The Role of Cognitive Skills in Economic Development

Journal of Economic Literature 2008, 46:3, 607–668 http:www.aeaweb.org/articles.php?doi=10.1257/jel.46.3.607

Eric A. Hanushek and Ludger Woessmann*

The role of improved schooling, a central part of most development strategies, has become controversial because expansion of school attainment has not guaranteed improved economic conditions. This paper reviews the role of cognitive skills in promoting economic well-being, with a particular focus on the role of school quality and quantity. It concludes that there is strong evidence that the cognitive skills of the population—rather than mere school attainment—are powerfully related to individual earnings, to the distribution of income, and to economic growth. New empirical results show the importance of both minimal and high level skills, the complementarity of skills and the quality of economic institutions, and the robustness of the relationship between skills and growth. International comparisons incorporating expanded data on cognitive skills reveal much larger skill deficits in developing countries than generally derived from just school enrollment and attainment. The magnitude of change needed makes clear that closing the economic gap with developed countries will require major structural changes in schooling institutions.

1. Introduction raise the schooling levels of the population. And, indeed, this is exactly the approach of t takes little analysis to see that schooling the Education for All initiative and a central Ilevels differ dramatically between devel- element of the Millennium Development oping and developed countries. Building Goals (see, e.g., UNESCO 2005 and David upon several decades of thought about E. Bloom 2006). human capital—and centuries of general But there are also some nagging uncer- attention to education in the more advanced tainties that exist with this strategy. First, countries—it is natural to believe that a pro- developed and developing countries differ ductive development strategy would be to in a myriad of ways other than schooling

* Hanushek: Stanford University, CESifo, and NBER. Paul Gertler, Manny Jimenez, Ruth Kagia, Beth King, Woessmann: Ifo Institute, University of Munich, and Lant Pritchett, Emiliana Vegas, the editor, and three CESifo. This project developed through conversa- anonymous referees. Jason Grissom provided important tions with Harry Patrinos, who provided useful com- research assistance. Support has come from the World ments and suggestions along the way. We have also Bank, CESifo, the Program on Education Policy and Gov- benefited from comments by Martha Ainsworth, Luis ernance of Harvard University, and the Packard Humani- Benveniste, François Bourguignon, Deon Filmer, ties Institute. 607 608 Journal of Economic Literature, Vol. XLVI (September 2008) levels. Second, a number of countries—both We will show in graphic terms the dif- on their own and with the assistance of oth- ferences in cognitive skills that exist, even ers—have expanded schooling opportunities after allowing for differences in school without seeing any dramatic catch-up with attainment. Most people would, in casual developed countries in terms of economic conversation, acknowledge that a year of well-being. Third, countries that do not schooling in a school in a Brazilian Amazon function well in general might not be more village was not the same as a year of school- able to mount effective education programs ing in a school in Belgium. They would also than they are to pursue other societal goals. agree that families, peers, and others con- Fourth, even when schooling policy is made tribute to education. Yet, the vast major- a focal point, many of the approaches under- ity of research on the economic impact of taken do not seem very effective and do not schools—largely due to expedience—ig- lead to the anticipated student outcomes. In nores both of these issues. The data suggest sum, is it obvious that education is the driv- that the casual conversation based on dis- ing force or merely one of several factors that parities in school attainment may actually are correlated with more fundamental devel- understate the magnitude of differences in opment forces? true education and skills across countries. The objective of this study is to review We think of education as the broad mix of what research says about the role of educa- inputs and processes that lead to individual tion in promoting economic well-being. We knowledge. Yet, because schooling and edu- pay particular attention to the robustness cation are conflated in common usage, we of the relationship between education and will generally refer specifically to cognitive economic outcomes across tests of alterna- skills, the part of education for which we tive specifications and hypotheses about the have good measures. underlying determinants of outcomes. We provide strong evidence that ignoring The discussion also has one distinctive ele- differences in cognitive skills significantly ment. We have come to conclude that cogni- distorts the picture about the relationship tive skills—particularly in assessing policies between education and economic outcomes. related to developing countries—are THE This distortion occurs at three levels. It misses key issue. It is both conventional and conve- important differences between education and nient in policy discussions to concentrate on skills on the one hand and individual earnings such things as years of school attainment or on the other. It misses an important underly- enrollment rates in schools. These things are ing factor determining the interpersonal dis- readily observed and measured. They appear tribution of incomes across societies. And, it in administrative data and they are published very significantly misses the important ele- on a consistent basis in virtually all countries ment of education in economic growth. of the world. And, they are very misleading The plan of this study is straightforward. in the policy debates. Based on a simple conceptual framework, Cognitive skills are related, among other we document the importance of cognitive things, to both the quantity and quality skills in determining individual earnings of schooling. But schooling that does not and, by implication, important aspects of improve cognitive skills, measured here by the income distribution. We then turn to comparable international tests of mathemat- the relationship of education and economic ics, science, and reading, has limited impact growth. Research into the economics of on aggregate economic outcomes and on growth has itself been a growth area, but economic development. much of the research focuses just on school Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 609 attainment with no consideration of cogni- Yet, while recognizing the impact of these tive skill differences that might arise from overall institutions, we find that cognitive variations in school quality or other sources skills play an important role. Furthermore, of learning. We show, in part with new evi- there is ample evidence that a high-quality dence, that the previous estimation is highly school system can lead to improved cognitive biased by concentration on just quantity of skills. And from a public policy perspective, schooling. interventions in the schools are generally The simple answer in the discussion of viewed as both more acceptable and more economic implications of education is that likely to succeed than, say, direct interven- cognitive skills have a strong impact on indi- tions in the family. vidual earnings. More than that, however, Given the evidence on the importance cognitive skills have a strong and robust of cognitive skills for economic outcomes, influence on economic growth. Models that we turn to what can be said about their include direct measures of cognitive skills production in developing countries. Although can account for about three times the varia- information on enrollment and attainment tion in economic growth than models that has been fairly widely available, cognitive include only years of schooling; including the skills information has not. We use newly cognitive skills measures makes the coeffi- developed data on international assessments cient on years of schooling go to zero; and of cognitive skills (also employed in the anal- the estimates of such more inclusive models ysis of growth) to show that the education are far more robust to variations in the over- deficits in developing countries are larger all model specification. In both the earnings than previously appreciated. and the growth areas, we can reject the most Finally, in terms of framing the analysis frequently mentioned alternative explana- here, we motivate much of the discussion by tions of the relationships. a consideration of world development goals To be sure, while there is a policy link to and the impacts of educational quality on schools, none of this says that schools per se economic outcomes in the developing world. are the answer. Even though it is common to Yet the bulk of the evidence on outcomes treat education and schooling synonymously, has clear and direct implications for devel- it is important to distinguish between oped countries. In simplest terms, available knowledge and skills on the one hand and evidence suggests that the economic situa- schooling. This distinction has important tion in, for example, the United States and substantive underpinnings. Cognitive skills Germany is governed by the same basic edu- may be developed in formal schooling, cational forces as that in developing coun- but—as extensively documented—they may tries of South America. Thus, this should also come from the family, the peers, the not be thought of so much as a treatise on culture, and so forth. Moreover, other fac- policies toward Sub-Saharan Africa but as tors obviously have an important impact on an analysis of the fundamental role of cogni- earnings and growth. For example, overall tive skills on the operations of international economic institutions—a well-defined sys- economies. tem of property rights, the openness of the economy, the security of the nation—can be 2. Conceptual Framework viewed almost as preconditions to economic development. And, without them, education We begin with a very simple earnings and skills may not have the desired impact model: individual earnings (y) are a function on economic outcomes. of the labor market skills of the individual 610 Journal of Economic Literature, Vol. XLVI (September 2008)

(H), where these skills are frequently referred ing H or its determinants in equation (2).1 to simply as the worker’s human capital. For We return to such estimation below but simplicity in equation (1), we assume that first discuss an alternative approach built on this is a one-dimensional index, although this direct measures of cognitive skills. is not important for our purposes: Consider test score measures of cognitive skills—that is, standardized assessments of (1) y 5 gH 1 e. mathematics, science, and reading achievement. If these measures, denoted C, completely capture variations in H, equation (1) The stochastic term, e, represents idiosyn- could be directly estimated with C, and the cratic earnings differences and is orthogonal key parameter (g) could be estimated in an to H. unbiased manner. Further, if school quantity, This abstract model has been refined in a S, is added to the estimation equation, it would wide variety of ways, most importantly by con- have no independent influence (in expecta- sidering the underlying behavior of individuals tion). But nobody believes that existing test in terms of their investments in developing data are complete measures of H. Instead, skills (Yoram Ben-Porath 1967, 1970; James J. the achievement test measures, C, are best Heckman 1976; Flavio Cunha et al. 2006). This thought of as error prone measures of H: basic model of earnings determination is central to most empirical investigations of wages and individual productivity. Before pursuing (3) C 5 H 1 m. this existing research, however, it is useful to understand where the skills might come from. With classical measurement errors, one These skills are affected by a range of factors would expect the estimate of g to be biased including family inputs (F), the quantity and toward zero and, if S and C are positively cor- quality of inputs provided by schools (which related as would be expected, the coefficient we incorporate as the function, Q(S), where on S in the same estimated equation would S is school attainment), individual ability (A), be biased upward even if S has no indepen- and other relevant factors (X) which include dent effect over and above its relationship labor market experience, health, and so forth. with C. This simple model would imply that Along with a stochastic term assumed uncor- the coefficient on C would be a lower bound related with the other determinants of H, we on the impact of human capital on incomes. can write this simply as The more common development, however, begins with using school attainment (2) H 5 lF 1 fQ(S) 1 dA 1 aX 1 n. as a measure of human capital and proceeds

Human capital is nonetheless a latent vari- 1 Translating the abstract idea of skills into quantity of schooling was indeed the genius of Jacob Mincer, able. To be useful and verifiable, it is neces- who pioneered both the consideration of the character sary to specify the measurement of H. The of human capital investment and the empirical deter- vast majority of existing theoretical and mination of wages that built on this (Mincer 1970, 1974). This work spawned an extensive literature about empirical work on earnings determination the determination of earnings and the appropriate solves this by taking the quantity of schooling approach to the estimation. From the Mincer develop- of the individual (S) as a direct measure of H ment and its extensions, S is substituted for H in equation (1) and its coefficient is frequently interpreted as and then dealing in one way or another with the rate of return on investment of one year of schooling the complications of not completely measur- when y is measured as the log of earnings (see below). Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 611 to interpret this under a variety of circum- There are nonetheless two complications stances. Propelled by readily available data in the interpretation of such models. The on school attainment within and across first is that schooling is but one of the fac- countries, economists have devoted enor- tors influencing cognitive skills and human mous energy to estimating the returns to capital formation. The second is that most additional years of schooling, and this work formulations of the Mincer model assume has been summarized and interpreted in a that school quality is either constant or can 2 number of different places. The focal point be captured by addition of direct measures has generally been how to get an unbiased of school quality in equation (4). estimate of g (or a simple transformation of The importance of nonschool influences g) under various considerations of other fac- on cognitive skills, particularly from the tors that might influence earnings and skills. family, has been well documented within For example, the ubiquitous Mincer earnings the literature on education production model takes the form functions, which provides the backdrop for the formulation in equation (2).3 If the 2 ( 4 ) y 5 b0 1 b1S 1 b2Z 1 b3Z 1 b4W 1 e, vector of other factors, W, in the earnings model includes the relevant other influences on human capital from equation where Z is labor market experience, W is a (2), the estimate of b would be simply vector of other measured factors affecting 1 fg 4 incomes, and y is labor market earnings, (as long as school quality is constant). typically measured in logarithms. In this, Unfortunately, having rich information according to equation (2), the estimated about other determinants of skills outside of school attainment is seldom if ever avail- return to a year of schooling (b1) is biased through the correlation of S with F, A, and able, because this requires data about fac- any omitted elements of X; examples of such tors contemporaneous with schooling and correlation would be predicted in standard long before observed labor market data optimizing models of the choice of years are available. While a number of ingenious of schooling (e.g., Card 1999, Paul Glewwe approaches have been used, including for 2002). Recognizing this, significant attention example exploiting the common experi- has concentrated on ability bias arising from ences of twins, it is seldom plausible to correlation of school attainment with A and conclude that the other factors in equation from other selection effects having to do with (2) have been adequately controlled, lead- families and ability (see Card 1999). Indeed, ing to the interpretation of b1 as the com- various estimates of earnings models have bined influence of school and correlated added test score measures to the Mincer model in equation (4) explicitly to control for ability differences. 3 See, for example, the discussion in Eric A. Hanushek (1979). 4 While equation (2) highlights measurement error and its sources, t he histor ica l treatment has concentrated a lmost 2 See early discussions in Mincer (1970) and Zvi exclusively on simple misreporting of years of schooling, as Griliches (1977) and more recent reviews in David Card opposed to potential omitted variables bias from neglect- (1999) and Heckman, Lochner, and Todd (2006). In an ing (correlated) components of the true skill differences international context, see George Psacharopoulos (1994), contained in H. See, for example, Orley Ashenfelter and Psacharopoulos and Harry Anthony Patrinos (2004), Alan B. Krueger (1994). In our context, simple survey and Colm Harmon, Hessel Oosterbeek, and Ian Walker errors in S are a relatively small part of the measurement (2003). errors and omissions in specifying human capital. 612 Journal of Economic Literature, Vol. XLVI (September 2008)

5 but omitted other influences. As such, b1 measures of quality, so that the coefficient is a reduced form coefficient that will give on S might be interpreted as the return to biased estimates of the potential impact a year of average quality school.7 A variety from a policy designed to change school of authors have pursued this approach of attainment alone. adding quality measures generally related The second major issue revolves around to inputs such as spending per pupil or variations in school quality, indicated by Q(S) pupil–teacher ratios. Unfortunately, prior in equation (2). Perhaps the simplest formu- work investigating the determinants of skills lation of this is following equation (2) does not support measuring school quality in this manner.8 (5) Q(S) 5 qS, Additional complications of estimation and interpretation arise if human capital includes important elements of noncognitive skills. where time in school, S, is modified by a qual- Noncognitive skills, while seldom precisely ity index, q. As long as the variation in q is defined, include a variety of interpersonal small, this is not a serious additional impedi- dimensions including communications abil- ment to estimation. In an international con- ity, team work skills, acceptance of social text this assumption is clearly unreasonable, norms, and the like. Along such a line, Samuel as will be described below. But, even in terms Bowles and Herbert Gintis and more recently of individual countries (where earnings esti- Heckman and his coauthors have argued mation is virtually always done), there is also that noncognitive skills are very important substantial evidence that school quality varies for earnings differences.9 Their formula- significantly.6 tion essentially begins with the notion that If estimated in logarithmic form, the specification in equation (5) suggests deal- (6) H 5 C 1 N 1 m ing with school quality by adding direct

5 In terms of equation (2), studies using school- schooling than those not educated in such circumstances ing and income differences of twins (see Card 1999) (Hanushek and Lei Zhang 2008). assume that school quality differences are relatively 7 In reality, not much attention has been given to func- unimportant or unsystematic so that quantity of school- tional form, and much of the estimation is done in linear or ing, S, is the central object. Then, if ability, family semilinear form. An exception is Card and Krueger (1992) circumstances, and other factors affecting skills are who develop a multiplicative specification, but their for- relatively constant across twins, differences in school- mulation has also been criticized (Heckman, Anne Layne- ing can be related to differences in earnings to obtain Farrar, and Todd 1996). an unbiased estimate of g. Of course, the key ques- 8 In terms of school inputs in earnings functions, see tion remaining is why S differs across otherwise iden- Julian R. Betts (1996). More generally in terms of equa- tical twins who presumably face identical investment tion (2), see Hanushek (2003) and Ludger Woessmann payoffs. Other instrumental variable approaches have (2007). An alternative approach related to this paper is also been introduced to deal with the endogeneity the inclusion of test score measures C directly in equa- ofschooling, but they frequently will suffer if human tion (4) with the notion of interpreting C as a direct capital evolves from nonschool factors as in equation (2). measure of school quality that purges any school qual- 6 Moreover, changes in school quality over time within ity variations from the coefficient on years of school- individual countries may be important. Typically, Mincer ing. In the spirit of equation (2), this would not be earnings models compare the earnings associated with easily interpretable if cognitive skills, C, in fact cap- school attainment across individuals of different ages, ture the relevant variations in human capital, H. who necessarily obtained their schooling at different 9 See, for example, the early work along these lines that times, and implicitly assume that a year of schooling is the includes Bowles and Gintis (1976) and Bowles, Gintis, and same, regardless of when received. As a simple example, Melissa Osborne (2001). These is extended in a variety of people educated under wartime conditions may receive ways in Cunha et al. (2006) and Heckman, Jora Stixrud, significantly different educational outcomes per year of and Sergio Urzua (2006). Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 613 and then duplicates the general form of this, measures of N are typically not available, equation (2) to describe the underlying and there is little agreement on even what determinants of C and N.10 This suggests the dimensions might be important.12 If, how- following modification of equation (4), which ever, various noncognitive dimensions are is a reduced form equation that combines important, the estimate of b59 is the reduced influences of both cognitive and noncogni- form effect of cognitive skills and correlated tive factors through the channels of C and S: noncognitive skills. Focusing on measures of cognitive skills has 2 (7) y 5 b90 1 b91S 1 b92Z 1 b93Z 1 b94X a number of advantages. First, they capture variations in the knowledge and ability that 1 b95C 1 e9. schools strive to produce with their curricula and thus relate the putative outputs of In this formulation, estimation of equa- schooling to labor market success. Second, by tion (7) with the inclusion of C yields an impli- emphasizing total outcomes of education, they cation that the coefficient onS (i.e., b19) would incorporate skills from any source—families, reflect the impact of human capital differ- schools, ability, and so forth as seen in equa- ences that are not captured by C.11 Yet, for the tion (2). Third, by allowing for differences in same reasons discussed previously, b19 would performance among students with differing not be simply fg. It is still biased by other quality of schooling (but possibly the same omitted determinants of N, such as the family. quantity of schooling), they open the inves- It is important to note, nonetheless, that tigation of the importance of different poli- finding a direct effect of schooling on earn- cies designed to affect the quality aspects of ings to be zero (b19 5 0) after conditioning on schools. In that regard, this approach permits cognitive skills is not the same as saying that aligning investigations of the labor market school attainment does not matter. It merely with the extensive work that has also delved says that the impact of school comes entirely into aspects of educational production func- through the impact on cognitive skills, so that tions (see Hanushek 2002). Finally, recent schooling that does not raise cognitive skills policy attention to accountability in schools— is not productive. In general, the impact of along with the acceptance of parents that school attainment is cognitive skills are important outcomes of schools—reinforce giving more attention to (8) 0y/0S 5 b19 1 b59 (0C/0S). test-based measures of cognitive skills. At the same time, the test score measures A more complete approach might be to of cognitive skills, as indicated, also have dis- include direct measures of noncognitive advantages. As described, the tests that are skills, N, into the estimation in equation (7). given are undoubtedly narrower than either While some attempts have been made to do what is taught in schools or what elements are

10 The focus of this work, Cunha et al. (2006), is some- however, on the specific data samples and questions being what different from the discussion here. They are attempt- investigated. ing to obtain a better description of lifetime investment 12 Reviews of these analyses along with new estima- behavior and of the returns to varying kinds of human tion is found in Bowles, Gintis, and Osborne (2001), capital investment. Cunha et al. (2006), and Heckman, Stixrud, and Urzua 11 Heckman and Edward Vytlacil (2001) go fur- (2006). They use survey measures to capture such ther to argue that it is not possible to separate school behaviors as motivation, persistence, time prefer- attainment and achievement because they are so ence, and self control, but the choice of these appears highly correlated. The importance of this depends, to be heavily dependent upon the specific survey data. 614 Journal of Economic Literature, Vol. XLVI (September 2008) important in the labor market, including non- income instead of individual earnings, y. cognitive skills. This narrowness is clearest Much modeling of economic growth high- when considering individual tests of particu- lights labor force skills or the human capi- lar domains of knowledge, such as primary tal of the country (along with other things as school reading. Most of the available tests are described below). given at the school level, frequently at the end Again, the vast majority of growth modeling of lower secondary education, so that they do has simply taken measures of school attain- not directly capture variation in higher edu- ment to characterize skills. Here, however, cation (although they may do so indirectly differences in educational outcomes (either through their predictive power for obtaining total or per year of schooling) become central further education). Additionally, even as tests because the analysis assumes that, say, ten of specific subject matter at the secondary years of schooling means the same in terms school level, the issue of measurement error of skills regardless of the country. Intuitively, in the tests cannot be ignored. The tests may the error in measuring skills by school attain- suffer from a variety of problems related to ment becomes large when comparing coun- the sampling of knowledge in the particular tries. More importantly, the error will be very domain, the reliability of questions, and even systematic, based on the country and, quite the impact of test taking conditions on scores. likely, different aspects of the country. Again, as described above, these concerns The relevant omitted variables and mea- generally imply that the estimated effects of surement errors are just those depicted cognitive skills will be a lower bound on the in equation (2). The aggregate skills of impact of improved skills. individuals in a country will vary with This discussion was designed to sketch family inputs, school quality, ability differ- out the range of possible issues in estimat- ences, and other country specific factors.13 ing human capital earnings functions, but This motivates our work here. International the importance of the various issues is an test scores provide consistent measures of empirical question. The possibility of biased aggregate differences in cognitive skills estimates through correlated omitted vari- across countries. As such, they do not attri- ables is particularly important in some bute all differences in cognitive skills to contexts, such as the endogeneity of school the schools in different countries, although attainment, but is also relevant elsewhere. many policy discussions will hinge on the Acknowledging the range of possible issues importance of schools in producing differ- does not capture the importance of them ences in cognitive skills. in specific empirical analyses. In the subse- The following sections investigate the exist- quent interpretations of various estimation ing evidence about how educational outcomes schemes, we will focus on the importance of relate to economic outcomes. Throughout we the various issues raised in the conceptual emphasize the impacts of variations in mea- model and emphasize evidence that deals sured cognitive skills on economic outcomes. with particular threats to identification. First, we demonstrate that these educational This discussion of individual economic outcomes has relevance for modeling the 13 Krueger and Mikael Lindahl (2001) are motivated growth of nations. Even though developed by differences in the aggregate and individual estimates of in different ways, many relevant aspects of g, and they focus on measurement error in school attain- growth models can be put in the context of ment. That analysis is directly analogous to the work on measurement error in modeling individual earnings, and equations (1) and (2) where the outcome of it does not consider the more significant issues about other interest is aggregate income or growth in sources of differences in skills (equation (2)). Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 615 outcomes produce the most consistent and estimated schooling effect could include both reliable information about education and the impacts of schooling and the fact that development. Second, these outcomes can those continuing in school could earn more in then be related directly to the relevant policy the absence of schooling. For the most part, options facing nations. The standardly used employing alternative estimation approaches measures of school attainment, on the other dealing with the problems of endogeneity hand, provide much less reliable measures of schooling do not lead to large changes in of skill differences, particularly in the cross- the estimates, and many times they suggest country growth context. that the returns are actually larger with the alternative estimation schemes than with 3. Individual Returns to Education and the simpler modeling strategies (e.g., Philip Economic Inequality Oreopoulos 2006). Harmon, Oosterbeek, and Walker (2003) systematically review 3.1 Impacts of School Attainment on the various issues and analytical approaches Individual Incomes dealing with them along with providing a set Most attention to the value of school- of consistent estimates of returns (largely for ing focuses on the economic returns to OECD countries) and conclude that, while differing levels of school attainment for the estimation approaches can have an impact individuals as depicted in equation (4). on the precise value of the rate of return, it This work, following the innovative anal- is clear that there is a strong causal impact of yses of human capital by Mincer (1970, school attainment on earnings. 1974), considers how investing in differ- The basic estimates of Mincer earnings ing amounts of schooling affects individual models are typically interpreted as the pri- earnings. Over the past thirty years, liter- vate returns to schooling. As is well known, ally hundreds of such studies have been the social returns could differ from the pri- conducted around the world, reviewed and vate returns—and could be either above or interpreted by a variety of studies such below the private returns. The most com- as Psacharopoulos (1994), Card (1999), mon argument is that the social returns Harmon, Oosterbeek, and Walker (2003), will exceed the private returns because of Psacharopoulos and Patrinos (2004), and the positive effects of education on crime, Heckman, Lochner, and Todd (2006). health, fertility, improved citizen participa- These basic estimations of rates of return tion, and (as we discuss below) on growth have uniformly shown that more schooling is and productivity of the economy as a whole. associated with higher individual earnings. Recent studies indeed find evidence of The rate of return to schooling across coun- externalities of education in such areas as tries is centered at about 10 percent with reduced crime (Lochner and Enrico Moretti variations in expected ways based largely on 2004), improved health of children (Janet scarcity: returns appear higher for low income Currie and Moretti 2003), and improved countries, for lower levels of schooling, and, civic participation (Thomas S. Dee 2004, frequently, for women (Psacharopoulos and Kevin Milligan, Moretti, and Oreopoulos Patrinos 2004). 2004). The evidence on direct production Much of the academic debate has focused spillovers of education among workers is on whether these simple estimates provide more mixed, with Moretti (2004) and the credible measures of the causal effect of studies cited therein finding favorable evi- schooling. In particular, if more able people dence and Daron Acemoglu and Joshua D. tend also to obtain additional schooling, the Angrist (2001) and Antonio Ciccone and 616 Journal of Economic Literature, Vol. XLVI (September 2008)

Giovanni Peri (2006) finding no evidence But it is not appropriate simply to presume for this kind of spillovers. that any spending on schools is a productive In the Mincer earnings work, a specific investment. It is instead necessary to ascer- version of social rates of return is frequently tain two things: how various investments calculated. The typical calculations do not translate into skills and how those skills take account of possible positive externali- relate to economic returns. This and the fol- ties, but they instead take account of the fact lowing sections provide a summary of what that the social cost of subsidized education is known about the individual returns spe- exceeds the private costs—thus lowering the cifically to cognitive skills in both developed social rate of return relative to the private rate and developing countries. of return (see Psacharopoulos and Patrinos As discussed in section 2, one of the chal- 2004). In addition, the social return could be lenges to understanding the impact of human below the private return also if schooling was capital has been simply knowing how to mea- more of a selection device than of a means sure human capital. Here we focus on how of boosting knowledge and skills of individu- well cognitive achievement measures—stu- als. The empirical analysis of these issues has dents’ performance on standardized tests— been very difficult because the labor market proxy for the relevant labor market skills outcomes of the screening/selection model when assessed against individuals’ perfor- and the productivity/human capital model mance in the labor market and the economy’s are very similar if not identical. Fabian Lange ability to grow. and Robert Topel (2006) review the theory Until fairly recently, little comprehen- and empirical work and conclude that there is sive data have been available to show any little evidence that the social rate of return to relationship between differences in cognitive schooling is below the private rate of return. skills and any related economic outcomes. Thus, although there are many uncertainties The many analyses of school attainment and about precisely how social returns might dif- Mincer earnings functions rely upon read- fer from private returns, there is overall little ily available data from censuses and surveys, reason to believe that the social returns are which find it easy to collect information on less than the private returns, and there are a earnings, school attainment, age, and other variety of reasons to believe that they could demographic information. On the other hand, be noticeably higher. it is difficult to obtain data on cognitive skills along with earnings and the other determi- 3.2 Impacts of Cognitive Skills on Individual nants of wages. Although cognitive test and Incomes—Developed Countries school resource data are increasingly available at the time of schooling, these are seldom The concentration on school attainment in linked to subsequent labor market informa- the academic literature, however, contrasts tion. Such analyses generally require tracking with much of the policy discussion that, individuals over time, a much more difficult even in the poorest areas, involves elements data collection scheme. Such longitudinal of “quality” of schooling. Most countries are data are, however, now becoming available. involved in policy debates about the improve- A variety of researchers are now able to ment of their schools. These debates, often document that the earnings advantages to phrased in terms of such things as teacher higher achievement on standardized tests are salaries or class sizes, rest on a presumption quite substantial. These results are derived that there is a high rate of return to schools from different specific approaches, but the in general and to quality in particular. basic underlying analysis involves estimating Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 617 a standard “Mincer” earnings function and Murnane et al. (2000) provide evidence adding a measure of individual cognitive from the High School and Beyond and the skills such as equation (7). The clearest analy- National Longitudinal Survey of the High ses are found in several references for the School Class of 1972. Their estimates sug- United States (analyzed in Hanushek 2002; gest some variation with males obtaining a see John Hillman Bishop 1989, 1991, June 15 percent increase and females a 10 per- O’Neill 1990, Jeff Grogger and Eric Eide cent increase per standard deviation of test 1995, McKinley L. Blackburn and David performance. Lazear (2003), relying on a Neumark 1993, 1995, Richard J. Murnane, somewhat younger sample from NELS88, John B. Willett, and Frank Levy 1995, Derek provides a single estimate of 12 percent. A. Neal and William R. Johnson 1996, Casey These estimates are also very close to those in B. Mulligan 1999, Murnane et al. 2000, Mulligan (1999), who finds 11 percent for the Joseph G. Altonji and Charles R. Pierret 2001, normalized AFQT score in the NLSY data.15 Murnane et al. 2001, and Edward P. Lazear Note that these returns can be thought of 2003). While these analyses emphasize dif- as how much earnings would increase with ferent aspects of individual earnings, they higher skills each and every year throughout typically find that measured achievement has the persons’ working career. Thus, the pres- a clear impact on earnings after allowing for ent value of the returns to cognitive skills is differences in the quantity of schooling, the large if these estimates can be interpreted as experiences of workers, and other factors that the structural impact, i.e., g in equation (1). might also influence earnings. In other words, These estimates are obtained fairly early in higher quality as measured by tests similar to the work career (mid-twenties to early thir- those currently being used in accountability ties), and analyses of the impact of cognitive systems around the world is closely related to skills across the entire work life are more lim- individual productivity and earnings. ited. Altonji and Pierret (2001) find that the Three recent U.S. studies provide direct impact of achievement on earnings grows with and quite consistent estimates of the impact of experience because the employer has a chance test performance on earnings (Mulligan 1999, to observe the performance of workers. The Murnane et al. 2000, Lazear 2003). These pattern of how returns change with age from studies employ different nationally represen- their analysis is shown in figure 1, where the tative data sets that follow students after they power of school attainment differences to leave school and enter the labor force. When predict differences in earnings is replaced scores are standardized, they suggest that one by cognitive skills as workers are in the labor standard deviation increase in mathematics force longer. The evidence is consistent with performance at the end of high schools trans- employers relying on readily available infor- lates into 12 percent higher annual earnings.14 mation on school attainment when they do

14 Because the units of measurement differ across tests, of measured cognitive skills on earnings by Bowles, Gintis, it is convenient to convert test scores into measures of the and Osborne (2001) finds that the mean estimate is only distribution of achievement across the population. A one- 0.07, leading them to conclude that the small gains are half standard deviation change would move somebody dwarfed by noncognitive factors. We return to this below. from the middle of the distribution (the fiftieth percen- 15 By way of comparison, we noted that estimates of tile) to the sixty-ninth percentile; a one standard deviation the value of an additional year of school attainment are change would move this person to the eighty-fourth per- typically about 10 percent. Of course, any investment centile. Because tests tend to follow a normal distribution, decisions must recognize that school attainment and test the percentile movements are largest at the center of the performance are generally produced together and that distribution. A separate review of the normalized impact costs of changing each must be taken into account. 618 Journal of Economic Literature, Vol. XLVI (September 2008)

14%

1 year of education 1 SD of academic achievement (AFQT) 12%

10%

6% Increase in earnings 4%

0% 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Work experience (years)

Figure 1. Returns to Observed Educational Quantity and Unobserved Academic Achievement over the Work Life

Notes: Based on data from National Longitudinal Survey of Youth (NLSY) and Armed Forces Qualification Test (AFQT). SD 5 standard deviation. Source: Based on Altonji and Pierret (2001). not have other information and switching to of cognitive skills is not restricted just to observations of skills and performance as that younger workers but holds across the experi- information becomes available through job ence spectrum. performance. On the other hand, Hanushek There are reasons to believe that these esti- and Zhang (2008) do not find that this pattern mates provide a lower bound on the impact of holds for a wider set of countries (although higher achievement. First, the labor market it continues to hold for the United States in experiences that are observed begin in the their data). Thus, there is some uncertainty mid-1980s and extend into the mid-1990s, currently about whether cognitive skills have but other evidence suggests that the value of differential effects on economic outcomes skills and of schooling has grown through- over the work-experience profile. out and past that period. Second, extrapo- Altonji and Pierret (2001) observe only lating from recent patterns, future general a limited age range, so that the chang- improvements in productivity are likely to ing returns which they find may well be lead to larger returns to skill. The considered thought of as leveling off after some amount analyses typically compare workers of dif- of labor market experience. Still, Hanushek ferent ages at one point in time to obtain an and Zhang (2008) find that the importance estimate of how earnings will change for any Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 619 individual. If, however, productivity improve- dents who do better in school, either through ments occur in the economy, these will tend grades or scores on standardized achieve- to raise the earnings of individuals over time. ment tests, tend to go farther in school (see, If recent patterns of skill bias in productiv- for example, Dennis J. Dugan 1976, Charles ity improvement continue, the impact of F. Manski and David A. Wise 1983). Notably, improvements in student skills are likely to Murnane et al. (2000) separate the direct rise over the work life instead of being con- returns to measured skill from the indi- stant as portrayed here (cf. Lawrence F. Katz rect returns of more schooling and suggest and Kevin M. Murphy 1992). On the other that perhaps one-third to one-half of the hand, such skill-biased change has not always full return to higher achievement comes been the case, and technology could push from further schooling. Similarly, Steven G. returns in the opposite direction. Third, Rivkin (1995) finds that variations in test cognitive skills measured by test scores are scores capture a considerable proportion prone to considerable measurement error of the systematic variation in high school as described earlier. Even if the tests were completion and in college continuation, so measuring exactly the relevant skill concept, that test score differences can fully explain we know that there are substantial errors black–white differences in schooling. Bishop in each test.16 These errors will in general (1991) and Hanushek, Rivkin, and Lori L. lead to downward biases in the estimated Taylor (1996), in considering the factors that coefficients. influence school attainment, find that indi- A limited number of additional studies are vidual achievement scores are highly corre- available for developed countries outside of lated with continued school attendance. Neal the United States. Steven McIntosh and Anna and Johnson (1996) in part use the impact of Vignoles (2001) study wages in the United achievement differences of blacks and whites Kingdom and find strong returns to both on school attainment to explain racial dif- numeracy and literacy. Because they look at ferences in incomes. Their point estimates discrete levels of skills, it is difficult to com- of the impact of cognitive skills (AFQT) pare the quantitative magnitudes directly to on earnings and school attendance appear the U.S. work. Ross Finnie and Ronald Meng to be roughly comparable to that found in (2002) and David A. Green and W. Craig Murnane et al. (2000). Jere R. Behrman et Riddell (2003) investigate returns to cogni- al. (1998) find strong achievement effects on tive skills in Canada. Both suggest that lit- both continuation into college and quality eracy has a significant return, but Finnie and of college; moreover, the effects are larger Meng (2002) find an insignificant return to when proper account is taken of the various numeracy. This latter finding stands at odds determinants of achievement. Hanushek and with most other analyses that have empha- Richard R. Pace (1995) find that college com- sized numeracy or math skills. pletion is significantly related to higher test Another part of the return to cognitive scores at the end of high school. Note also skills comes through continuation in school. that the effect of improvements in achieve- There is substantial U.S. evidence that stu- ment on school attainment incorporates

16 In most testing situations, both the reliability of the that would occur if an individual took the same test at dif- specific test and the validity of the test are considered. ferent points in time. Validity refers to the correspondence Reliability relates to how well the test measures the specific between the desired concept (skills related to productivity or material—and would include elements of specific question earnings differences) and the specific choice of test domains development and choice along with individual variations (such as mathematical concepts at some specific level). 620 Journal of Economic Literature, Vol. XLVI (September 2008) concerns about drop out rates. Specifically, Still, even in the absence of convincing higher student achievement keeps students identification strategies for cognitive skills, in school longer, which will lead among other we believe that these reduced form estimates things to higher graduation rates at all levels provide an indication of the potential earn- of schooling.17 ings impacts of policies that lead to improved Tamara Knighton and Patrick Bussière student achievement. The consistency of the (2006) find that higher scores at age fif- estimated impacts across different model teen lead to significantly higher rates of specifications, different time periods, and postsecondary schooling of Canadian nine- different samples provides support for the teen-year-olds. This finding is particularly underlying importance of cognitive skills. At interesting for the international comparisons the same time, the estimation of individual that we consider below, because the analysis earnings models with cognitive skills almost follows up on precisely the international test- always indicates that school attainment has an ing that is used in our analysis of economic independent impact.18 By the development in growth (see section 5 below). The OECD section 2, this finding would imply either that tested random samples of fifteen-year-old the impact of schooling through the noncogni- students across participating countries under tive channel or the measurement errors in cog- the Programme for International Student nitive skills was important. To the extent that Assessment (PISA) in 2000, and students tak- school attainment captures these other dimen- ing these tests in Canada were then followed sions, support for the strength of cognitive and surveyed in 2002 and 2004. skills is increased. More generally, the identifi- The argument on the other side is that none cation of causal impacts of cognitive skills is an of the studies of the impact of cognitive skills important topic for fruitful future research. on either earnings or school attainment have provided any convincing analysis of the causal 3.3 Impacts of Cognitive Skills on impact of scores. By this interpretation, the Individual Incomes—Developing estimated impact of cognitive skills should be Countries considered simply as the reduced form coefficient. Unlike the efforts to identify the rate of Questions remain about whether the clear return to school attainment through a variety impacts of cognitive skills in the United of means, this estimation has stopped without States generalize to other countries, par- providing any substantial evidence that the ticularly developing countries. The existing observed variation in cognitive skills is truly literature on returns to cognitive skills in exogenous. The concern is that other influ- developing countries is restricted to a rela- ences on earnings—say, noncognitive skills or tively limited number of mostly African coun- direct influences of families on earnings—are tries: Ghana, Kenya, Morocco, South Africa, omitted from the estimation, leading to stan- and Tanzania, as well as Pakistan. Moreover, dard omitted variables bias. a number of studies actually employ the

17 This work has not, however, investigated how achievement affects the ultimate outcomes of additional 18 A few previous analyses have shown that the impact schooling. For example, if over time lower-achieving stu- of school attainment is zero or reduced substantially after dents tend increasingly to attend further schooling, these inclusion of cognitive skills (e.g., W. Lee Hansen, Burton schools may be forced to offer more remedial courses, and A. Weisbrod, and William J. Scanlon 1970), but the the variation of what students know and can do at the end review by Bowles, Gintis, and Osborne (2001) indicates of school may expand commensurately. that this is uncommon. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 621 same basic data, albeit with different ana- Nonetheless, the overall summary is that lytical approaches, but come up with some- the available estimates of the impact of cog- what different results.19 Table 1 provides a nitive skills on outcomes suggest strong eco- simple summary of the quantitative esti- nomic returns within developing countries. mates available for developing countries. The substantial magnitude of the typical The summary of the evidence in estimates indicates that educational quality table 1 permits a tentative conclusion that concerns are very real for developing coun- the returns to cognitive skills may be even tries and that this aspect of schools simply larger in developing countries than in cannot be ignored. developed countries. This of course would Evidence also suggests that cognitive be consistent with the range of estimates skills are directly related to school attain- for returns to quantity of schooling (e.g., ment. In Brazil, a country plagued by high Psacharopoulos 1994 and Psacharopoulos rates of grade repetition and ultimate school and Patrinos 2004), which are frequently dropouts, Ralph W. Harbison and Hanushek interpreted as indicating diminishing mar- (1992) show that higher cognitive skills ginal returns to schooling. (These estimated in primary school lead to lower repetition effects reflect the increase in log earnings rates. Further, Hanushek, Victor Lavy, and associated with a one standard deviation Kohtaro Hitomi (2008) find that lower qual- increase in measured tests; for small changes ity schools, measured by lower value-added in test scores, this estimate is approximately to cognitive achievement, lead to higher the proportionate increase in earnings.) dropout rates in Egyptian primary schools. There are some reasons for caution in Thus, as found for developed countries, the interpreting the precise magnitude of esti- full economic impact of higher educational mates. First, the estimates appear to be quality comes in part through greater school quite sensitive to the estimation methodol- attainment. ogy itself. Both within individual studies and This complementarity of school qual- across studies using the same basic data, the ity and attainment also means that actions results are quite sensitive to the techniques that actually improve quality of schools will employed in uncovering the fundamental yield a bonus in terms of meeting goals for parameter for cognitive skills.20 Second, the attainment. Conversely, simply attempt- evidence on variations within developing ing to expand access and attainment, say countries is not entirely clear. For example, through starting a large number of low Jolliffe (1998) finds little impact of skills quality schools, will be self-defeating to the on farm income, while Behrman, David R. extent that there is a direct reaction to the Ross, and Richard Sabot (2008) suggest an low quality that affects the actual attain- equivalence across sectors at least on theo- ment results. retical grounds. 3.4 Evidence from the International Adult Literacy Survey

19 Unlike in much of the work in developed countries, The preceding analyses in developed coun- these studies collected both earnings information and cognitive skills data at the same time and did not rely on tries rely largely on panel data that follow longitudinal data collections. individuals from school into the labor mar- 20 The sensitivity to estimation approach is not always ket. The alternative approach as found in the the case; see, for example, Dean Jolliffe (1998). A critique and interpretation of the alternative approaches within a International Adult Literacy Survey (IALS) number of these studies can be found in Glewwe (2002). is to test a sample of adults and then to relate 622 Journal of Economic Literature, Vol. XLVI (September 2008)

Table 1 Summary of Estimated Returns to a Standard Deviation Increase in Cognitive Skills

Country Study Estimated Effecta Notes Ghana Glewwe (1996) 0.21**20.3** (government) Alternative estimation approaches yield 0.1420.17 (private) some differences; math effects shown generally more important than reading effects, and all hold even with Raven’s test for ability. Ghana Jolliffe (1998) 0.0520.07* Household income related to average math score with relatively small variation by estimation approach; effect is only observed with off-farm income, and on-farm income is not significantly related to cognitive skills. Ghana Vijverberg (1999) ? Income estimates for math and reading with nonfarm self-employment; highly variable estimates (including both positive and negative effects) but effects not generally statistically significant.

Kenya Boissiere, Knight, and 0.19**20.22** Total sample estimates: small varia- Sabot (1985); Knight and tion by primary and secondary school Sabot (1990) leavers.

Morocco Angrist and Lavy (1997) ? Cannot convert to standardized scores because use indexes of performance; French writing skills appear most important for earnings, but results depend on estimation approach. Pakistan Alderman, Behrman, 0.1220.28* Variation by alternative approaches and Ross, and Sabot (1996) by controls for ability and health; larger and more significant without ability and health controls. Pakistan Behrman, Ross, and Sabot 0.25 Estimates of structural model with (2008) combined scores for cognitive skill; significant effects of combined math and reading scores which are instrumented by school inputs

South Africa Moll (1998) 0.34**20.48** Depending on estimation method, varying impact of computation; comprehension (not shown) generally insignificant.

Tanzania Boissiere, Knight, and 0.0720.13* Total sample estimates: smaller for Sabot (1985); Knight and primary than secondary school leavers. Sabot (1990)

Notes: * Significant at 0.05 level; ** Significant at 0.01 level. a Estimates indicate proportional increase in wages from a one standard deviation increase in measured test scores. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 623 these measures to labor market experiences.21 As in the prior analyses, both school attain- An advantage of this data collection approach ment and cognitive skills are seen to enter is that it provides information about the labor into the determination of individual incomes. market experiences across a broader range of With the exception of Poland, literacy scores age and labor market experience.22 have a consistent positive impact on earnings Consistent data on basic skills of literacy (figure 2). The (unweighted) average of the and numeracy for a representative sample impact of literacy scores is 0.093, only slightly of the population aged fifteen to sixty-five less than found previously for the U.S. stud- were collected for a sample of countries ies. The United States is noticeably higher between 1994 and 1998. The analysis here than other countries and the previous U.S. combines the different IALS scores on skills studies, perhaps reflecting that these earnings into a single measure of literacy and numer- are obtained across the entire work life.24 The acy (referred to simply as literacy scores). average excluding the United States is still These data permit direct comparisons of 0.08. Again, the similarity to the prior esti- the relative importance of school attain- mates of the return to cognitive skills, coming ment and cognitive skills across countries, from very different sampling schemes in dif- although the bias toward developed econo- ferent economic markets, lends more support mies remains. Hanushek and Zhang (2008) to the significance of cognitive skills as a con- estimate returns to school attainment and sistent measure of human capital. to literacy scores for the thirteen countries The estimated impact of school attainment where continuous measures of individual across the thirteen countries is 0.059 after earnings are available. Their samples include adjusting the Mincer returns for the literacy full-time workers between twenty-six and scores and down from 0.071 when cognitive sixty-five years of age. The dependent vari- skills are not considered. As noted in sec- able is the logarithm of annual earnings tion 2, however, these estimates are difficult from employment, and control variables are to interpret because of the potential role of gender, potential experience and its square, omitted variables in determining unmeasured and an indicator for living in rural area. cognitive and noncognitive skills. Figures 2 and 3 provide the relevant sum- More interestingly, Hanushek and Zhang mary information on the returns to cogni- (2008) can estimate a Mincer earnings func- tive skills, estimated in a model that jointly tions along the lines of equation (4) where the includes school attainment and literacy scores, measured literacy scores are excluded but the and on the returns to school attainment.23 model is augmented by measures of families,

21 This design was subsequently repeated in 2003 with ferent time periods to be equivalent in quality terms. This the Adult Literacy and Lifeskills Survey (ALL), but only procedure involves equating the marginal impact of a year six countries participated and the data were unavailable of schooling on literacy scores across time (after allow- for this study. The work in developing countries is also ing for other influences on literacy scores). All references more likely to rely upon a single cross section of workers to school attainment here refer to their quality-adjusted who are tested contemporaneously. school attainment. 22 This approach does also present some complications, 24 The previous discussion of the analysis by because the individuals of different ages have both dif- Altonji and Pierret (2001) can reconcile the different adult learning experiences and different times of ference in quantitative magnitudes of the impact attending school of possibly different quality. Hanushek of cognitive skills on U.S. earnings. Hanushek and Zhang (2008) consider these alternatives, but they do and Zhang (2008) find that the impact of literacy not change the qualitative results about the impact of cog- scores rises from that for the youngest workers, nitive skills that are presented here. consistent with Altonji and Pierret. They do not, how- 23 An element of the analysis in Hanushek and Zhang ever, find support for this statistical discrimina- (2008) is adjusting the years of schooling obtained in dif- tion hypothesis in the remaining twelve countries. 624 journalof Economic Literature, Vol. XLVI (September2008)

0,26 deviation

standard

per

Increase

XLS. Netherlands Switzerland Chile Finland Germany Hungary Italy Denmark Norway Czech Sweden Poland Rep.

Figure 2. Returns to Cognitive Skills, International Adult Literacy Survey

Source: Hanushek and Zhang (2008).

0.12

csoost Returus to quality-adjusted schooling ecscses Returns accounting for family inputs and ability

0.10

0.08

0.06

0.04 0.02

Chile U.S. Poland Germany Ttaly Czech Switzerland Deumark Hungesy Sweden Norway Netherlands Finland Rep.

Figure 3. Impact of Controlling for Nonschool Taputs on the Estimated Returns to School Attainment, international Adult Literacy Survey

Source: Hanushek and Zhang (2008).

Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 625 school quality, and ability. This permits direct an individual’s cognitive skills yield earn- estimation of the impact of school attainment ings changes similar to those estimated in on wages (conditional on the adequate model- the various models? The experiment we have ing of the factors in equation (2)). As seen from in mind is randomly introducing a different figure 3, this adjustment to the estimated level of cognitive skills across a group of indi- returns to schooling is more significant than viduals and then observing subsequent labor just incorporating literacy scores in the model. market outcomes. In the case of estimation From this figure, it is apparent that the aver- of the returns to school attainment, exten- age returns fall significantly (from 0.071 to sive but highly focused research has delved 0.044) while the variation across countries is into these causality questions (Card 1999). As also lessened considerably. These adjustments sketched in section 2, however, more general are also more significant than is typical in the issues such as systematic variations in school literature concerned with the estimation the quality or other sources of educational out- returns to schooling (Card 1999). comes and skills have not been important The literacy tests in IALS are designed in these analyses. These latter issues are the to measure quite basic skills only, and yet motivation for our work and the reason for the differences are strongly associated with our concentration on cognitive skills as a higher earnings.25 These results, from a broad direct measure of human capital. age spectrum across a number of countries, With cognitive skills, no similar literature reinforce the importance of cognitive skills. on causality questions exists, but the potential The sample of countries for the IALS problems are considerably different. Most of unfortunately contains just one developing the cognitive skills tests used in the devel- country—Chile. Nonetheless, it is suggestive oped country studies, with the exception of that the returns both to quantity of school- the IALS-type sampling, are given at a date ing and cognitive skills exceed those found before the labor market experiences—elim- across the countries with the exception of the inating the reverse causation possibility that United States. In the three transition econo- higher income leads individuals to do things mies (Czech Republic, Hungary, and Poland), that raise their test scores.26 Nevertheless, as the returns to school attainment are also near was developed in section 2, this fact alone the top of the sample, but the returns to cog- does not solve all of the interpretative issues. nitive skills are noticeably lower—perhaps Two other factors threaten the interpretation reflecting institutional aspects of their labor of the estimated effects of cognitive skills: markets. measurement error in tests and other correlated but omitted influences on earnings. 3.5 Causality As is well known, test scores inherently For policy purposes, we are interested in have errors in measuring the underlying a rather simple question: Would changing cognitive domains that are being tested. A

25 It should be noted, however, that results from dif- simple correlation of 0.73. This consistency suggests that ferent tests, even when described as measuring dif- the available assessments of cognitive skills may cap- ferent parts of the distribution of cognitive skills, tend ture a wider range of knowledge and skills than would to be highly correlated—particularly at the country be suggested by the descriptions of the individual tests. level. Hanushek and Zhang (2008) correlate the literacy 26 The IALS sampling raises the concern that tests test results from IALS (identified as measuring basic change with age, because of continual learning or simple age skills)with the higher order math test results from the depreciation of skills and knowledge. An investigation of this Third International Mathematics and Science Study by Hanushek and Zhang (2008) suggests that these are not (TIMSS) for comparable age groups in 1995 and find a large concerns in the estimation of the earnings functions. 626 Journal of Economic Literature, Vol. XLVI (September 2008) portion of this is simply that individuals will The implicit inclusion of the correlated por- obtain somewhat different scores if tested tion of the different skills does not lead per again with the same test instrument or with se to large problems as a proxy for overall a different instrument designed to measure labor market skills. It is a more significant the same concepts. This type of error is a problem if we subsequently consider, say, characteristic of the measurement technol- school policies that might operate on just ogy and, in these specific applications, is cognitive skills and not also on the noncog- likely to lead to a standard downward bias nitive skills. in the estimated impact of cognitive skills. As is generally the case, the analyses consid- A second issue is the specificity of the indi- ered here cannot rule out a variety of factors vidual tests employed across the underly- that might bias the estimates and jeopardize ing research; that is, most work relies on the interpretation. Nonetheless, we return specific subject matter tests at a given level to one simple finding: Under a wide range of of difficulty. Again, this is likely to be pres- different labor market conditions, modeling ent quite generally in the various empirical approaches, and samples of individuals, cog- applications. Its impact on the estimates nitive skills are directly related to individual is less clear, because it will depend on the earnings and, moreover, there is a consis- structure of specific tests. On the other tency even in the point estimates. hand, because general cognitive skills tests If we take these estimates as indicating for one subject tend to be very highly cor- a causal relationship, the most important related with the scores in other subjects issue for policy purposes is the source of for individuals, this problem may not be any test score differences. It is natural to overly important. Finally, because indi- believe that schools have an influence on vidual skills may change between the time tests, but clearly other factors also enter. of testing and the period of observed earn- The extensive investigations of the determi- ings, additional error may enter, but its nants of achievement differences indicate implications are unclear in the abstract. that parents, peers, neighborhoods, and More important concerns come from other factors enter along with school factors other omitted factors that might indepen- in determining achievement (see Hanushek dently influence earnings but be corre- 2002). Thus, most importantly, it is inap- lated with cognitive skills. One candidate, propriate to interpret test scores as simply explored early by Bowles and Gintis (1976) reflecting school quality or school policy. In and Bowles, Gintis, and Osborne (2001) and particular, if we can find approaches that extended recently by Heckman, Stixrud, increase skills reliably—whether school and Urzua (2006), is noncognitive skills based or not, the available evidence strongly (see also Cunha et al. 2006). The Heckman, indicates that individual earnings and pro- Stixrud, and Urzua (2006) analysis explores ductivity will also increase. the impact of various measures of noncog- The other side of this issue is also impor- nitive skills (indices of perceived self-worth tant, however. Using just quantity of school- and of one’s control over own life) within ing in the earnings analyses assumes that standard earnings determination models formal schooling is the only source of skill and finds that both cognitive and noncogni- development. But, if a variety of other inputs tive skills influence labor market outcomes. such as families or peers is also important It is less clear, however, how omission of in the formation of human capital, simple these factors might bias the estimates of the years of schooling is subject to this addi- impacts of cognitive skills considered here. tional source of omitted variables bias. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 627

3.6 Income Distribution Again, these studies do not attempt to describe the causal structure, and it would One implication of the impact of cognitive be inappropriate to attribute the variance in skills on individual earnings is that the distri- earnings simply to differences in the quan- bution of those skills in the economy will have tity or quality of schooling. Nonetheless, to a direct effect on the distribution of income. the extent that these contribute to variations Cognitive skills by themselves do not of course in cognitive skills, it is fair to conclude that determine the full distribution, because other policies aimed at improving school quality factors such as labor market institutions, taxes, (and educational outcomes) will affect the and the like enter. But the importance of skills income distribution. is becoming increasingly evident. Very suggestive evidence on the impact of 4. Quantity of Schooling and skills on the income distribution comes from Economic Growth Stephen Nickell (2004). Nickell, using the Given the microeconomic evidence of the IALS data, considers how differences in the productivity-enhancing effects of education distribution of incomes across countries are and skills, it is natural to extend the view to affected by the distribution of skills and by the macroeconomic perspective of long-run institutional factors including unionization economic growth of countries. Our approach and minimum wages. While union coverage is to the education–growth relationship is statistically significant, he concludes that “the the same as that to the education–earn- bulk of the variation in earnings dispersion is ings relationship. We pursue a simple model generated by skill dispersion” (p. C11).27 that aggregate human capital is relevant to The impact of the skill distribution across growth. Our analysis is designed to compare countries is shown dramatically in figure 4, and contrast simple school attainment mea- which is derived from a comparison of the sures, which have been the near universal dispersion of wages and the dispersion of measure of human capital, with direct inter- prose literacy scores (each measured as the national assessments of cognitive skills. This ratio of the ninetieth to the tenth percentile). section introduces the broad literature based The tight pattern around the regression line on school attainment; the next section pro- reflects a simple correlation of 0.85 (which is vides the contrast with the use of cognitive not affected by including the other institu- skills measures. tional factors). From a theoretical viewpoint, there are at Other studies have also concluded that skills least three mechanisms through which edu- have an increasing impact on the distribution cation may affect economic growth. First, of income (e.g., Chinhui Juhn, Murphy, and just as in the micro perspective, education Brooks Pierce 1993). In the United States, increases the human capital inherent in the the distribution of incomes within schooling labor force, which increases labor produc- groups has been rising (Levy and Murnane tivity and thus transitional growth towards 1992), i.e., holding constant schooling attain- a higher equilibrium level of output (as in ment, the income distribution has become augmented neoclassical growth theories, more dispersed in reflection of growing cf. N. Gregory Mankiw, David Romer, and rewards to individual skills. David N. Weil 1992). Second, education may increase the innovative capacity of the economy, and the new knowledge on new 27 Jose De Gregorio and Jong-Wha Lee (2002) find a (somewhat weaker) positive association between inequal- technologies, products and processes pro- ity in years of schooling and income inequality. motes growth (as in theories of endogenous 628 Journal of Economic Literature, Vol. XLVI (September 2008)

4.5

64" $"/

4.0

3.5 *3& 6,

3.0

Earnings inequality "64

48* /&5 2.5 '*/ (&3 #&- %&/ 48& 2.0 /03

1.5 1.3 1.5 1.7 1.9 Test score inequality

Figure 4. Inequality of Test Scores and Earnings

Notes: Measure of inequality is the ratio of ninth decile to the first decile in both cases; test performance refers to prose literacy in the International Adult Literacy Survey. Source: Based on Nickell (2004). growth, cf., e.g., Robert E. Lucas 1988, Edmund Phelps 1966, Jess Benhabib and Paul M. Romer 1990a, Philippe Aghion Mark M. Spiegel 2005). and Peter Howitt 1998). Third, education 4.1 Results of Initial Cross-Country may facilitate the diffusion and transmis- Growth Regressions sion of knowledge needed to understand and process new information and to imple- Just as in the literature on microeco- ment successfully new technologies devised nomic returns to education, the majority of by others, which again promotes economic the macroeconomic literature on economic growth (cf., e.g., Richard R. Nelson and growth that tries to test these predictions Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 629 employs the quantitative measure of years of cross-country differences in the quality of schooling, now averaged across the labor of education and in the strength of family, force.28 Early studies used adult literacy rates health, and other influences is probably the (e.g., Costas Azariadis and Allan Drazen major drawback of such a quantitative mea- 1990, Romer 1990b) or school enrollment sure of schooling, and we come back to this ratios (e.g., Robert J. Barro 1991, Mankiw, issue in great detail below. Romer, and Weil 1992, Ross Levine and The standard method to estimate the David Renelt 1992) as proxies for the human effect of education on economic growth is capital of an economy. (See Woessmann to estimate cross-country growth regressions 2003 for a survey of measurement and speci- where countries’ average annual growth in fication issues from early growth accounting gross domestic product (GDP) per capita over to current cross-country growth regressions.) several decades is expressed as a function of These were followed by attempts to measure measures of schooling and a set of other vari- average years of schooling based on perpet- ables deemed to be important for economic ual inventory methods (cf. Frederic F. Louat, growth. Following the seminal contributions Dean T. Jamison, and Lawrence J. Lau 1991, by Barro (1991, 1997) and Mankiw, Romer, Vikram Nehru, Eric Swanson, and Ashutosh and Weil (1992),30 a vast early literature of Dubey 1995). An important innovation by cross-country growth regressions has tended Barro and Lee (1993, 2001) was the develop- to find a significant positive association ment of internationally comparable data on between quantitative measures of schooling average years of schooling for a large sample and economic growth (for extensive reviews of countries and years, based on a combina- of the literature, see, e.g., Topel 1999, Temple tion of census or survey data on educational 2001, Krueger and Lindahl 2001, Barbara attainment wherever possible and using lit- Sianesi and John Van Reenen 2003). To give eracy and enrollment data to fill gaps in the an idea of the robustness of this association, census data. in the recent extensive robustness analysis by But, as discussed, using average years of Xavier Sala-i-Martin, Gernot Doppelhofer, schooling as the education measure implicitly and Ronald I. Miller (2004) of sixty-seven assumes that a year of schooling delivers the explanatory variables in growth regres- same increase in knowledge and skills regard- sions on a sample of eighty-eight countries, less of the education system. For example, a primary schooling turns out to be the most year of schooling in Papua New Guinea is robust influence factor (after an East Asian assumed to create the same increase in pro- dummy) on growth in GDP per capita in ductive human capital as a year of schooling 1960–96. in Japan. Additionally, this measure assumes A closely related literature weights years of that formal schooling is the primary (sole) schooling by parameters from microeconomic source of education and, again, that varia- Mincer earnings equations (see section 3.1 tions in nonschool factors have a negligible above) to construct a measure of the stock of effect on education outcomes.29 This neglect human capital, which is then used in growth

28 More precisely, the most commonly used measure is 30 Jonathan Temple and Woessmann (2006) show that average years of schooling in the working-age population, the significantly positive effect of education that Mankiw, usually defined as the population aged fifteen years and Romer, and Weil (1992) find does not depend on their over, instead of the actual labor force. often criticized use of an education flow measure based on 29 If the omitted variables are uncorrelated with enrollment rates, but can be replicated when using years school attainment—an unlikely event—no bias would be of schooling as a measure of the level of human capital in introduced. their model. 630 Journal of Economic Literature, Vol. XLVI (September 2008) accounting and development accounting real GDP per capita in 1960–2000 comes exercises. These use a given macroeconomic from the latest update (version 6.1) of the production function together with parameter Penn World Tables by Alan Heston, Robert estimates from other research to calculate the Summers, and Bettina Aten (2002).32 Figure share of cross-country differences in growth 5 plots the average annual rate of growth in or levels of income which can be accounted GDP per capita over the forty-year period for by cross-country differences in education against years of schooling at the beginning (see Peter J. Klenow and Andres Rodriguez- of the period for a sample of ninety-two Clare 1997 and Robert E. Hall and Charles countries. Both growth and education are I. Jones 1999 for examples). expressed conditional on the initial level of Because this literature has been extensively output, to account for the significant condi- reviewed elsewhere (see references above), tional convergence effect.33 we focus just on a few of the most impor- The regression results depicted by figure 5 tant issues that emerge in the literature with imply that each year of schooling is statisti- respect to the influence of human capital. cally significantly associated with a long-run growth rate that is 0.58 percentage points higher. The association is somewhat lower 4.2 More Recent Evidence on the Effects (at 0.32) but still significant when regional of Levels of and Growth in Years of dummies are added to the regression. The Schooling positive association is substantially larger in the sample of non-OECD countries (at 0.56) To frame the discussion of cognitive skills than in the sample of OECD countries (at that follows, we produce our own estimates 0.26). Alternatively, results based on the sam- of common models that incorporate school ples of countries below the median of initial attainment. These estimates use improved output and above the median are in line with school attainment data and extend the obser- the pattern of larger returns to education in vation period for economic growth through developing countries. 2000. However, after controlling for the institu- We use an extended version of the edu- tional differences reflected in the openness of cation data by Daniel Cohen and Marcelo each country and in the security of property Soto (2007), representing the average years rights, the association with school attainment of schooling of the population aged fifteen 31 to sixty-four. As discussed below, one line 32 Jan Hanousek, Dana Hajkova, and Randall K. Filer of investigation has been the impact of mis- (2004) argue that growth rates are better calculated using measurement of the quantity of education the IMF International Finance Statistics. Our results in this paper are not significantly affected by using these on growth; the Cohen and Soto (2007) data alternative growth measures. improve upon the original quantity data 33 Added-variable plots show the association between by Barro and Lee (1993, 2001). Data on two variables after the influences of other control variables are taken out. Thus, both of the two variables are first regressed on the other controls (in this case, initial- GDP). Only the residual of these regressions, which is the 31 Eliot A. Jamison, Jamison, and Hanushek (2007) part of the variation in the two variables which cannot supplement the Cohen and Soto attainment series with be accounted for by the controls, is used in the graph. In imputed data based on the Barro and Lee series in order so doing, the graph makes sure that the depicted asso- to expand the number of countries available for the growth ciation between the two variables is not driven by the analysis. This approach adds eight countries to the growth control variables. The procedure is numerically equiva- analysis. For details of the extension along with the basic lent to including the other controls in a multivariate data on educational attainment, see Jamison, Jamison, regression of the dependent variable (growth) on the and Hanushek (2006). independent variable under consideration in the graph. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 631

SGP TWN

4 KOR BWA HKG

THA CYP CHN BRB JPN 2 PRT MYS IRL MUS ROM IDN ESP TUN GRC ASU PAK DOM INDITASYEGTMITA AURITR MUS ISR MAGGABYASURGY ISLIND BEL TUR FRA PAN CERORTITO NLD LSO 0 IRN USARAGRAN COL ZWE DUEASUUWE ASU NPL ASUMEH RY Conditional growth DZA UGA ECU GTM CRIPRGIRGSEHSEHSEA PHL ZAFURIRY PER CHE NZARG JAM BIASTAET IT TZA CIV BENOMR HND BOL 2 MGOTU BDI SEN VEN ZMB NGAMDG MOZ coef ฀0.581, se ฀0.095, t 6.10 NIC NER 4

4 2 0 2 4 6 Conditional years of schooling

Figure 5. Added-variable Plot of Growth and Years of Schooling without Test Score Controls

Notes: Added-variable plot of a regression of the average annual rate of growth (in percent) of real GDP per capita in 1960–2000 on average years of schooling in 1960 and the initial level of real GDP per capita in 1960. Own calculations.

becomes substantially smaller and turns Benhabib and Spiegel (1994) and dis- insignificant. It is close to zero when the total cussed in Barro and Sala-i-Martin (2004), fertility rate is controlled for. Thus, while found a positive effect of educational there is a clear positive association between levels, but not of changes in education. years of schooling and growth in the latest However, Temple (1999) shows that in the available data, it is also somewhat sensitive to latter case, an existing positive association model specification. was hidden by a few unrepresentative out- A considerable controversy has emerged lying observations. Considerable evidence in the literature about whether it is the has also emerged that there was substan- level of years of schooling (as would be tial measurement error in the education predicted by several models of endog- data (cf. Krueger and Lindahl 2001), and enous growth) or the change in years it is well known that measurement error of schooling (as would be predicted in affects results based on changes in vari- basic neoclassical frameworks) which is ables even more than results based on the more important driver of economic their levels. Subsequent evidence suggests growth. The early evidence, such as in that both levels of and changes in years of 632 Journal of Economic Literature, Vol. XLVI (September 2008) schooling may show a positive association tation for countries close to the technological with growth (cf. Norman Gemmell 1996, frontier. As a consequence, the composition of Topel 1999, Krueger and Lindahl 2001). human capital between basic and higher edu- More recently, two studies have tried to cation may be important, with initial levels of overcome some problems of mismeasure- education being more important for imitation ment in the early Barro–Lee data on years and higher education being more important of schooling: Angel de la Fuente and Rafael for innovation. Vandenbussche, Aghion, and Doménech (2001, 2006) for the sample of Meghir (2006) provide evidence from a panel OECD countries and Cohen and Soto (2007) of OECD countries in line with this argu- for a broader sample of countries (and the ment, which—when applied to developing data that we use here). Both studies find countries—might suggest that a focus on basic robust evidence of a positive association skills seems warranted for developing coun- between changes in education and economic tries. We will come back to the issue of the growth. Even more recently, Ciccone and relative importance of basic versus advanced Elias Papaioannou (2005) find strong sup- skills in more detail in section 5.5 below. port for both the human capital level and the Two more skeptical studies raise note- human capital accumulation effects using worthy caveats, and we will return to each cross-country industry-level data that allow of them below. First, Mark Bils and Klenow them to control for country-specific and (2000) raise the issue of causality, suggesting industry-specific effects. that reverse causation running from higher When we add the change in years of economic growth to additional education schooling over 1960–2000 to the specifica- may be at least as important as the causal tion depicted in figure 5 and similar speci- effect of education on growth in the cross- fications, it never turns significant with the country association. We address the issue sole exception of the sample of twenty-three in cross-country regressions in section 5.2 OECD countries, and there it is sensitive to below. Second, one of the conclusions that the inclusion of Korea. (Because of the pos- Lant Pritchett (2001, 2006) draws from the sibly substantial amount of mismeasurement fragility of the evidence linking changes in in the education data, though, the results on education to economic growth is that it is the first-differenced data on changes in edu- important for economic growth to get other cation may well suffer). things right as well, in particular the insti- Thus, while recent research tends to find a tutional framework of the economy. We positive effect of schooling quantity on eco- address this issue in section 5.6 below. nomic growth, it seems beyond the scope of current data to draw strong conclusions 5. Cognitive Skills and Economic Growth about the relative importance of different mechanisms by which schooling quantity 5.1 A Review of the Basic Results may affect economic growth. However, several recent studies suggest that education is The most important caveat with the lit- important both as an investment in human erature on education and growth reviewed capital and in facilitating research and devel- in the preceding section, though, is that it opment and the diffusion of technologies. With sticks to years of schooling as its measure of respect to the relative importance of the lat- human capital at the neglect of qualitative ter two mechanisms, Jerome Vandenbussche, differences in ensuing knowledge. As dis- Aghion, and Costas Meghir (2006) suggest cussed, this neglect probably misses the that innovation is more important than imi- core of what education is all about. And Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 633 this neglect is clearly more severe in cross- The precise scaling on the transformed country comparisons than in analyses within metric is of course subject to consider- countries (such as the prior work on earnings able noise, in particular for the early tests determination). Rather than just counting and for countries performing far below the students’ average years of schooling, it seems international mean. The tests are usually not crucial to focus on how much students have developed to provide reliable estimates of learned while in school when estimating the performance in the tails of the achievement effect of education on economic growth. distribution, which would be relevant for very From the mid-1960s to today, international poorly performing countries. However, the agencies have conducted many international rough pattern of overall performance should tests of students’ performance in cogni- not be severely affected by the rescaling. For tive skills such as mathematics and science. example, the average performance level of The different tests contain both “academic” Peruvian students on PISA 2002 where no questions related to the school curricula as rescaling is involved is 292 in math, 333 in well as “life skill” questions requiring prac- science and 327 in reading. tical applications to real-world phenomena. Over the past ten years, empirical growth Employing a rescaling method that makes research demonstrates that consideration performance at different international tests of cognitive skills alters the assessment of comparable, we can use performance on these the role of education and knowledge in the standardized tests as a measure of cognitive process of economic development dramati- skills. (See the appendix to this paper for cally. When using the data from the inter- details on testing and rescaling of the data.) national student achievement tests through Figure 6 presents average student perfor- 1991 to build a measure of labor force mance on twelve testing occasions, combin- quality, Hanushek and Dennis D. Kimko ing results from a total of thirty-six separate (2000)—first released as Hanushek and test observations at different age levels and in Dongwook Kim (1995)—find a statistically different subjects, on the transformed scale and economically significant positive effect which maps performance on each test to the of the cognitive skills on economic growth scale of the recent PISA international test. in 1960–90 that dwarfs the association This scale has a mean of 500 and a standard between quantity of education and growth. deviation of 100 among the OECD countries Thus, even more than in the case of educa- in PISA. To facilitate comparisons, the within- tion and individual earnings, ignoring dif- country standard deviation of PISA test scores ferences in cognitive skills very significantly ranges between 80 and 108 in mathematics misses the true importance of education for in the OECD countries; the U.S. value is 98. economic growth. Their estimates suggest As is obvious from the figure, the developing that one country-level standard deviation countries that ever participated in one of the higher test performance would yield around tests perform dramatically lower than any one percentage point higher annual growth country in the group of OECD countries. The rates. (The country-level standard deviation variation in cognitive skills that exists among is equivalent to forty-seven test-score points OECD countries is already substantial, but in PISA 2000 mathematics, the scale used in the magnitude of the difference to developing figure 6.) countries in the average amount of learning Their estimate stems from a statistical that has taken place after a given number of model that relates annual growth rates of years of schooling dwarfs any within-OECD real GDP per capita to the measure of cogni- difference. tive skills, years of schooling, the initial level 634 Journal of Economic Literature, Vol. XLVI (September 2008)

550 —

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'*.4'*44'*344*.4 4*444*34 5*.445*.441*4"1*3-45*.441*4"

Figure 6. Adjusted Performance on International Student Achievement Tests

Source: Hanushek and Woessmann (forthcoming), based on the different tests; see appendix for details. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 635 of income, and a wide variety of other control tional achievement measures are taken into variables (including in different specifications account, and to over 60 percent in samples the population growth rates, political mea- with reasonable data quality. sures, openness of the economies, and the Extensions of the measure of Hanushek like). Hanushek and Kimko (2000) find that and Kimko (2000) and its imputation in adding the international achievement test Woessmann (2003) are also used in the measures to a base specification including cross-country growth regressions by Barry P. only initial income and educational quantity Bosworth and Susan M. Collins (2003) and boosts the variance in GDP per capita among in the cross-country industry-level analysis the thirty-one countries in their sample that by Ciccone and Papaioannou (2005). Both can be explained by the model from 33 to also find that measured cognitive skills 73 percent. The effect of years of school- strongly dominate any effect of educational ing is greatly reduced by including cogni- quantity on growth.34 Serge Coulombe, Jean- tive skills, leaving it mostly insignificant. François Tremblay, and Sylvie Marchand At the same time, adding the other factors (2004) and Coulombe and Tremblay (2006) leaves the effects of cognitive skills basically use test-score data from the International unchanged. Adult Literacy Survey (see section 3.4 above) Several studies have since found very in a panel of fourteen OECD countries, con- similar results. Another early contribution, firming the result that the test-score mea- by Doo Won Lee and Tong Hun Lee (1995), sure outperforms quantitative measures of found an effect size similar to Hanushek education. and Kimko (2000) using data from the Jamison, Jamison, and Hanushek (2007) 1970–71 First International Science Study further extend the Hanushek and Kimko on the participating seventeen countries, (2000) analysis by using the mathematics also leaving quantitative measures of edu- component of the transformed and extended cation with no significant effect on growth. tests shown in figure 6, replicating and Using a more encompassing set of interna- strengthening the previous results by using tional tests, Barro (2001) also finds that, test data from a larger number of countries, while both the quantity of schooling and controlling for a larger number of potentially test scores matter for economic growth, confounding variables, and extending the measured cognitive skills are much more time period of the analysis. Using the panel important. Employing the measure of cog- structure of their growth data, they suggest nitive skills developed by Hanushek and that cognitive skills seem to improve income Kimko (2000) in a development accounting levels mainly though speeding up technolog- framework, Woessmann (2002, 2003) finds ical progress, rather than shifting the level that the share of cross-country variation in of the production function or increasing the levels of economic development attribut- impact of an additional year of schooling. able to international differences in human In sum, the existing evidence suggests that capital rises dramatically when cognitive what students know as depicted in tests of skills are taken into account. Building on E. Gundlach, D. Rudman, and Woessmann 34 Bosworth and Collins (2003) cannot distinguish (2002), this work analyzes output per the effect of cognitive skills from the effect of quality of worker in 132 countries in 1990. The varia- government institutions. The analysis in section 5.6 below tion that can be attributed to international shows, however, that they can be separated when we use our new measure of cognitive skills that also extends the differences in human capital rises from 21 country sample by several additional data points on inter- percent to 45 percent once the interna- national tests scores. 636 Journal of Economic Literature, Vol. XLVI (September 2008) cognitive skills is substantially more impor- But in fact, even if the East Asian countries tant for economic growth than the mere are excluded from the analysis, a strong— quantity of schooling. albeit slightly smaller—relationship is still observed between growth and test perfor- 5.2 Issues of Endogeneity mance. This consistency of results across Growth modeling is naturally subject to a alternative samples suggests the basic impor- common concern: Do the identified factors tance of cognitive skills. Our current work, represent truly causal influences or mere reported below, replicates this test of exclud- associations that will not affect growth if ing the East Asian countries in the context of altered by policy? The basic concerns were extended growth analyses and reaches simi- set out in section 2. lar conclusions. Causality is difficult to establish conclu- Another concern is that other factors sively within the aggregate growth context, that affect growth, such as efficient mar- but it is possible to rule out the most impor- ket organizations, are also associated with tant alternative hypotheses about the nature efficient and productive schools—so that, of the cognitive skills–growth relationship. again, the test measures might really be a Many concerns about the nature of the rela- proxy for other attributes of the country. To tionship of cognitive skills and growth are investigate this, Hanushek and Kimko con- addressed in detail by Hanushek and Kimko centrate on immigrants to the United States (2000). They conclude that causation con- who received their education in their home cerns are very different in the case of cogni- countries. They find that immigrants who tive skills than with quantity of schooling and were schooled in countries that have higher are much less likely to be a significant issue scores on the international math and science in interpreting the results. Because these examinations earn more in the United States. arguments are also important for assessing On the other hand immigrants receiving our results below, we begin by describing part or all of their schooling in the United the Hanushek and Kimko investigations. In States do not see any earnings advantage simplest terms, by showing that the estima- linked to the cognitive skills of their home tion is robust to major alternative specifica- country. This analysis makes allowance for tions while also not being the result of other any differences in school attainment, labor hypothesized mechanisms, they provide market experience, or being native English- strong additional support for the validity of language speakers. In other words, skill dif- their central interpretation. ferences as measured by the international One common concern in analyses such as tests are clearly rewarded in the U.S. labor theirs (and ours here) is that schooling might market, reinforcing the validity of the tests as not be the actual cause of growth but, in fact, a measure of individual skills and productiv- may just reflect other attributes of the econ- ity (and also discounting the notion that the omy that are beneficial to growth. For exam- economic performance of these immigrants ple, the East Asian countries consistently simply reflects the culture and family prac- score very highly on the international tests tices of the immigrants). (see figure 6), and they also had extraordi- Finally, the observed relationships could narily high growth over the 1960–90 period. simply reflect reverse causality, that is, that It may be that other aspects of these East countries that are growing rapidly have the Asian economies have driven their growth added resources necessary to improve their and that the statistical analysis of labor force schools and that better student performance quality simply is picking out these countries. is the result of growth, not the cause of Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 637 growth. As a simple test of this, Hanushek the most important factor sustaining the and Kimko investigated whether the interna- growth of the U.S. economy is the openness tional math and science test scores were sys- and fluidity of its markets. The United States tematically related to the resources devoted maintains generally freer labor and product to the schools in the years prior to the tests. markets than most countries in the world. They were not. If anything, their results sug- The government generally has less regulation gested relatively better performance in those on firms, and trade unions are less extensive countries spending less on their schools. than those in many other countries. Even More recent work corroborates the result of broader, the United States has generally no resources-skills relationship across coun- less intrusion of government in the opera- tries (see Hanushek and Woessmann 2007). tion of the economy, including lower tax One final issue warrants consideration: rates and minimal government production The United States has never done well on through nationalized industries. These fac- these international assessments, yet its tors encourage investment, permit the rapid growth rate has been very high for a long development of new products and activities period of time. The reconciliation is that by firms, and allow U.S. workers to adjust quality of the labor force is just one aspect to new opportunities. While identifying the of the economy that enters into the determi- precise importance of these factors is diffi- nation of growth. A variety of factors clearly cult, a variety of analyses suggest that such contribute, and these factors work to over- market differences could be very important come any deficits in quality. These other explanations for differences in growth rates factors may also be necessary for growth. (see, for example, Anne O. Krueger 1974, In other words, simply providing more or World Bank 1993, Stephen L. Parente and higher-quality schooling may yield little in Edward C. Prescott 1994, 1999). the way of economic growth in the absence Second, over the twentieth century, the of other elements, such as the appropriate expansion of the education system in the market, legal, and governmental institutions United States outpaced that around the to support a functioning modern economy. world. The United States pushed to open Past experiences investing in less developed secondary schools to all citizens (Claudia countries that lack these institutional fea- Goldin and Katz 2008). With this came also tures suggest that schooling is not necessar- a move to expand higher education with ily itself a sufficient engine of growth (e.g., the development of land grant universities, William Easterly 2001, Pritchett 2001). the G.I. bill, and direct grants and loans to We take up these issues about quality of students. More schooling with less learning societal institutions in detail below, because each year still yielded more human capi- the evidence suggests that they are ver y impor- tal than found in other nations that have tant and could potentially distort the analysis less schooling but more learning in each of of the impacts of human capital. Here, how- those years. (This advantage has, however, ever, we briefly consider the U.S. situation, clearly ended as many OECD countries have both because it sets the stage for more recent expanded schools to exceed the quantity of analyses and because it helps to provide some schooling found in the United States; see balance to the overall picture of growth. Organisation for Economic Co-operation Three other factors immediately come to and Development 2003.) mind as being important in U.S. growth and Third, the analysis of growth rates across as potentially masking to detrimental effects countries emphasizes quality of the pri- of low school quality. First, almost certainly mary and secondary schools of the United 638 Journal of Economic Literature, Vol. XLVI (September 2008)

States. It does not include any measures of in figure 6.36 We interpret this as a proxy the quality of U.S. colleges. By most evalu- for the average educational performance of ations, U.S. colleges and universities rank the whole labor force. This measure encom- at the very top in the world.35 A number of passes overall cognitive skills, not just those models of economic growth in fact empha- developed in schools. Thus, whether skills are size the importance of scientists and engi- developed at home, in schools, or elsewhere, neers as a key ingredient to growth. By they are included in the growth analyses. these views, the technically trained college As in the analyses underlying figure 5, the students who contribute to invention and to source of the income data is version 6.1 of the development of new products provide a spe- Penn World Tables (cf. Heston, Summers, and cial element to the growth equation. Here, Aten 2002), and the data on years of school- again, the United States appears to have the ing is an extended version of the Cohen and best programs. Soto (2007) data. The basic result is reported in column 2 of 5.3 Some New Evidence table 2 and depicted graphically in figure 7 To provide the most up-to-date picture, we (see section 4.2 above for a brief technical extend the existing evidence in several ways. description of added-variable plots). After The new evidence adds additional interna- controlling for the initial level of GDP per tional student achievement tests not previ- capita and for years of schooling, the test- ously available and uses the most recent data score measure features a statistically signifi- on economic growth which allow an analysis cant effect on the growth in real GDP per for an even longer time period (1960–2000). capita in 1960–2000. According to this spec- Furthermore, the new data extend the sam- ification, test scores that are larger by one ple of countries with available test-score and standard deviation (measured at the student growth information from thirty-one coun- level across all OECD countries in PISA) are tries in Hanushek and Kimko (2000) to fifty associated with an average annual growth countries (see the appendix to this paper for rate in GDP per capita that is two percent- details on the data). In the subsequent sec- age points higher over the whole forty-year tions, we will also use these data to analyze period. Below we discuss the quantitative effects of the distribution of cognitive skills size of these estimates. at the bottom and at the top on economic When cognitive skills are added to a model growth, as well as interactions between that just includes initial income and years of cognitive skills and the institutional infra- schooling (column 1 of table 2), the share of structure of an economy. variation in economic growth explained by Our measure of cognitive skills is a sim- the model (the adjusted R2) jumps from 0.25 ple average of the mathematics and science to 0.73. As in figure 5, quantity of schooling is scores over all the international tests depicted statistically significantly related to economic

35 Ranking colleges and universities is clearly difficult, at Global Fortune 500 countries, U.S. institutions had ten but the available attempts confirm the position of U.S. of the top twenty-two places and twenty-four of the top research universities. In the 2007 academic rankings of fifty-nine places (see http://www.ensmp.fr/Actualites/PR/ the world’s research universities by the Institute of Higher EMP-ranking.html accessed January 12, 2008). Education, Shanghai Jiao Tong University, the United 36 Another recent set of international tests has focused States had seventeen of the top twenty universities and on reading. We are concerned about the reliability of fifty-four of the top ninety-nine (see http://ed.sjtu.edu.cn/ these measures and have not focused on them in our anal- rank/2007/ARWU2007TOP500list.htm accessed January ysis. Nonetheless, consideration of them in addition to or 12, 2008). In a 2007 professional ranking by the Ecole instead of the math and science tests does not change our des mines de Paris based on graduates who were CEOs basic results. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 639

Table 2 Education as Determinant of Growth of Income per Capita, 196022000

Dependent variable: average annual growth rate in GDP per capita, 1960–2000

(1) (2) (3)a (4) GDP per capita 1960 20.379 20.302 20.277 20.351 (4.24) (5.54) (4.43) (6.01) Years of schooling 1960 0.369 0.026 0.052 0.004 (3.23) (0.34) (0.64) (0.05) Test score (mean) 1.980 1.548 1.265 (9.12) (4.96) (4.06) Openness 0.508 (1.39) Protection against expropriation 0.388 (2.29) Constant 2.785 24.737 23.701 24.695 (7.41) (5.54) (3.32) (5.09) N 50 50 50 47 R2 (adj.) 0.252 0.728 0.741 0.784 Notes: t-statistics in parentheses. a Regression includes five regional dummies.

growth in a specification that does not include America, Middle East and North Africa, the measure of cognitive skills, but the associ- Sub-Saharan Africa, and the industrial coun- ation between years of schooling and growth tries—by including five regional dummies turns insignificant and its marginal effect is (column 3 of table 2). That is, even when con- reduced to close to zero once cognitive skills sidering just the variation that exists within are included in the model (see figure 8).37 In each region, cognitive skills are significantly other words, school attainment has no inde- related to economic growth. Eliminating the pendent effect over and above its impact between-region variance reduces the test- on cognitive skills. The result remains the score coefficient from 1.98 to 1.55, but it same when the measure of years of school- remains strongly significant. ing refers to the average between 1960 and One of the most important fundamen- 2000, rather than the initial 1960 value. In tal determinants of economic growth the different specifications, there is evidence discussed in the recent literature is the for conditional convergence in the sense that institutional framework of the economy countries with higher initial income tend to (see section 5.6 below for details). The grow more slowly over the subsequent period. most common and powerful measures of The same pattern of results is preserved the institutional framework used in empiri- when we ignore any variation between cal work are the openness of the economy world regions—East Asia, South Asia, Latin to international trade and the security of

37 The coefficient estimate on years of schooling in the sample reported in figure 5, corresponding to the fact fifty-country sample of column 1 of table 2 is somewhat discussed above that the estimate tends to be smaller in smaller than the one reported for the ninety-two-country high-income countries. 640 Journal of Economic Literature, Vol. XLVI (September 2008)

0 Conditional growth

coef ฀1.980, se 0.217, t 9.12

4 1.5 1 0.5 0 0.5 1 Conditional test score Figure 7. Added-Variable Plot of Growth and Test Scores

ROM Conditional growth

coef ฀0.026, se 0.078, t 0.34

2 4 2 0 2 4 Conditional years of schooling

Figure 8. Added-Variable Plot of Growth and Years of Schooling with Test Score Controls

Notes: Added-variable plot of a regression of the average annual rate of growth (in percent) of real GDP per capita in 1960–2000 on the initial level of real GDP per capita in 1960, average test scores on international student achievement tests, and average years of schooling in 1960. Author calculations; see table 2, column 2. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 641 property rights.38 When we add these two Second, in columns 3 and 4, we subdivide institutional variables to our model, they the sample into countries above and below are jointly highly significant (column 4 of the sample median of initial GDP per capita. table 2). But the positive effect of cognitive Again, the significant effect of cognitive skills skills on economic growth is very robust remains robust in both subsamples. Here, the to the inclusion of these controls, albeit effect of test scores is considerably larger in somewhat reduced in magnitude to 1.26. the low-income countries, and the difference Other potential determinants of economic in the coefficients on test scores is statistically growth often discussed in the literature significant at the five percent level. Thus, are fertility and geography. However, when if anything, the effect of cognitive skills is we add the total fertility rate and common larger in developing countries than in devel- geographical proxies, such as latitude or the oped countries. Furthermore, the robustness fraction of the land area of a country that is of the effect in the subsamples is remark- located within the geographic tropics, to the able, in particular considering the small specification reported in column 4 of table 2, sample sizes of the specifications reported neither of these additional variables is statis- in table 3. Similarly, the effect of cognitive tically significantly associated with economic skills remains robust in the two subsamples growth. Furthermore, none of the other of countries above and below the median of results, in particular for cognitive skills, are economic growth over the considered period, qualitatively affected. with the point estimate larger in the high- An important issue is whether the role growth sample. of cognitive skills in the process of eco- 5.4 Robustness Checks nomic development differs between developing and developed countries. In table 3, Extensive robustness tests confirm the we divide the sample of countries into two strong and significant relationship between groups in two different ways. First, in col- cognitive skills and economic growth. umns 1 and 2, we subdivide the sample into Importantly, the results do not appear to be OECD countries and non-OECD coun- an artifact of the specific time period, set tries. Results are remarkably similar, with of countries, or achievement measurement the point estimate of the effect of cognitive decisions. skills slightly larger in non-OECD coun- To start with, we can look at the associa- tries. However, the effect of cognitive skills tion between school attainment and cogni- on economic growth does not differ signifi- tive skills. The simple correlation coefficient cantly between the two groups of countries. between test scores and years of school- The results remain qualitatively the same ing is 0.64. Identification of the separate when openness and quality of institutions impacts of test scores and school attainment are again added as control variables. comes from divergences in the relationship

38 The proxy for openness used here is the fraction of assesses the risk that investments will be expropriated in years between 1960 and 1998 that a country was classified different countries), ranging from 0 to 10 (high figures as having an economy open to international trade, based on corresponding to low risk), as used by Acemoglu, Simon five factors including tariffs, quotas, exchange rate controls, Johnson, and James A. Robinson (2001) and provided in export controls, and whether or not a socialist economy John W. McArthur and Sachs (2001). This measure of the (cf. Jeffrey D. Sachs and Andrew M. Warner 1995). The risk of confiscation and forced nationalization of property proxy for security of property rights is an index of the pro- is often used as a summary variable for institutional qual- tection against expropriation risk, averaged over 1985–95, ity, and similar data were first used in this framework by from Political Risk Services (a private company which Stephen Knack and Philip Keefer (1995). 642 Journal of Economic Literature, Vol. XLVI (September 2008)

TABLE 3 Education as Determinant of Growth of Income per Capita, 1960–2000: Subsamples

(1) (2) (3) (4)

Developing Low-income High-income OECD sample countriesa countriesb countriesc GDP per capita 1960 –0.262 –0.301 –0.063 –0.294 (1.77) (5.81) (0.28) (6.38) Years of schooling 1960 0.025 0.025 0.006 0.152 (0.20) (0.26) (0.05) (1.70) Test score (mean) 2.056 1.736 2.286 1.287 (6.10) (4.17) (6.98) (5.37) Constant –5.139 –3.539 –6.412 –2.489 (3.63) (1.96) (4.52) (2.86) N 27 23 25 25 R2 (adj.) 0.676 0.830 0.707 0.783 Notes: Dependent variable: average annual growth rate in GDP per capita, 1960–2000. t-statistic in parentheses. a Non-OECD countries. b Countries below sample median of GDP per capital 1960. c Countries above sample median of GDP per capital 1960.

between the two, and it is useful to ensure the ten countries with the largest negative that the results are not simply driven by pat- residuals on the regression just mentioned), terns of measurement error or omitted fac- we find that test scores remain a strongly tors that might underlie the divergences. significant factor in growth while years of To check the robustness of the estimates in schooling are insignificant. But at the same this dimension, we begin with the countries time, these countries are also not driving the which most distinguish the two measures results: Dropping all these twenty countries, from one another. When regressing years of which give the most leverage for the identifi- schooling on test scores, among the countries cation of test scores from years of schooling, with the highest years of schooling for their we still obtain the same qualitative result test-score level (the largest positive residuals) (significant test scores, insignificant years of are Switzerland, the United States, South schooling). Africa, Peru, Australia, and Norway. Among The results reported in tables 2 and 3 are the countries with the lowest years of school- also robust to several alternative approaches ing for their test-score level (the largest to measuring the cognitive skills. The results negative residuals) are China, Iran, Taiwan, remain qualitatively the same when using Singapore, India, and Malaysia. The gaps only the tests performed at the level of lower between these two groups of countries are secondary education, excluding any test predictive of economic growth: When the in primary schooling or in the final year of sample is restricted just to the twenty coun- secondary education. Arguably, test scores tries with the largest differences between at the end of the secondary level, which the two education measures (the ten coun- combine the knowledge accumulated over tries with the largest positive residuals and primary and secondary schooling, may be Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 643 more relevant for the human capital of the traced back to the early test scores. Again, labor force than test scores that capture only our results are robust to such an instrumen- the knowledge at the end of either primary tal-variable approach. In sum, the results or lower secondary school. At the same time, are not driven by either early or late test the duration of secondary education differs scores alone. across countries, so that tests performed in The results are also robust to performing the final year of secondary schooling in each the analyses in two subperiods, 1960–80 and country may not be as readily comparable 1980–2000. The most recent period includes across countries as the grade-based target the Asian currency crisis and other major eco- populations. Further, given differing school nomic disruptions that could affect the appar- completion rates, the test for the final year of ent impact of cognitive skills on growth—but secondary schooling may imply cross-coun- they do not. Test scores exert a statistically try samples with differential selectivity of significant positive effect on growth in both test takers. Neither the primary-school tests subperiods, while years of schooling remain nor the tests in the final secondary year are insignificant in both subperiods. crucial for the results. As discussed in the previous section, one Furthermore, results are qualitatively the may worry about the extent to which East same when using only scores on tests per- Asian countries are driving the associa- formed since 1995. These recent tests have tion between cognitive skills and economic not been used in the previous analyses and are growth. As is obvious from figure 7, several generally viewed as having the highest stan- East Asian countries feature both high cog- dard of sampling and quality control. Likewise, nitive skills and high economic growth, and results are robust to using tests scores since the top right corner of the figure is notice- 1995 for just lower secondary grades. ably inhabited by East Asian countries. Still, A drawback of using only the more recent the regression reported above that controls tests is that such an approach requires a for regional dummies already showed that strong version of the assumption that test the association between cognitive skills performance is reasonably constant over and growth is not solely due to a difference time, because it relates test performance between the group of East Asian countries measured since 1995 to the economic data and the rest of the countries. Furthermore, for 1960–2000. To make sure that higher similar to the results reported in Hanushek previous economic growth is not driving the and Kimko (2000), when we drop all ten measured test performance, we also used a East Asian countries from our sample of fifty test score measure that disregards all tests countries, the estimate on cognitive skills since the late 1990s. Our results turn out to remains statistically highly significant at a be robust, with a point estimate on the test point estimate of 1.3. The significant effect score variable that is significantly higher, in the sample without East Asian countries is when we restrict the tests to only those con- also evident in the two separate subperiods, ducted until 1995 (sample reduced to thirty- with the point estimates being larger in the four countries) and until 1984 (twenty-two separate regressions. countries). We can also use the average Finally, we can look at the different sub- early test scores (either until 1984 or until jects separately. Thus, we can divide our 1995) as an instrument for the average of combined test-score measure into one using all test scores in a two-stage least-squares only the math tests and one using only the regression, in order to utilize only that part science tests. All results remain qualitatively of the total test-score measure that can be the same when we use the test scores in math 644 Journal of Economic Literature, Vol. XLVI (September 2008) and science separately. Even more, both education affect growth differently. Loosely subject-specific test scores are significantly speaking, is it a few “rocket scientists” at the associated with growth when entered jointly. very top of the distribution who are needed to There is some tendency for math perfor- spur economic growth or is it “education for mance to dominate science performance in all” that is needed to lay a broad base at the different robustness specifications but overall lower parts of the educational distribution? performance in math and science carry sepa- Does educational performance at different rate weight for economic growth. points in the distribution of the population So far, the growth analyses have not used have separate effects on economic growth? performance on the reading tests, because To estimate such effects, we measure the they may be affected by testing in different share of students in each country that reaches languages and may not be easily combined a certain threshold of basic skills at the inter- into a common one-dimensional scale with national scale, as well as the share of students math and science tests. However, the inter- that surpasses an international threshold of national reading tests are supposed to be top performance. As the two thresholds, we designed to minimize the impact of variation use 400 and 600 test-score points, respec- in language, and we can use them separately tively, on the transformed international scale from the math and science tests. Using read- as shown in figure 6. ing performance in place of math and sci- The threshold of 400 points is meant to cap- ence performance yields the same qualitative ture a notion of basic literacy. On the PISA 2003 results: Reading performance is strongly and math test, for example, this would correspond significantly related to economic growth, ren- to the middle of the level 1 range (358 to 420 dering years of schooling insignificant. This test-score points) which denotes that students result is robust to using reading tests only in can answer questions involving familiar con- lower secondary school, only up to 1991, or texts where all relevant information is present only since 1995, as well as in two subperiods and the questions are clearly defined. While 1960–80 and 1980–2000, with the impact of the PISA 2003 science test does not define a cognitive skills being uniformly statistically full set of proficiency levels, the threshold of significant. When entering the reading score 400 points is used as the lowest bound for a together with the math and science scores, basic level of science literacy (Organisation reading is clearly dominated by the other for Economic Co-operation and Development subjects. 2004, p. 292). In general, a level of 400 points Thus, the math and science dimensions means performance at one standard deviation of performance seem to have independent below the OECD mean. The share of students effects on economic growth, while the read- achieving this level ranges from 18 percent in ing effect is significant only without control- Peru to 97 percent in the Netherlands and ling for the other subjects. Because of the thin Japan, with an international median of 86 per- country samples, however, we trust the pattern cent in our sample. The threshold of 600 points of results more that the specific estimates. captures the notion of very high performers, performing at more than one standard devia- 5.5 Distribution of Cognitive Skills and tion above the OECD mean. The share of stu- Economic Growth dents achieving this level ranges from below The results so far consider only the mean 0.1 percent in Colombia and Morocco to 18 of cognitive skills in a country. From a policy percent in Singapore and Korea and 22 per- viewpoint, though, it is important to know cent in Taiwan, with an international median whether different parts of the distribution of of 5 percent in our sample. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 645

Table 4 Cognitive Skills and Growth: Distribution and Institutional Interaction

Dependent variable: average annual growth rate in GDP per capita, 196022000. (1) (2) (3) GDP per capita 1960 20.287 20.297 20.355 (5.12) (5.64) (6.03) Years of schooling 1960 0.022 20.031 20.017 (0.28) (0.41) (0.22) Share of students above threshold of 400 2.732 (3.61) Share of students above threshold of 600 12.880 (4.35) Test score (mean) 0.942 1.494 (2.30) (4.46) Openness 0.732 (2.13) Test score 3 openness 1.609 (2.34) Protection against expropriation 0.485 (3.00) Test score 3 protection against expropriation 0.210 (1.19) Constant 1.335 3.814 4.617 (2.97) (11.24) (16.18) N 50 47 47 R2 (adj.) 0.719 0.785 0.781 Note: t-statistics in parentheses.

When we enter the share of students above Nonetheless, the evidence strongly suggests the two thresholds jointly in our growth model that both dimensions of educational perfor- (see column 1 of table 4), both turn out to be mance count for the growth potential of an separately significantly related to economic economy (see Hanushek and Woessmann growth. That is, both education for all and forthcoming for greater detail).39 the share of absolutely top performers seem Additional specifications using different to exert separately identifiable effects on eco- points of the distribution of test scores sup- nomic growth. These initial results should be port this general view. The positive effect viewed as suggestive rather than definite, not of cognitive skills is highly robust to mea- the least because of issues of multicollinearity suring test-score performance at different between the two measures of cognitive skills percentiles of the distribution, such as the which have a bivariate correlation of 0.73. Importantly, the relative size of the effects of performance at the bottom and at the top 39 In contrast to the result of Amparo Castelló and of the distribution depends on the specific Doménech (2002) based on years of schooling, we do not find a significant effect of inequality of cognitive skills per specification used, and further research is se on economic growth, but rather significant effects at needed to yield more detailed predictions. different points of the distribution. 646 Journal of Economic Literature, Vol. XLVI (September 2008) twenty-fifth, seventy-fifth, and ninety-fifth priation. (Note that protection against expro- percentile, rather than at the mean. When priation and openness are strongly correlated, including two measures at a time, they are with a correlation coefficient of 0.71.) At the always jointly, and often separately, signifi- same time, though, the results show that, on cant. When including two percentile mea- average, cognitive skills exert a positive effect sures, it is not always clear whether the on economic growth independent of these higher ones tend to dominate the lower measures of the quality of institutions. While ones or vice versa in different specifications, Acemoglu, Johnson, and Robinson (2001, which are again hampered by strong multi- 2002, 2005) find that geographical features collinearity of the test-score measures. The do not exert an effect on economic growth highest bivariate correlation among the dif- independent of institutions, this remains a dis- ferent test-score measures is between mean puted subject (cf., e.g., McArthur and Sachs performance and the share of students in a 2001). When we add proxies for geography country reaching the threshold of 400 test- such as location in the geographic tropics or score points, at 0.99. Thus, mean perfor- latitude to our basic specification, these do not mance seems to capture mainly the pattern enter significantly and do not change the find- of basic literacy across the countries in our ings on institutions and on cognitive skills. sample. The specifications including two test- While the evidence confirms an independ- score variables remain qualitatively the same ent effect of cognitive skills on economic when including five regional dummies, and growth, this effect may differ depending the pattern of significance also holds when on the economic institutions of a country. the other control variables are included. Douglass C. North (1990), for example, In sum, both basic and top dimensions emphasizes that the institutional framework of cognitive skills seem to have indepen- plays an important role in shaping the rela- dent positive effects on economic growth. tive profitability of piracy versus productive However, as in the case of the math, science, activity. If the available knowledge and skills and reading dimensions of performance, the are used in the former rather than the lat- relatively small sample of countries allows for ter activity, one may certainly expect the an assessment of the general pattern of results effect on economic growth to be substan- more than of specific separate estimates. tially different, and maybe even to turn negative. Similarly, Murphy, Andrei Shleifer, 5.6 Institutions, Cognitive Skills, and and Robert W. Vishny (1991) show that the Growth allocation of talent between rent-seeking In recent years, there has been an increas- and entrepreneurship matters for economic ing emphasis on the role of economic institu- growth: countries with relatively more engi- tions as the fundamental cause of differences neering college majors grow faster and coun- in economic development (cf. Acemoglu, tries with relatively more law concentrators Johnson, and Robinson 2001, 2002, 2005). grow more slowly. Easterly (2001) argues that As we saw in column 4 of table 2, the quality education may not have much impact in less of institutions as measured by the protection developed countries that lack other facilitat- against expropriation is indeed significantly ing factors such as functioning institutions related to economic growth in our model. for markets and legal systems. In a similar A second measure of institutional quality, way, Pritchett (2001, 2006) suggests that, openness to international trade, also tends to due to deficiencies in the institutional envi- be significantly related to economic growth, ronment, cognitive skills might have been at least jointly with protection against expro- applied to socially unproductive activities in Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 647

2.5

1.5

1 Effect of test score on growth

0.5

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Openness

Figure 9. The Effect of Cognitive Skills on Growth Depending on Openness

Notes: Estimated effect of average achievement test scores on the average annual rate of growth of real GDP per capita in 1960–2000, depending on the degree of openness to international trade of a country. Author calculations; see table 4, column 2. many developing countries, rendering the openness and cognitive skills not only have average effect of education on growth across significant individual effects on economic all countries negligible. While his result of growth but also a significant positive interac- negligible average growth effects of increases tion. This result is depicted in figure 9. The in educational quantity may have more to do effect of cognitive skills on economic growth with issues of measuring education than with is indeed significantly higher in countries that perverse economic institutions, his point that have been fully open to international trade the social returns to education and skills may than in countries that have been fully closed. be low in countries with perverse institutional (Jamison, Jamison, and Hanushek 2007 find environments is certainly worth pursuing. a similar result, in that the impact of cogni- Thus, in column 2 of table 4, we add an tive skills on technical progress is strong in interaction term between cognitive skills and countries with open trade regimes and essen- one of our institutional measures, openness to tially zero in closed economies). The effect of international trade, to our growth specifica- cognitive skills on economic growth is signifi- tion (to facilitate interpretation, the test-score cantly positive, albeit relatively low at 0.9, in variable is centered in the specifications that closed economies, and it increases to a size include interactions). The results suggest that of 2.5 in open economies. There is a similar 648 Journal of Economic Literature, Vol. XLVI (September 2008) positive interaction effect between test scores the robustness of the estimates to alterna- and openness when openness is specified as tive samples and specifications and the a dummy for countries that have been closed added support from tests of major threats to for the majority of the time (openness below identification, we believe that this is a useful 0.3). The reported result is robust to including and potentially important exercise. the measure of protection against expropria- Two aspects of any educational reform tion. When using protection against expro- plan are important. First, what is the mag- priation rather than openness to trade as the nitude of the reform that is accomplished? measure of quality of institutions in column 3, Second, how fast does any reform achieve there is similarly a positive interaction term its results? Without being specific about the with cognitive skills, although it lacks statisti- potential schooling reforms, here we simply cal significance. investigate the economic results that might In sum, both the quality of the institu- be anticipated on the assumption that some tional environment and the level of cognitive set of schooling reforms actually leads to skills seem important for economic develop- substantial achievement gains over an iden- ment. Furthermore, the effect of cognitive tified time period. skills on economic growth seems to be sig- Our analysis puts the economic implica- nificantly larger in countries with a produc- tions in terms of standard deviations of test tive institutional framework, so that good scores (measured at the student level, as institutional quality and good cognitive skills throughout this paper). To provide a bench- can reinforce each other in advancing eco- mark, we consider a reform that yields a 0.5 nomic development. Thus, the macroeco- standard deviation improvement in aver- nomic effect of education depends on other age achievement of school completers. This complementary growth-enhancing policies metric is hard to understand intuitively, and institutions. Nonetheless, we still also in part because most people have experi- find a significant positive growth effect of ences within a single country. It is pos- cognitive skills even in countries with a poor sible, however, to put this in the context of institutional environment. the previous estimation. Consider a developing country with average performance 5.7 The Implications of Improved at roughly 400 test-score points, what we Cognitive Skills described as approximately minimal literacy It is important to understand the implica- on these tests. For example, on the PISA tions of policies designed to improve edu- 2003 examinations, average achievement in cational outcomes. The previous estimation Brazil, Indonesia, Mexico, and Thailand fell provides information about the long-run close to this level. An aggressive reform plan economic implications of improvements in would be to close half the gap with the aver- cognitive skills. To understand better the age OECD student, which would be a half impact of improved achievement, it is use- standard deviation improvement. ful to relate policy reforms directly to the As an alternative policy change, consider pattern of economic outcomes that are what it would mean if a country currently per- consistent with feasible improvements. For forming near the mean of OECD countries this exercise, we assume that the estimated in PISA at 500 test-score points (for example, coefficients provide the causal impact of dif- Norway or the United States in PISA 2000 or ferences in cognitive skills. As discussed in Germany in PISA 2003, see figure 6) would section 2, this interpretation is threatened manage to increase its cognitive skills to the by a variety of factors. Nonetheless, given level of top performers in PISA at roughly Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 649

540 test-score points (for example, Finland or improvement.” For the calibration, policies Korea on either PISA test).40 Such an increase are assumed to begin in 2005—so that a of 40 test-score points amounts to 0.4 stan- twenty-year reform would be complete in dard deviation. These calculations also point 2025. The actual reform policy is presumed out the asymmetry of the test score distribu- to operate linearly such that, for example, a tion with a considerably longer left tail of the twenty-year reform that ultimately yielded country distribution. one-half standard deviation higher achieve- The timing of the reform is also impor- ment would see the performance of gradu- tant. Two aspects of timing enter. First, such ates increasing by 0.025 standard deviations movement of student performance cannot each year over the period. It is also nec- be achieved instantaneously but requires essary to characterize the impact on the changes in schools that will be accomplished economy, which we assume is proportional over some time (say, through systematic to the average achievement levels of prime replacement of teachers through retirements age workers.42 Finally, for this exercise we and subsequent hiring). The time path of any project the growth impact according to the reform is difficult to specify, but achieving the basic achievement model that also includes change of 0.5 standard deviations described the independent impact of economic institu- above for an entire nation may realistically tions—column 4 of table 2. take twenty to thirty years.41 The figure indicates how much larger the Second, if the reforms succeed, their level of GDP is at any point after the reform impact on the economy will not be immediate. policy is begun as compared to that with no In particular, the new graduates from school reform. In other words, the estimates suggest will initially be a small to negligible portion the increase in GDP expected over and above of the labor force. It will be sometime after any growth resulting from other factors. the reform of the schools before the impact Obviously, for any magnitude of achieve- on the economy is realized. In other words, ment improvement, a faster reform will the prior estimates are best thought of as the have larger impacts on the economy, simply long run, or equilibrium, outcomes of a labor because the better workers become a domi- force with a given cognitive skills. nant part of the workforce sooner. But, the To show the impact of these elements of figure shows that even a twenty- or thirty-year reform, figure 10 simulates the impact on reform plan has a powerful impact on GDP. the economy of reform policies taking ten, twenty, or thirty years for a 0.5 standard devi- 42 We specifically assume that the relevant achievement ation improvement in student outcomes at levels depend on workers in the first thirty-five years of the end of upper secondary schooling—what their work life and calculate the average achievement levels based upon the progressive improvements of school com- we label as a “moderately strong knowledge pleters under the different reform periods. The full impact of an educational reform is not felt until thirty-five years past completion of the reform, e.g., for forty-five years with 40 Differences among nations do vary somewhat across a ten-year reform period. To our knowledge, no past work the separate tests. For example, by the PISA 2006 tests, has indicated how achievement impacts would be felt on the United States scores were somewhat farther behind the economy. Our linear impact that depends on the work- Finland and other top performers than in 2003. The force average is probably conservative, because new tech- important point here is demonstrating the impact of sub- nologies that rely on better trained workers could probably stantial performance improvements, and not necessarily be introduced once there is a substantial number of more moving to the very top of the distribution. skilled workers available instead of relying on improve- 41 Rough calculations of the relationship between ment throughout the workforce. Alternatively, improve- changes in teacher quality and results are found in ments that depend on innovation may depend most on the Hanushek (2005). These are based on assumptions of stock of young, very highly skilled workers, and the impact teacher turnover that mirror the U.S. experience. of educational improvements might be quite quick. 650 journal ofEconomic Literature, Vol. XLVI (September 2008)

49%

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Figure 10. Improved GDP with Moderately Strong Knowledge Improvement(0.5 s.d_)

For example, a twenty-year plan would yield It must nonetheless be clear that these a GDPthat was five percent greater in 2037 effects represent the result from actual gains (compared with an economy with no increase in cognitive skills. There have been many in cognitive skills). The figure also plots 3.5 atternpts around the world to improve stu- percent of GDP, an aggressive spendinglevel dent outcomes, and manyof these have failed for education in many countries of the world. to yield actual gains in student performance. Five percent of GDPis significantly greater Bad reforms, those without impacts on stu- than the typical country’s spending onall dents, will not have these impacts. primaryand secondary schooling, so thatitis This simulation shows that the previous truly a significant change that would permit estimates of impacts of cognitive skills on the growth dividend to more than coverall growthhave really large impacts onnational of primary and secondary school spending. economies. At the same time, while the But even a thirty-year reform program(that rewardsare large, they also imply that poli- would not be fully accomplished until 2035) cies must be considered across lengthy time would yield more than five percent higher periods and require patience-—-a patience real GDP by 2041, that is not always clear in national policy Projecting these net gains from improved making. achievement further past the reform period These reforms must also be put in a showsvividly the long ran impacts of reform. broader perspective, because other kinds of Over a seventy-five year horizon, a twenty- institutional changes and investments will year reform yields a real GDPthatis 36 per- also take substantial time. Changing basic cent higher than would be with no changein economicinstitutions, for example, can sel- cognitive skills, dombe aaccomplished over night, and their Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 651 impacts will take time before the economy countries in the Demographic and Health adjusts. Thus, in large part, our calculations Surveys (DHS) and similar surveys (cf. Deon about the time path of benefits differ more Filmer 2006), conducted in a large number in the fact that we make it explicit than in its of developing countries. These household pattern compared to a variety of other eco- survey data are much more reliable than the nomic policies. administrative data on school enrollment rates. Administrative data have traditionally been used in country reporting as well as in 6. Where Does the Developing a variety of recent studies that try to evalu- World Stand? ate progress on the quantitative development Given the crucial importance of cognitive goals, but it appears that the administrative skills for economic development, it is tell- data available in many developing countries ing to document how the developing coun- often overstate actual enrollment and com- tries fare in this regard. In the following, we pletion rates. Further, the self-reported data document both the quantity of schooling and on the highest grade completed is more rel- cognitive skills achieved by developing coun- evant for actual education than enrollment tries from an international perspective, and rates, which are affected by grade repetition this vividly illustrates the magnitude of the and the like. task at hand. While almost all OECD countries have universal school attainment to grade 9, 6.1 Lack of Quantity of Schooling essentially all developing regions are far from The disadvantages of less developed coun- that. In the average African country in the tries in terms of educational enrollment and data, only 13 percent of each cohort finishes attainment have been well documented and grade 9, and less than 30 percent in Central are well known. As noted, current interna- America and South and East Asia. Even in tional policy initiatives—the Millennium South America, this figure is only 43 percent, Development Goals and the Education for although on the other hand only 17 percent All initiative—focus on the importance of of a cohort do not complete grade 5 (which expanded school attainment in developing often serves as an initial indication of basic countries. literacy and numeracy rates). In West and To provide an aggregate picture, fig- Central Africa, 59 percent of each cohort do ure 11 presents the share of children aged not even complete grade 5, and 44 percent fifteen to nineteen who have completed never enroll in school in the first place.43 It grade 9, dropped out between grades 5 is notable across countries, however, that and 9 or between grades 1 and 5, or never the lack of grade 5 attainment is at least as enrolled, for eight regions of developing often due to dropping out of school than countries. Grades 5 and 9 are chosen as two due to never enrolling. In any event, while possible definitions of basic schooling. The the pattern of educational attainment varies age range of fifteen to nineteen is chosen to greatly across countries and regions, the lack balance the relevance of the data for most of quantitative educational attainment from recent conditions against the censoring prob- universal completion of basic education— lem of some children still being in school. The basic patterns observed are, however, the same when using estimates adjusted for 43 These household survey data are corroborated by UNESCO data that show net enrollment rates in primary the censoring (Pritchett 2004). The shares schools in the region to be 55 percent in 1999 and 65 per- are unweighted averages of the available cent in 2004 (UNESCO 2007). 652 Journal of Economic Literature, Vol. XLVI (September 2008)

East and South Africa

West and Central Africa

Central America

South Asia

East Asia and Paciﬁc

Middle East and North Africa

South America

Europe and Central Asia

| | | | | | 0 0.2 0.4 0.6 0.8 1

Finished grade 9 Dropout between grades 1 and 5 Dropout between grades 5 and 9 Never enrolled

Figure 11. Lack of Educational Attainment in Developing Countries

Note: Based on Pritchett (2004). be it grade 5 or grade 9—is immense in the average developing country does not neces- majority of developing countries. sarily mean that the students have become Focusing on this dimension of schooling functionally literate in terms of basic cogni- quantity, many policy initiatives of national tive skills. As a recent report by the World governments and international development Bank Independent Evaluation Group (2006) agencies have tried to increase the educational documents, high priority was accorded to attainment of the population. The data in fig- increasing enrollment in primary schools in ure 11 show that there remains a long way to developing countries over the past fifteen go. But even this dire picture may understate years, but much less attention was directed the challenge that becomes apparent when to whether children are learning adequately. cognitive achievement is also considered. In figure 6 above, we have already documented the particularly low levels of mean 6.2 Lack of Achievement Outcomes performance of students attending school The description of school completion in basically all the developing countries that unfortunately ignores the level of cogni- have participated in at least one of the inter- tive skills actually acquired. Completing national student achievement tests. But of five or even nine years of schooling in the course, mean performance can hide a lot of Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 653 dispersion that exists within countries, and developing countries, and, furthermore, the the prior analyses of growth (section 5.5) children enrolled in school at the different show that there is separate information at testing grades are probably only a select different percentiles of the test-score data. group of all children of the respective age in Figures 12 and 13 depict the share of these countries. students in a country that surpasses the 6.3 The Size of the Task at Hand: Schooling thresholds of 400 and 600 test-score points Quantity and Cognitive Skills on the transformed scale of the combined Combined international tests—the same measure and thresholds that we used in the growth analy- We have seen that developing countries ses of section 5.5. Figure 12 shows the sam- are severely lacking in terms of both school- ple of fifty countries which forms the basis of ing quantity and student outcomes. Figure 14 our growth analyses, and figure 13 shows the shows the combination of the two. For the four- remaining twenty-seven countries that par- teen countries that both have reliable attain- ticipated in one of the international student ment data from the household surveys and achievement tests but lack internationally have participated in the international student comparable GDP data for the 1960–2000 achievement tests, we combine educational period that would allow them to be included attainment of fifteen to nineteen-year-olds in the growth analyses. from the latest available year with test scores at When considering the basic educational the end of lower secondary education (eighth achievement of students, we are interested in grade or fifteen-year-olds) from a year close the share of students who surpass the thresh- by.44 This allows us to calculate rough shares old of 400 test-score points, which may be among recent cohorts of school- leaving age of viewed as a rough threshold of basic literacy how many were never enrolled in school, how in mathematics and science. As is evident many dropped out of school by grade 5 and from the figures, this share varies immensely by grade 9, how many finished grade 9 with a across countries. In countries such as Japan, test-score performance below 400 which sig- the Netherlands, Korea, Taiwan, and Finland, nals functional illiteracy, and finally how many less than 5 percent of tested students fall finished grade 9 with a test-score performance below this literacy threshold. By contrast, in above 400. Only the last group can be viewed many of the developing countries participat- as having reached basic literacy in cognitive ing in the international achievement tests, skills (cf. Pritchett 2004, Woessmann 2004). more than half of the tested students do not Figure 14 presents the countries in reach this threshold of literacy. The countries increasing order of the share of students with the largest shares of test-taking students mastering basic skills. In eleven of the who are functionally illiterate by this defi- nition are Peru (82 percent), Saudi Arabia (67 percent), Brazil (66 percent), Morocco 44 Specifically, the years of the household survey data and the associated tests (where TIMSS always refers to the (66 percent), South Africa (65 percent), respective eighth grade subtests) are as follows: Albania and Botswana (63 percent), and Ghana (60 per- Peru: attainment data for 2000, combined with test scores cent). In these countries, more than 60 per- from PISA 2002; Armenia: 2000 and TIMSS 2003; Brazil: 1996 and PISA 2000; Colombia: 2000 and TIMSS 1995; cent of those in school do not reach a level Egypt, Ghana, and Morocco: 2003 and TIMSS 2003; Indo- of basic literacy in cognitive skills. It should nesia: 2002 and average of TIMSS 2003 and PISA 2003; be noted that the group of developing coun- Moldova: 2000 and average of TIMSS 1999 and TIMSS 2003; Philippines: 2003 and average of TIMSS 1999 and tries participating in the international tests TIMSS 2003; South Africa: 1999 and TIMSS 1999; Thailand: is probably already a select sample from all 2002 and PISA 2003; Turkey: 1998 and TIMSS 1999. 654 Journal of Economic Literature, Vol. XLVI (September 2008)

Japan Netherlands Korea Taiwan Finland Canada Singapore Hong Kong Sweden Australia China Belgium Austria United Kingdom France India Switzerland USA Ireland New Zealand Iceland Norway Denmark Italy Malaysia Spain Thailand Israel Cyprus Portugal Greece Romania Iran Zimbabwe Jordan Colombia Chile Uruguay Turkey Egypt Argentina Mexico Philippines Indonesia Tunisia Ghana South Africa Morocco Brazil Peru

0 0.2 0.4 0.6 0.8 1

Below 400 Between 400 and 600 Above 600

Figure 12. Share of Students below 400 (“Illiterate”), between 400 and 600, and above 600 Test-Score Points, Countries in Growth Analysis

Source: Hanushek and Woessmann (forthcoming), based on several international tests; see text for details. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 655

Estonia Hungary Slovenia Czech Republic Macao Germany Slovak Republic Lithuania Russian Federation Latvia Liechtenstein Poland Swaziland Moldova Luxembourg Bulgaria Armenia Serbia Nigeria Macedonia Bahrain Lebanon Kuwait Palestine Albania Botswana Saudi Arabia 0 0.2 0.4 0.6 0.8 1

Below 400 Between 400 and 600 Above 600

Figure 13. Share of Students below 400 (“Illiterate”), between 400 and 600, and above 600 Test-Score Points, Countries Not in Growth Analysis

Source: Hanushek and Woessmann (forthcoming), based on several international tests; see text for details.

fourteen countries, the share of fully liter- Armenia and 63 percent in Moldova can be ate students in recent cohorts is less than viewed as literate at the end of lower sec- one third. In Ghana, South Africa, and ondary schooling. Brazil, only 5 percent, 7 percent, and 8 per- An example of a basic test question from cent of a cohort, respectively, reach literacy. one of the international achievement tests The remaining more than 90 percent of the can, perhaps better than anything, illus- population are illiterate because they never trate the scope of the problem in develop- enrolled in school; because they dropped ing countries. One question asked to eighth out of school at the primary or early second- graders in the Trends in International ary level; or because, even after completing Mathematics and Science Study (TIMSS) lower secondary education, their grasp of 2003 was: “Alice ran a race in 49.86 sec- basic cognitive skills was so low that they onds. Betty ran the same race in 52.30 sec- have to be viewed as fundamentally illiter- onds. How much longer did it take Betty to ate. In contrast, 55 percent of a cohort in run the race than Alice? (a) 2.44 seconds (b) 656 Journal of Economic Literature, Vol. XLVI (September 2008)

Ghana South Africa Brazil Peru 5% 7% 8% 12% 1% 1% 6% 4% 6%

12% 10% 14% 32% 29% 33% 39% 46% 48% 40% 46%

Morocco Albania Philippines Turkey

1% 1% 6% 6% 4% 3% 13% 17% 21% 23% 22% 15% 37% 15% 27% 49% 17% 35% 52% 35%

Indonesia Colombia Egypt Thailand

1% 1% 1% 6% 1% 11% 10% 5% 27% 30% 32% 42% 26% 33% 38% 30% 32% 19% 23% 29%

Armenia Moldova

1% Never enrolled

14% Dropout between grades 1 and 5 27% Dropout between grades 5 and 9 55% 63% 22% 18% Finished grade 9 without reaching basic skills Finished grade 9 with basic skills

Figure 14. Types of Lack of Education among 15–19-Year-Olds in Developing Countries

Note: Own calculations for all countries that have consistent World Bank survey data on educational attainment (Filmer 2006) along with micro data from at least one international student achievement test. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 657

2.54 seconds (c) 3.56 seconds (d) 3.76 sec- 7.1 Summary of Main Results onds.” While 88 percent of eighth-grade students in Singapore, 80 percent in Hungary, Our analysis has produced two remarkably and 74 percent in the United States got the simple but clear conclusions. correct answer (a), only 19 percent of students in eighth grade in Saudi Arabia, 29 1. Cognitive skills have powerful effects percent in South Africa, and 32 percent in on individual earnings, on the distri- Ghana got the correct answer (cf. Pritchett bution of income, and on economic 2004 for a similar example). Random guess- growth. ing would have yielded 25 percent correct on average. The accumulated evidence from analyses When we combine data on quantita- of economic outcomes is that cognitive skills tive educational attainment and cognitive have powerful economic effects. Much of the skills for the countries with reliable data on earlier discussion has concentrated solely on both dimensions, it becomes apparent that school attainment, or the quantity of school- the task at hand is truly staggering in most ing. This focus is unfortunate, because it developing countries. In many developing distorts both the analysis and the policy countries, the share of any cohort that com- discussions. pletes lower secondary education and passes Individual earnings are systematically at least a low benchmark of basic literacy in related to cognitive skills. The distribution of cognitive skills is below one person in ten. skills in society appears closely related to the Thus, the education deficits in developing distribution of income. And, perhaps most countries seem even larger than generally importantly, economic growth is strongly appreciated. Several additional references affected by the skills of workers. for examples of extremely low educational Other factors obviously also enter into performance of children even after years of growth and may well have stronger effects. schooling from different developing coun- For example, having well-functioning eco- tries are provided in Pritchett (2004). The nomic institutions such as established prop- state of the quantity and quality of educa- erty rights, open labor and product markets, tion and skills in most developing countries and participation in international markets is truly dismal. have clear importance for economic development and may also magnify the benefits of cognitive skills. Nonetheless, existing evi- 7. Conclusion dence suggests that cognitive skills indepen- This study was motivated by doubts that dently affect economic outcomes even after have been raised about the role of educa- allowing for these other factors. tion and human capital in economic devel- Moreover, the evidence on the strong rela- opment. These doubts come from a variety tionship between cognitive skills and eco- of vantage points ranging from whether the nomic outcomes is remarkably robust. While research has correctly identified the impact it is difficult to establish conclusively that this of education to whether other institutional is a causal relationship, the robustness of the aspects of countries might be more impor- result lends considerable credence to such tant. They also encompass concerns about an interpretation. The relationship does not whether or not we really know how to change appear to result from particular data sam- educational outcomes, particularly in devel- ples or model specifications. Nor can it be oping countries. explained away by a set of plausible alternative 658 Journal of Economic Literature, Vol. XLVI (September 2008) hypotheses about other forces or mechanisms recting this shortcoming should have the that might lie behind the relationship. highest priority. It is impossible to develop To be sure, cognitive skills may come from effective policies without having a good formal schools, from parents, or from other understanding of which work and which do influences on students. But, a more skilled not. Currently available measures of pro- population—almost certainly including both gram “quality” frequently rely upon various a broadly educated population and a cadre input measures that unfortunately are not of top performers—results in stronger eco- systematically related to student learning. nomic performance for nations. Moreover, the existing international tests— such as the PISA tests of the OECD—may 2. The current situation in developing not be best suited to provide accurate assess- countries is much worse than gen- ments of student performance in developing erally pictured on the basis just of countries. The evolving capacity for adap- school enrollment and attainment. tive testing that can adjust test content to the student’s ability level seems particularly Available measures of school attainment important in the developing country con- uniformly indicate that developing coun- text. Adaptive testing offers the possibility tries lag dramatically behind developed of meaningful within-country variation in countries. This fact has driven a variety of scores along with the ability to link overall efforts to expand schooling in developing performance with global standards. countries, including the Education for All initiative. Yet, much of the discussion and 7.2 Implications for Policy much of the policy making has tended to The economic importance of cognitive downplay the issues of cognitive skills. skills of students and its dismal level in International testing indicates that, even most developing countries inevitably lead to among those attaining lower secondary questions about whether it can be affected schooling, literacy rates (by international by policy. The shift of focus from years of standards) are very low in many develop- schooling to cognitive skills has important ing countries. By reasonable calculations, a policy implications because policies that range of countries has fewer than 10 per- extend schooling may be very different from cent of its youth currently reaching minimal the best policies to improve skills. The pol- literacy and numeracy levels, even when icy conundrum is that student achievement school attainment data look considerably has been relatively impervious to a number better. of interventions that have been tried by Because of the previous findings—that countries around the world.45 knowledge rather than just time in school is As we discussed in section 2, the rel- what counts —policies must pay more atten- evant cognitive skills are the product of a tion to the quality of schools. Particularly in variety of influences. A wide body of litera- terms of aggregate growth, school attain- ture emphasizes the key impacts of families, ment has a positive impact only if it raises the cognitive skills of students—something 45 A substantial portion of the policy conundrums of that does not happen with sufficient regu- the past is the lack of reliable evaluations of alternative larity in many developing countries. programs. See the discussion in Glewwe and Michael For developing countries, the sporadic or Kremer (2006) about how better information can be developed through random assignment experimentation nonexistent assessment of student knowl- or other approaches that better identify the causal impacts edge is an especially important issue—cor- of various factors. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 659 peers, schools, and ability (cf. Hanushek currently existing gaps could reasonably be 2002). From the standpoint of economic significantly reduced by resource policies impacts, the source of any change in cog- within existing institutional structures. nitive skills does not matter. For exam- Although uncertainty exists about the ple, a health and nutrition program that best set of policies, our candidate for the improves children’s ability to concentrate fundamental failure of current school policy and thus leads to gains in basic achieve- is the lack incentives for improved student ment is as relevant as an improvement in performance. Moreover, recent research the quality of teachers in the child’s school. suggests that three sets of policies can help At the same time, most societies are more to improve the overall incentives in schools: willing to intervene through schooling— strong accountability systems that accu- which has been a domain of generally rec- rately measure student performance, local ognized public involvement—than through autonomy that allows schools to make appro- policies that become intertwined with the priate educational choices, and choice and family. Thus, policy attention has focused competition in schools so that parents can largely on what can be done through schools. enter into determining the incentives that The important thing for policy is sim- schools face. Hanushek and Woessmann ply that the intervention actually improves (2007) provide a more detailed discussion achievement. Many of the policy initiatives, of policy options to improve cognitive skills both in developed and developing countries, along with reviewing the existing evidence. have not proved successful in improving When asking how education policies in achievement, and this has led to some cyni- developing countries can create the compe- cism about the efficacy of interventions. tencies and learning achievements required While an in-depth discussion of the school for their citizens to prosper in the future, policy issues goes beyond the scope of this the binding constraint seems to be insti- paper, the existing research strongly sug- tutional reforms, not resource expansions gests that getting the substantial improve- within the current institutional systems. For ments in the quality of schools that are educational investments to translate into necessary requires structural changes in student learning, all the people involved in schooling institutions. The research on the education process have to face the right the potential impact of increased school incentives that make them act in ways that resources has been controversial. Our own advance student performance. assessment is that the extensive research has shown that simply putting more resources Appendix: Data on Cognitive Skills into schools—pure spending, reduced class The analysis in this paper relies upon a sizes, increased teacher training, and the variety of cognitive achievement tests. The like—will not reliably lead to improve- central analysis of growth and macroeco- ments in student outcomes when the over- nomic performance uses information from all institutional structure is not changed the international tests of a set of nations vol- (see, for example, Hanushek 1995, 2003 untarily participating in a cooperative ven- and Woessmann 2005, 2007). But, the mag- ture under the International Association for nitude of the challenge—particularly in the Evaluation of Educational Achievement developing countries—makes it unneces- (IEA) and from the OECD. The most recent sary to replay these arguments. Even those of the IEA tests is the TIMSS for 2003, who argue that general resource policies although there is a much longer history are efficacious would not argue that the identified below along with its history in 660 Journal of Economic Literature, Vol. XLVI (September 2008) testing reading (PIRLS). The OECD tests, Interestingly, the TIMSS tests with their called the PISA, began in 2000 and cover curricular focus and the PISA tests with all OECD countries plus others. their real-world application focus are highly These tests have different groups of coun- correlated at the country level. For exam- tries, sampling of students, and perspectives ple, the correlation coefficients between on what should be tested (see Teresa Smith the TIMSS 2003 tests of eighth graders and Neidorf et al. 2006). Our approach is to PISA 2003 tests of fifteen-year-olds across aggregate across the variety of tests for each the nineteen countries participating in both country in order to develop a composite are 0.87 in math and 0.97 in science, and measure of performance. Perhaps the most they are 0.86 in both math and science important issue is whether or not the tests are across the twenty-one countries participat- measuring a common dimension of cognitive ing both in the TIMSS 1999 tests and the skills. The TIMSS tests of math and science PISA 2000 /02 tests. Similarly, there is a high are developed by an international panel but correlation at the country level between the are related to common elements of primary curriculum based student tests of TIMSS and secondary school curriculum, while the and the practical literacy adult examina- PISA tests are designed to be assessments tions of IALS (Hanushek and Zhang 2008). of more applied ideas. In our develop- Tests with very different foci and perspec- ment of a common metric we also employ tives tend, nonetheless, to be highly related, data from the U.S. National Assessment of lending support to our approach of aggre- Educational Progress (NAEP). That test, gating different tests for each country. which is conceptually closest to the TIMSS The general idea behind our approach tests except that it relates more directly to to aggregation is that of empirical calibra- U.S. curriculum, provides information over tion. We rely upon information about the time on a consistent basis. overall distribution of scores on each test to Part of the analysis on individual returns compare national responses. This contrasts relied on the IALS, a set of tests given to with the psychometric approach to scaling twenty countries between 1994–98. These that calls for calibrating tests through use tests cover several functional areas includ- of common elements on each test. In real- ing: prose literacy—the knowledge and ity, each of the testing situations described skills needed to understand and use infor- below is a separate activity with no general mation from texts including editorials, news attempt to provide common scaling. stories, poems, and fiction; document lit- The strength of our approach is that dif- eracy—the knowledge and skills required ferent tests across a common subject mat- to locate and use information contained in ter tend to be highly correlated at both the various formats, including job applications, individual and aggregate level. Thus, the payroll forms, transportation schedules, distributional information that we use is maps, tables, and graphics; and quantitative closely related to variations in individual literacy—the knowledge and skills required performance levels. to apply arithmetic operations, either alone As shown in table A1, there are data or sequentially, to numbers embedded in from international student achievement printed materials, such as balancing a check- tests on twelve international testing occa- book, calculating a tip, completing an order sions. Containing separate tests in different form, or determining the amount of interest subjects and at different age groups, these on a loan from an advertisement. They were testing occasions yield thirty-six separate designed to be very practical. test observations altogether, each with Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 661

Table A1 The International Student Achievement Tests

Abbr. Study Year Subject Agea,b Countriesc 1 FIMS First International 1964 Math 13,FS 11 Mathematics Study 2 FISS First International Science 1970271 Science 10,14,FS 14,16,16 Study 3 FIRS First International Reading 1970272 Reading 13 12 Study 4 SIMS Second International 1980282 Math 13,FS 17,12 Mathematics Study 5 SISS Second International Science 1983284 Science 10,13,FS 15,17,13 Study 6 SIRS Second International 1990291 Reading 9,13 26,30 Reading Study 7 TIMSS Third International 1994295 Math/Science 9(314), 25,39,21 Mathematics and Science 13(718),FS Study 8 TIMSS-Repeat TIMSS-Repeat 1999 Math/Science 13(8) 38 9 PISA 2000/02 Programme for International 2000102 Reading/ Math/ 15 31110 Student Assessment Science 10 PIRLS Progress in International 2001 Reading 9(4) 34 Reading Literacy Study 11 TIMSS 2003 Trends in International 2003 Math/Science 9(4),13(8) 24,45 Mathematics and Science Study 12 PISA 2003 Programme for International 2003 Reading/ Math/ 15 40 Student Assessment Science

Notes: a Grade in parentheses where grade level was target population. b FS 5 final year of secondary education. c Number of participating countries that yielded internationally comparable performance data.

between eleven and forty-five participating In order to make performance on the countries with internationally comparable different international tests comparable, performance data. Most of the tests were Hanushek and Woessmann (forthcom- conducted by the IEA, with the exception of ing) develop a common metric to adjust the OECD-conducted PISA tests.46 both the level of test performance and the

46 In this study, we do not include the two tests con- bias to the international testing. By contrast, the tests ducted by the International Assessment of Educational included here are not associated with the curriculum in Progress (IAEP) in 1988 and 1991, because they used any particular country, but have been devised in an inter- the U.S. NAEP test as their testing instrument, which is national cooperative process between all participating geared to the U.S. curriculum and may thus introduce countries. 662 Journal of Economic Literature, Vol. XLVI (September 2008) variation of test performance through two skills of graduates are constant over time, data transformations. First, because the this averaging is appropriate and uses the United States has both participated in all available information to obtain the most of the international tests and has main- reliable estimate of skills. If on the other tained its own longitudinal testing (the hand there is changing performance, this NAEP), Hanushek and Woessmann (forth- averaging will introduce measurement coming) calibrate the U.S. international error of varying degrees over the sample of performance over time to the external economic data (1960–2000). The analysis in standard—thus benchmarking each of the Hanushek and Woessmann (forthcoming) separate international tests to a comparable shows some variation over time, but there level. Second, while this provides a rela- is no clear way to deal with this here. tive comparison of countries taking each When looking at effects of the distribution test over time, it is also necessary to estab- of cognitive skills, we go beyond the mean lish the variance on the tests so that direct performance of a country’s students and cal- compatibility of countries taking different culate the share of students above a certain tests can be established. The calibration of test-score threshold, as well as the perfor- the dispersion of the tests relies on holding mance of students at different percentiles the score variance constant within a group of a country, both based on our transformed of countries with stable education systems metric of scores. This requires going into the (defined in terms of secondary school atten- details of the student-level micro data for dance rates) over time. For this, Hanushek each international test, which we can do for and Woessmann (forthcoming) use the each test in mathematics and science with thirteen OECD countries who had half or the exception of FIMS, where the micro data more students completing upper secondary seem no longer accessible. See Hanushek and education around the beginning of interna- Woessmann (forthcoming) for details. tional testing in the 1970s as the “stable” We observe a total of seventy-seven coun- country group, and standardize variances tries that have ever participated in any of to their group performance on the 2000 the nine international student achievement PISA tests. The details of the transforma- tests in mathematics and science.47 Fifty of tion are found in Hanushek and Woessmann these are included in the analyses of eco- (forthcoming). nomic growth.48 Twenty-five countries are To create our measure of cognitive skills employed in this study, we use a simple 47 The latest round of PISA results, conducted in 2006 average of the transformed mathemat- and released in December 2007, is not contained in our ics and science scores over all the avail- analyses because it substantially postdates our 1960–2000 period of observation. There are five countries participat- able international tests in which a country ing in PISA 2006 that had never participated on a previous participated, combining data from up to international test. Likewise, the 2006 round of the PIRLS nine international testing occasions and primary-school reading test includes three additional par- ticipants without prior international achievement data. thirty individual test point observations. 48 There are four countries with test-score data which This procedure of averaging performance have a few years missing at the beginning or end of the over a forty year period is meant to proxy 1960–2000 period on the income data in the Penn World Tables. In particular, data for Tunisia starts in 1961 rather the educational performance of the whole than 1960, and data for Cyprus (1996), Singapore (1996), labor force, because the basic objective is and Taiwan (1998) end slightly earlier than in 2000. These not to measure the skills of students but to countries were included in the growth regressions by estimating average annual growth over the available thirty- obtain an index of the skills of the workers six–thirty-nine year period rather than the whole forty in a country. If the quality of schools and year period. Hanushek and Woessmann: The Role of Cognitive Skills in Economic Development 663 not included in the growth database due to tion.” Quarterly Journal of Economics, 116(1): lack of data on economic output or because 313–50. Angrist, Joshua D., and Victor Lavy. 1997. “The Effect they drop out of the sample for a standard of a Change in Language of Instruction on the exclusion criterion in growth analyses (fifteen Returns to Schooling in Morocco.” Journal of Labor former communist countries, three countries Economics, 15(1): S48–76. Ashenfelter, Orley, and Alan B. 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