We document five stylized facts of economic growth. (1) The “residual ” rather than factor accumulation accounts for most of the income and growth differences across nations. (2) Income diverges over the long run. (3) Factor accumulation is persistent while growth is not persistent and the growth path of countries exhibits remarkable variation across countries. (4) Economic activity is highly concentrated, with all factors of production flowing to the richest areas. (5) National policies closely associated with long-run economic growth rates. We argue that these facts do not support models with diminishing returns, constant returns to scale, some fixed factor of production, and that highlight the role of factor accumulation. Empirical work, however, does not yet decisively distinguish among the different theoretical conceptions of “total factor productivity growth.” Economists should devote more effort towards modeling and quantifying total factor productivity.

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test scores are strongly related to growth. Indirect specification tests are generally consistent with a causal link: direct spending on schools is unrelated to student performance differences; the estimated growth effects of improved labor-force quality hold when East Asian countries are excluded; and, finally, home-country quality differences of immigrants are directly related to U.S. earnings if the immigrants are educated in their own country but not in the United States. The last estimates of micro productivity effects, however, introduce uncertainty about the magnitude of the growth effects. (JEL O40, I20, J24) Recent theoretical analyses of international differences in growth rates have focused attention on the role of human capital. Most crosscountry empirical studies of long-run economic growth now include some proxy for human capital, and these are invariably significant. Data limitations have, however, forced severe

Standard theoretical arguments tell us that countries with relatively little capital benefit from financial integration as foreign capital flows in and speeds up the process of convergence. We show in a calibrated neoclassical model that conventionally measured welfare gains from this type of convergence appear relatively limited for the typical emerging market country. The welfare gain from switching from financial autarky to perfect capital mobility is roughly equivalent to a 1 % permanent increase in domestic consumption for the typical non-OECD country. This is negligible relative to the welfare gain from a take-off in domestic productivity of the magnitude observed in some of these countries.

This paper surveys the empirical literature on the growth effects of education and social capital. The main focus is on the crosscountry evidence for the OECD countries, but the paper also briefly reviews evidence from labour economics, to clarify where empirical work on education using macro data may be relatively useful. It is argued that on balance, the recent cross-country evidence points to productivity benefits of education that are at least as large as those identified by labour economists. The paper also discusses the implications of this finding. Finally, the paper reviews the emerging literature on the benefits of social capital. Since this

Three dimensions of the performance of firms in Ghana’s manufacturing sector are investigated in this paper: their technology and the importance of technical and allocative efficiency. We show that the diversity of factor choices in not due to a non-homothetic technology. Observable skills are not quantitatively important as determinants of productivity. Technical inefficiency is not lower in firms with foreign ownership or older firms and its dispersion across firms is similar to that found in other economies. Large firms face far higher relative labour costs than small firms. If these factor price differentials could be levelled out, substantial gains thorough improvements in allocative efficiency would be possible.

We study cross-country differences in the aggregate production function when skilled and unskilled labor are imperfect substitutes. We find that there is a skill bias in cross-country technology differences. Higher-income countries use skilled labor more efficiently than lower-income countries, while they use unskilled labor relatively and, possibly, absolutely less efficiently. We also propose a simple explanation for our findings: rich countries, which are skilled-labor abundant, choose technologies that are best suited to skilled workers; poor countries, which are unskilled-labor abundant, choose technologies more appropriate to unskilled workers. We discuss alternative explanations, such as capital-skill complementarity and differences in schooling quality. (JEL E13, E23, J31, O14) An important question in macroeconomics is how to accurately describe the relationship between aggregate inputs and aggregate output— the aggregate production function—and how this relationship varies across countries. Currently, most research focuses on the model (1) y � k � �Ah � 1 � �, where y, k, and h are, respectively, output, physical capital, and human capital per worker. This aggregate production function is generally allowed to vary across countries via the total factor productivity (TFP) term A 1� �. The typical finding is that TFP is higher in high-income countries. 1

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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 skillintensive 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. In particular, we show that in OECD economies it is crucial to isolate the two separate margins of primary/secondary and tertiary education. Interestingly, the latter type of schooling proves to be a factor of economic divergence.