Can you reform your way to higher growth?

There are a lot of plausible policy changes that could raise the potential GDP of the U.S. (or many other countries). Whether those policy changes would lead to an appreciable change in growth rates is unclear, because the force that pushes economies towards a balanced growth path - convergence - operates very slowly. Then again, who says that a balanced growth path even exists?

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Academic References

  1. Barro, R. J. and Sala-i-Martin, X. (1992) “Convergence,” Journal of Political Economy, 100(2), pp. 223–251. Available at: Link.
    • Abstract

      A key economic issue is whether poor countries or regions tend to grow faster than rich ones: are there automatic forces that lead to convergence over time in the levels of per capita income and product? The authors use the neoclassical growth model as a framework to study convergence across the forty-eight contiguous U.S. states. They exploit data on personal income since 1840 and on gross state product since 1963. The U.S. states provide clear evidence of convergence, but the findings can be reconciled quantitatively with the neoclassical model only if diminishing returns to capital set in very slowly. Copyright 1992 by University of Chicago Press.

  2. Barro, R. J. (2016) “Economic Growth and Convergence: Applied to China,” China & World Economy, 24(5), pp. 5–19. doi: 10.1111/cwe.12172.
  3. Barro, R. J. and Sala-i-Martin, X. (1991) “Convergence across States and Regions,” Brookings Papers on Economic Activity, 22(1), pp. 107–182. Available at: Link.
    • Abstract

      No abstract is available for this item.

  4. Bils, M. and Klenow, P. J. (2000) “Does Schooling Cause Growth?,” The American Economic Review. American Economic Association, 90(5), pp. pp. 1160–1183. Available at: Link.
    • Abstract

      A number of economists find that growth and schooling are highly correlated across countries. A model is examined in which the ability to build on the human capital of one’s elders plays an important role in linking growth to schooling. The model is calibrated to quantify the strength of the effect of schooling on growth by using evidence from the labor literature on Mincerian returns to education. The upshot is that the impact of schooling on growth explains less than one-third of the empirical cross-country relationship. The ability of reverse causality to explain this empirical relationship is also investigated.

  5. Cohen, D. and Soto, M. (2007) “Growth and human capital: good data, good results,” Journal of Economic Growth. Springer Netherlands, 12(1), pp. 51–76.
    • Abstract

      We present a new data set for years of schooling across countries for the 1960–2000 period. The series are constructed from the OECD database on educational attainment and from surveys published by UNESCO. Two features that improve the quality of our data with respect to other series, particularly for series in first-differences, are the use of surveys based on uniform classification systems of education over time, and an intensified use of information by age groups. As a result of the improvement in quality, these new series can be used as a direct substitute for Barro and Lee’s (2001; Oxford Economic Papers, 3, 541–563) data in empirical research. In standard cross-country growth regressions we find that our series yield significant coefficients for schooling. In panel data estimates our series are also significant even when the regressions account for the accumulation of physical capital. Moreover, the estimated macro return is consistent with those reported in labour studies. These results differ from the typical findings of the earlier literature and are a consequence of the reduction in measurement error in the series.

  6. Hanushek, E. and Woessmann, L. (2012) “Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation,” Journal of Economic Growth. Springer Netherlands, 17(4), pp. 267–321. Available at: Link.
    • Abstract

      We develop a new metric for the distribution of educational achievement across countries that can further track the cognitive skill distribution within countries and over time. Cross-country growth regressions generate a close relationship between educational achievement and GDP growth that is remarkably stable across extensive sensitivity analyses of specification, time period, and country samples. In a series of now-common microeconometric approaches for addressing causality, we narrow the range of plausible interpretations of this strong cognitive skills-growth relationship. These alternative estimation approaches, including instrumental variables, difference-in-differences among immigrants on the U.S. labor market, and longitudinal analysis of changes in cognitive skills and in growth rates, leave the stylized fact of a strong impact of cognitive skills unchanged. Moreover, the results indicate that school policy can be an important instrument to spur growth. The shares of basic literates and high performers have independent relationships with growth, the latter being larger in poorer countries.

  7. Hanushek, E. A. and Kimko, D. D. (2000) “Schooling, Labor-Force Quality, and the Growth of Nations,” The American Economic Review. American Economic Association, 90(5), pp. pp. 1184–1208. Available at: Link.
    • Abstract

      Direct measures of labor-force quality from international mathematics and science 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.

  8. Hendricks, L. (2010) “Cross-country variation in educational attainment: structural change or within-industry skill upgrading?,” Journal of Economic Growth. Springer Netherlands, 15(3), pp. 205–233. Available at: Link.
    • Abstract

      Educational attainment varies greatly across countries and within countries over time. This paper asks whether the variation in education is primarily due to industry composition or to within-industry skill intensities. The main finding is that within-industry variation accounts for at least two-thirds of the cross-country and the time-series variation in educational attainment. The within-industry education gaps are broadly consistent with a model of industry neutral cross-country differences in skilled labor productivity. These results suggest that theories of educational development should focus on skill upgrading within industries rather than structural change.

  9. Hendricks, L. (2002) “How Important Is Human Capital for Development? Evidence from Immigrant Earnings,” The American Economic Review. American Economic Association, 92(1), pp. pp. 198–219. Available at: Link.
    • Abstract

      This paper offers new evidence on the sources of cross-country income differences. It exploits the idea that observing immigrant workers from different countries in the same labor market provides an opportunity to estimate their human-capital endowments. These estimates suggest that human and physical capital account for only a fraction of cross-country income differences. For countries below 40 percent of U.S. output per worker, less than half of the output gap relative to the United States is attributed to human and physical capital. (JEL O15, O41, F22)

  10. Jones, C. I. (2002) “Sources of U.S. Economic Growth in a World of Ideas,” American Economic Review, 92(1), pp. 220–239.
    • Abstract

      Rising educational attainment and research intensity in recent decades suggest that the U.S. economy is far from its steady state. This paper develops a model reconciling these facts with the stability of U.S. growth rates. In the model, long-run growth arises from the worldwide discovery of ideas, which depends on population growth. Nevertheless, constant growth can temporarily proceed at a faster rate, provided research intensity and educational attainment rise steadily over time. Growth accounting reveals that these factors explain 80 percent of recent U.S. growth, with less than 20 percent coming from world population growth.

  11. Parman, J. (2011) “American Mobility and the Expansion of Public Education,” The Journal of Economic History. Cambridge Univ Press, 71(01), pp. 105–132.
  12. Pritchett, L. (2001) “Where Has All the Education Gone?,” The World Bank Economic Review. Oxford University Press, 15(3), pp. pp. 367–391. Available at: Link.
    • Abstract

      Cross-national data show no association between increases in human capital attributable to the rising educational attainment of the labor force and the rate of growth of output per worker. This implies that the association of educational capital growth with conventional measures of total factor production is large, strongly statistically significant, and negative. These are "on average" results, derived from imposing a constant coefficient. However, the development impact of education varied widely across countries and has fallen short of expectations for three possible reasons. First, the institutional/governance environment could have been sufficiently perverse that the accumulation of educational capital lowered economic growth. Second, marginal returns to education could have fallen rapidly as the supply of educated labor expanded while demand remained stagnant. Third, educational quality could have been so low that years of schooling created no human capital. The extent and mix of these three phenomena vary from country to country in explaining the actual economic impact of education, or the lack thereof.

  13. Sala-i-Martin, X. X. (1996) “The Classical Approach to Convergence Analysis,” Economic Journal, 106(437), pp. 1019–1036. Available at: Link.
    • Abstract

      The concepts of sigma-convergence, absolute beta-convergence and conditional beta-convergence are discussed in this paper. The concepts are applied to a variety of data sets that include a large cross-section of 110 countries, the subsample of OECD countries, the states within the United States, the prefectures of Japan, and regions within several European countries. Except for the large cross-section of countries, all data sets display strong evidence of sigma-convergence and absolute beta-convergence. The cross-section of countries exhibits sigma-divergence and conditional beta-convergence. The speed of conditional convergence, which is very similar across data sets, is close to 2 percent per year. Copyright 1996 by Royal Economic Society.

  14. Solow, R. M. (1956) “A Contribution to the Theory of Economic Growth,” The Quarterly Journal of Economics. Oxford University Press, 70(1), pp. pp. 65–94. Available at: Link.
    • Abstract

      I. Introduction, 65.–II. A model of long-run growth, 66.–III. Possible growth patterns, 68.–IV. Examples, 73.–V. Behavior of interest and wage rates, 78.–VI. Extensions, 85.–VII. Qualifications, 91.

  15. Tabarrok, A. and Goldschlag, N. (2015) Is Regulation to Blame for the Decline in American Entrepreneurship? 15-11. George Mason University Working Paper. Available at: Link#.

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