HUMAN CAPITAL AND GROWTH: THEORY AND EVIDENCE

HUMAN CAPITAL AND GROWTH: THEORY AND EVIDENCE

November 1989 | Paul M. Romer
This paper by Paul M. Romer explores the role of human capital in endogenous growth theory. It outlines a theoretical framework that distinguishes between intangible assets like education and experience, and knowledge or science, and examines how these factors affect production. The key finding is that the initial level of literacy, for example, may be crucial for understanding subsequent growth, despite the usual emphasis on input change rates in growth accounting. Empirically, while literacy may not significantly predict growth rates in cross-country regressions, it helps predict the subsequent rate of investment and, indirectly, growth. The paper also discusses the effects of measurement error and the importance of correcting for it in data analysis. The theoretical framework is detailed, focusing on the production of goods, the role of science and knowledge, and the production of designs. It highlights the nonrivalrous and nonexcludable nature of knowledge, which complicates the traditional assumptions of perfect competition and price-taking behavior. The paper concludes by discussing the empirical implications, suggesting that the level of human capital variables like education and scientific talent will be correlated with both the rate of income growth and the share of investment in physical capital.This paper by Paul M. Romer explores the role of human capital in endogenous growth theory. It outlines a theoretical framework that distinguishes between intangible assets like education and experience, and knowledge or science, and examines how these factors affect production. The key finding is that the initial level of literacy, for example, may be crucial for understanding subsequent growth, despite the usual emphasis on input change rates in growth accounting. Empirically, while literacy may not significantly predict growth rates in cross-country regressions, it helps predict the subsequent rate of investment and, indirectly, growth. The paper also discusses the effects of measurement error and the importance of correcting for it in data analysis. The theoretical framework is detailed, focusing on the production of goods, the role of science and knowledge, and the production of designs. It highlights the nonrivalrous and nonexcludable nature of knowledge, which complicates the traditional assumptions of perfect competition and price-taking behavior. The paper concludes by discussing the empirical implications, suggesting that the level of human capital variables like education and scientific talent will be correlated with both the rate of income growth and the share of investment in physical capital.
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