A panel data approach is advocated and implemented for studying growth convergence. The familiar equation for testing convergence is reformulated as a dynamic panel data model and different panel data estimators are used to estimate it. The main usefulness of the panel approach lies in its ability to allow for differences in the aggregate production function across economies. This leads to results that are significantly different from those obtained from single cross-country regressions. In the process of identifying the individual 'country effect,' the point where neoclassical growth meets development economics can also be seen.
This paper presents a simple model of human capital, ideas, and economic growth that integrates contributions from several different strands of the growth literature. The model generates a regression specification that is very similar to that employed by Mankiw, Romer and Weil (1992), but the economics underlying the specification is very different. In particular, the model emphasizes the importance of ideas and technology transfer in addition to capital accumulation. The model suggests that cross-country data on educational attainment is most appropriately interpreted from the macro standpoint as something like an investment rate rather than as a capital stock. Finally, this setup helps to resolve a puzzle recently highlighted by the empirical growth literature concerning human capital and economic growth by following Bils and Klenow (1996) in emphasizing a relationship between wages and educational attainment that is consistent with Mincerian wage regressions.
The long literatures on the determinants of wage rates at the individual level and on the empirical relation between productivity and wage rates intersect when attention is focused on longitudinally linked employer-employee data. We estimate separate statistical components of wage rates associated with the observable individual characteristics, unobservable individual heterogeneity and unobservable employer heterogeneity. We define general human capital as the portable components of the full-time, full-year wage rate. Within each employer in the linked sample, we create employer-aggregates of the general human capital. We then estimate the relation between sales per employee, general human capital, and employer wage heterogeneity using micro data for the employing firms. The results reveal direct statistical links between the productivity outcome (sales/worker) and general human capital, controlling for firm-specific wage rate heterogeneity, which can be interpreted as specific human capital or as part of a firm-specific compensation strategy.
Using post-war data from forty-seven countries, we examine the cross-sectional relation between the mean growth rate of real product (growth) and variables suggested by the theoretical literature. Barro's hypothesis that the variability of monetary shocks adversely affects growth receives strong support, as do several other hypotheses. We also show that our variables influence growth by affecting both the fraction of product devoted to investment and the return to capital. Finally, while an index of civil liberty explains growth only marginally, it dominates the other variables in explaining investment.
This paper summarizes and tries to reconcile evidence from the microeconometric and empirical macro growth literatures on the effect of schooling on income and GDP growth. Much microeconometric evidence suggests that education is an important causal determinant of income for individuals within countries. At a national level, however, recent studies have found that increases in educational attainment are unrelated to economic growth. This discrepancy appears to be a result of the high rate of measurement error in first-differenced cross-country education data. After accounting for measurement error, the effect of changes in educational attainment on income growth in cross-country data is at least as great as microeconometric estimates of the rate of return to years of schooling. Another finding of the macro growth literature--that economic growth depends positively on the initial stock of human capital--is not robust when the assumption of a constant-coefficient model is relaxed.
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This paper extend previous research on the effect of investment on labor productivity at the country level by accounting for investment in R&D, as well as for investment in fixed and human capital. Privately-funded R&D investment is found to have a significant positive effect on productivity. Moreover, this effect appears to be quite large. This estimated social (national) rate of return to private R&D investment is about seven times as large as the return too investment in equipment and structures.
Barro and Lee (1994), in an influential empirical study of the determinants of economic growth, find that, whereas growth is positively related to male schooling, it is negatively related to female schooling. Stokey (1994) has suggested that this is largely due to the influence of four Asian countries (Hong Kong, Singapore, Taiwan and Korea) that have very high levels of growth but very low levels of female schooling, and that deleting the female education variable would cast doubt on the statistical significance of the male education variable. Deletion diagnostics and partial scatter plots are analysed to identify influential observations. The sensitivity of the Barro-Lee results to deleting selected countries from the sample and deleting female education from their growth equations is then examined. The results obtained point to the fragile nature of both the significant negative effect of female education and the significant positive effect of male education in the Barro-Lee model.
This paper examines whether the Solow growth model is consistent with the international variation in the standard of living. It shows that an augmented Solow model that includes accumulation of human as well as physical capital provides an excellent description of the cross-country data. The paper also examines the implications of the Solow model for convergence in standards of living, that is, for whether poor countries tend to grow faster than rich countries. The evidence indicates that, holding population growth and capital accumulation constant, countries converge at about the rate the augmented Solow model predicts.
The New Economy: Beyond the Hype explores the causes of differences in growth performance in the OECD area, in particular the acceleration of trend growth in the United States and a few other OECD economies over the past decade. It looks beyond the business cycle and asks what structural shifts, if any, have taken place in growth patterns in OECD economies in recent years. It also examines the implications of those shifts for policymakers.
The theoretical, conceptual, and practical difficulties with the use of cross national data on schooling are so large it is reasonable to avoid using this type of aggregate data for any purpose for which individual level data would do. There are, however, three questions for which the use of cross national data on schooling is necessary and could potentially help answer interesting questions. First, explaining the cross national differences in the evolution and dynamics of output growth is an important agenda. Do differences in the evolution and dynamics of schooling help explain the big facts about output growth? Largely, no. Second, the existence and magnitude of output externalities to schooling is an important question with at least normative policy implications, and evidence for externalities requires at least some level of spatial aggregation. Does the cross-national data provide support for output externalities? Largely, no. Third, cross national (or more broadly spatially aggregated) data allows the exploration of the impact on returns to schooling (or in the gap between private and social returns) of differences in economic environments. This last question has been and seems a promising line for future research.
This paper outlines a theoretical framework for thinking about the role of human capital in a model of endogenous growth. The framework pay particular attention to two questions: What are the theoretical differences between intangibles like education and experience on the one hand, and knowledge or science on the other? and How do knowledge and science actually affect production? One implication derived from this framework is that the initial level of a variable like literacy may be important for understanding subsequent growth. This emphasis on the level of an input contrasts with the usual emphasis from growth accounting on rates of change of inputs. The principal empirical finding is that literacy has no additional explanatory power in a cross-country regression of growth rates on investment and other variables, but consistent with the model, the initial level of literacy does help predict the subsequent rate of investment, and indirectly, the rate of growth.
This paper studies the puzzling lack of correlation between income and schooling in macro regressions. It is argued that the root of the puzzle is threefold. First, there is a problem of a proper definition of the way in which years of schooling should enter in a production function. Second, collinearity between physical and human capital stocks seriously undermines the ability of educational indicators to display any significance in growth regressions. And third, failure to cope with measurement error and endogeneity produces biased estimates. After dealing with these problems, the neoclassical approach to human capital is strongly supported by the data.
We examine the empirical implications of models that display perpetual growth through human capital accumulation in a case study of Taiwan. Our results show that incorporating a labor quality index into the labor input improves the performance of the growth model in Taiwan over the 1965–1989 period. The results are robust to alternative enhancements to raw labor input measures and to the inclusion of additional relevant variables often correlated with economic growth in developing countries. The evidence supports the theoretical suggestion that labor skill is a useful augmentation of the raw labor measure commonly used in empirical growth studies.
This paper demonstrates some techniques for testing the robustness of cross-section and panel data regressions, and applies them to the influential augmented Solow growth model. The paper focuses on robust estimation and analysis of sensitivity to measurement error. In particular, it is shown that estimated technology parameters and convergence rates are highly sensitive to measurement error.
Recent studies have found that economic growth appears to be unrelated to increases in educational attainment. In this note I show that there is a correlation in one dataset, but it is typically hidden by unrepresentative observations.
Several papers have suggested that the relationship between changes in average schooling and growth is weak in the cross-country data. This might call into question the relevance of micro estimates of returns to schooling, at least for developing countries. This paper examines the reliability of some of the aggregate evidence, and presents an alternative framework for analysing these questions.
We examine the contribution of human capital to economy-wide technological improvements through the two channels of innovation and imitation. We develop a theoretical model showing that skilled labor has a higher growth-enhancing effect closer to the technological frontier under the reasonable assumption that innovation is a relatively more skill-intensive activity than imitation. Also, we provide evidence in favor of this prediction using a panel dataset covering 19 OECD countries between 1960 and 2000 and explain why previous empirical research had found no positive relationship between initial schooling level and subsequent growth in rich countries.
This paper presents, using a new measure of human capital, robust results to show that in both the augmented and fully extended Solow model with conditional convergence, human capital plays a significant role in explaining economic growth among the OECD countries.
The paper investigates three models on the role of education in economic growth: human capital theory, a threshold effect, and interaction effects between education and technological activity. Data for 24 OECD countries on GDP, employment, and investment from the Penn World Tables over the period 1950 to 1990 was used. Five sources are used for educational data. The descriptive statistics suggest that the convergence in labor productivity levels among these nations appears to correspond to their convergence in schooling levels. However, econometric results showing a positive and significant effect of formal education on productivity growth among OECD countries are spotty at best. With only one or two exceptions, educational levels, the growth in educational attainment, and interaction effects between schooling and R&D were not found to be significant determinants of country labor productivity growth.
Max Weber attributed the higher economic prosperity of Protestant regions to a Protestant work ethic. We provide an alternative theory, where Protestant economies prospered because instruction in reading the Bible generated the human capital crucial to economic prosperity. County-level data from late 19thcentury Prussia reveal that Protestantism was indeed associated not only with higher economic prosperity, but also with better education. We find that Protestants’ higher literacy can account for the whole gap in economic prosperity. Results hold when we exploit the initial concentric dispersion of the Reformation to use distance to Wittenberg as an instrument for Protestantism.
The use of imperfect proxies for human capital introduces severe measurement errors in the empirical growth literature. This paper tries to improve on the measurement of human capital by allowing rates of return to education to differ between education levels and by weighing standard quantitative measures of education (years of schooling) by an indicator of the quality of education (student performance on cognitive achievement tests). With this improved measurement of education, 45 percent of the world-wide dispersion in levels of economic development (as measured by per-capita income) can be accounted for by differences in human capital. Leaving countries with imputed human-capital data, which may be further contaminated by classical measurement error, out of the sample, human-capital differences account for as much as 60 percent of the income dispersion. In the sample of OECD countries, virtually the whole income dispersion can be accounted for by differences in quality-adjusted human capital. The quality adjustment of the human-capital measure seems to be much more crucial for the development-accounting results than recent attempts to improve on the data recording of the quantity of education. The results suggest that the humancapital- augmented neoclassical growth model is a useful framework for understanding international development differences, while an effect of human capital on technical differentiation across countries cannot be substantiated.
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