20

16 39 58

Ghana

1992


22 15 6

24 22 10

22 22 19

19 26 20

14 19 45

South Africa

1993


27 18 11

21 18 13

17 17 16

16 21 28

19 25 32

Source: Yang (2004).

is associated with a much higher expenditure per student. When the data is disaggregated by level, by and large, the poor benefit more from expenditure on primary education (see Table 24.3). Wider human capital Human capital includes health. Yet evidence on health impacts is not as widely available as is evidence on the effect of education. In general, it is found that the more educated a woman, the lower her fertility, with no evidence of a threshold effect. The mechanism by which this is achieved is that parental education enhances the adoption of contraceptive techniques, and most importantly that female education raises the opportunity cost of children (Becker and Lewis, 1973; Ben-Porath, 1973; Cochrane, 1979; Rosenzweig and Schultz, 1989; Barro, 1991; Appleton, 1996). Age at marriage has been rising steadily in North African countries, due largely to school attendance (Westoff, 1992). In Honduras, Indonesia, Kenya and Mexico, schooled women desire fewer children, and express this through a higher rate of contraceptive use. Education also reduces infant mortality. For example, a ten percentage point increase in female primary education can be expected to decrease infant mortality by 4.1 deaths per 1000. Thus, in Pakistan, an extra year

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of schooling for an additional 1000 girls would prevent 60 infant deaths (UNICEF, 1999, p. 7). The more educated the parents, particularly the mother, the lower is maternal mortality and the healthier is the child. Parental education is significantly associated with the health status of children (defined by a reduction in mortality or an improvement in survival risks), even after controlling for socio-economic status and for access to health services (Cleland and Wilson, 1987; Hobcraft, 1993). Rising levels of maternal education reduce the odds of the child dying before age two. This relationship holds in both urban and rural settings. As with fertility, there are no thresholds in the relationship. Child mortality falls by about 8 percent for each additional year of parental schooling. The influence of parental schooling operates through the use of medical services (such as prenatal care and clinic visits) and changes in household health behavior (such as washing hands and boiling water). These behavioral changes may result both from perceptual and attitudinal changes and from the ability of the educated (whose incomes are higher than those of the uneducated) to afford better nutrition and better health services for their children (Caldwell, 1979). Even before taking account of these externalities, the returns to investment in women’s education exceed those to men’s education for those women who obtain employment. Once the health and fertility externalities are added, the case for educating girls becomes even stronger. The benefit–cost ratio of these health and fertility externalities in Pakistan, for instance, has been estimated at about 3:1. Non-market benefits and externalities The benefits of education captured in the rate-of-return estimates reported above are market benefits; that is, they are based on the price more and less educated people command in the labor market. However, there is another set of benefits stemming from a host of beneficial effects of education that are not traded in the market (Duncan, 1976). Such non-market effects are often compounded with public or external effects; that is, they affect not only the recipient of education but others as well. One of the problems in arriving at estimates of non-market and external effects is that benefits often overlap into more than one category. Table 24.4 provides a catalogue of such effects coming mainly from the United States. However, the fact that parental, especially the mother’s, education lowers fertility has been well documented for developing countries (Rosenzweig and Evenson, 1977; Sathar, 1984). As mentioned above, because of a perhaps unfortunate convention in the early 1960s literature on the economics of education, the adjective ‘social’

Education and human capital Table 24.4

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Non-market and external benefits of education

Benefit type

Findings

Study source

Child education

Parental education affects child’s educational level and scholastic achievement.

Murnane (1981), Angrist and Lavy (1996)

Child health

Child’s health positively related to parental education

Edwards and Grossman (1979), Grossman and Joyce (1989)

Fertility

Mother’s education lowers daughter’s births

Sandefur and McLanahan (1990), Rosenzweig and Evenson (1977), Sathar (1984)

Own health

More education increases life expectancy

Feldman et al. (1989), Robins (1984)

Spouse’s health

More schooling improves spouse’s health and lowers mortality

Auster et al. (1969), Grossman (1975)

Job search efficiency

More schooling reduces cost of search, increases mobility

Greenwood (1975), DaVanzo (1983)

Desired family size

More schooling improves contraceptive efficiency

Michael and Willis (1976), Rosenzweig and Schultz (1989)

Technological change

Schooling helps R&D and diffusion

Nelson (1972), Wozniac (1987)

Social cohesion

Schooling increases voting and reduces alienation

Gintis (1971), Comer (1988)

Crime

Education reduces criminal activity

Yamada et al. (1991), Ehrlich (1975)

Source: Based on and adapted from Wolfe and Zuvekas (1997).

attached to a rate-of-return calculation really meant ‘adjusted for the full cost of education, whether paid by the individual or the state’. Because of the universal public subsidization of education, by arithmetic definition the social rate of return is lower than the private rate. However, if one were to include difficult-to-measure spillover effects of education (say, in reducing crime) not realized by the individual, then the externalities-inclusive social rate of return might well be above the private one. The problem is that it is

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very hard to measure the spillover effects of education and add them up to the conventional (wage-based) benefits. The issue has also been raised as to what level of schooling is associated with most externalities relative to the other levels, in order to correct the hierarchy of the returns to education. For example, Birdsall (1996) argued that the returns to higher education are probably underestimated, given the assumed externalities university graduates bring to the economy. On the other hand, Psacharopoulos (1996) counter-argued that if externalities by level of schooling should be considered, then probably primary education has the highest externalities. This (untested) result is achieved by weighing the probability of a university graduate inventing a new vaccine, against the social costs imposed onto the rest of society by the illiterate masses. In the case of farmers adopting new varieties, better-schooled farmers are the first ones to use them and act as a source of information to others on the benefits of the new seeds. Based on farm surveys in India and the Philippines, Rosenzweig (1996, p. 28) reports that the profits of a farmer were 4 percent higher if his ‘representative’ neighbor in the village had completed primary schooling compared to his profitability when the neighbor had no schooling. Beyond the effect on neighbors (the classic geographicproximity example of an externality), Basu (1998) has carried the concept within the family, identifying intra-household externalities arising from the presence of a literate member. There might be a threshold in terms of human capital accumulation before a country can reap growth benefits. Azariadis and Drazen (1990) were the first to suggest this in the growth literature, while educators (Bowman and Anderson, 1963) and economic historians (Easterlin, 1981) had been suggesting it for a long time. Once the stock of knowledge surpasses certain critical values, aggregate production possibilities may expand especially rapidly (Azariadis and Drazen, 1990). In a back-of-theenvelope empirical testing of this theory, they found that the threshold might be early literacy. Using data from Brazil, Lau et al. (1996) found a threshold effect of education on output, namely an interval over which the effects are convex, between three and four years of average education. In other words, a country must have a critical mass of basic education before the returns to education manifest themselves. Or, there are increasing returns to the average level of education. This finding is consistent with Romer’s (1986) hypothesis that there exist increasing returns to intangible capital. The Mincerian earnings function was used in a country cross-section to decompose the effect of education on growth into: (1) an effect of the changed returns to education over time; (2) an indirect effect of schooling’s positive effect on schooling growth; and (3) a direct effect of education


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raising income, holding education growth constant (Glaeser, 1994). The indirect, schooling-to-schooling effect had the greatest impact in the decomposition. This finding is in the spirit of Becker and Murphy (1992) suggesting that earlier human capital creates later human capital, and the new growth literature on increasing returns to scale. Several other studies have found that parental education is a strong determinant of children’s school participation and eventual educational attainment (see, for example, Birdsall, 1985). But this is practically all there is in terms of empirical evidence. As noted by Schultz (1994, p. 45), there is little concrete guidance in this literature on where precisely to look for this externality. Quality versus quantity A standard criticism of empirical estimates of the returns to education is that such returns refer to the quantity of schooling, saying nothing about quality. Several studies have shown the importance of school quality in determining earnings (Behrman and Birdsall, 1983; Solmon, 1985; Psacharopoulos and Velez, 1993; Card and Krueger, 1996; Bedi, 1997). This is not really a critique of the rate-of-return literature – rather it is pointing to an omission because of the difficulty of obtaining information on learning outcomes. Yet a counter-argument could be that rates of return to investment in education, as conventionally estimated, by definition refer to the average level of quality across all schools in the sample. So, if school quality is important in determining earnings, improving school quality must yield even higher returns to education. Most of the evidence on the developmental effects of education refers to the extensive margin; that is, to the number of years of schooling of the labor force. Evidence on the intensive margin – the quality of education provided – is scarce (Behrman and Birdsall, 1983). The reason is that, in developing countries, longitudinal data sets that follow the student from school to adult life and measure economic performance are rare. Furthermore educational quality means different things to different people. First, there is the traditional input definition, by which higher expenditure per pupil or lower repetition rates are indicators of good quality. But throwing money at schools does not necessarily mean that such money will be used efficiently, and automatically promoting everyone in a class does not mean that graduates will (at least) have been made literate. Second, there is the output definition of educational quality, based on the students’ learning achievement. But because so many factors other than schooling (for example, prior cognitive knowledge and family background correlate with cognitive achievement in a cross-section), it is difficult to isolate the particular effects of education.

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Policy implications In education, as in any other field, universal policy prescriptions simply do not exist. The strategy and tactics of education depend upon the initial conditions in a particular country, which means that whereas policy A is suitable for country X, policy B may be more suitable for country Y. Given this qualification, the accumulated evidence in the economics of education in the past 30 years permits some broad policy generalizations. The list which follows is conservative, in the sense that, unless the initial conditions in a given country dictate otherwise, the propositions may be applicable to a large number of countries. Emphasis on primary education in developing countries Human capital theory holds that investment in human resources results in improved productivity, and that both the costs of the investments and the benefits of improved productivity can be used to calculate an economic rate of return. Human capital investments generally take the form of education or training and may include health care as well. An important distinction is made between private and social rates of return. Private rates of return accrue to families from human capital investments. Social rates of return include private returns, but also consider positive externalities such as improved public health, diffusion of democratic values and practices, and more freedoms for individuals in society. The existence of social returns provides a rationale for public investment in primary education. The World Bank policy paper on Primary Education and subsequent education policy papers (World Bank, 1990, 1995, 1999) embraced human capital theory, observing that education, particularly at the primary level, increases the productivity of the workforce through improved literacy, numeracy and health status. Other international public agencies, governments and academics have substantially agreed with the general interpretation of the human capital justification for public investment in primary education. Emphasis on general over specific skills Manpower planning models were debunked as a planning tool for a dynamic market economy (Psacharopoulos et al., 1983). Cost–benefit analysis was used to show that, not only were these investments generally unable to match the demand and supply of skills well, but they also suffered low returns because of their small benefits and high cost (see for example, Psacharopoulos and Loxley, 1985). Emphasis on cost recovery in higher education At the highest level of education, cost recovery is the most promising policy for both efficiency and equity reasons. Too much of a typical education


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budget is devoted to the university level, which typically has the lowest social rate of return, and where a disproportionate number of students come from the more affluent parts of society (World Bank, 1986). Some sons and daughters of poor farmers make it to university, but they are the exceptions that prove the rule. Yet attendance at the university is typically free, and students may even receive a cash allowance. If students pay at least part of the cost of their education, they are more likely to make better choices on whether to enroll and what to study. For the talented poor, selective scholarships or loans can be provided. Along with cost recovery, universities could adopt more traditional efficiency measures, such as the consolidation of dispersed campuses into larger units. Economies of scale apply as much to university campuses as to industrial plants. The average cost per student declines sharply once enrollment exceeds 500 (Psacharopoulos, 1982). Conclusions The concept of human capital has a long history in the economics literature. Decades of writings have established firmly that spending on education is an investment with an economic return. Firm conclusions about education’s contributions to productivity have been established. The empirical literature counts hundreds of studies that have estimated the economic return to investments in education, as well as other forms of human capital. Still, research on the subject is ongoing, given that important theoretical and empirical questions remain unanswered. New methodological tools enable researchers to estimate the causal impact of education on earnings and the heterogeneity of returns to schooling across population subgroups. The impact of the quality of human capital – in addition to the quantity – is gaining more attention in the empirical literature. The link to growth has been especially critical in recent years. Data limitations are partly to blame for a lack of consensus among researchers, but much more needs to be done to reconcile for example the high and robust returns to schoolings at the individual level, with the mixed signals at the macro or cross-country level. Given that the degree of model sophistication is not matched by the data used in empirical applications, then one may want to rely more confidently on the micro evidence. Other forms of human capital produce returns, and often these other forms interact with education. Among the established relationships, for example, is that the more educated a woman, the lower her fertility. Education also reduces infant mortality. Also, the more educated the parents, particularly the mother, the lower is maternal mortality and the healthier is the child. Parental education is significantly associated with the health status of children, even after controlling for socio-economic status and for access to health services.

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