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Directed Technological Change & Cross Country Income Differences: A Quantitative Analysis

Jerzmanowski, Michal and Tamura, Robert (2017): Directed Technological Change & Cross Country Income Differences: A Quantitative Analysis.

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Abstract

Research aimed at understanding cross-country income differences finds that inputs of human and physical capital play a limited role in explaining those differences. However, most of this work assumes workers with different education levels are perfect substitutes. Does moving away from this assumption affect our conclusions about the causes of long run development? To answer this question we construct measures of skill-specific productivity and barriers to innovation for a large sample of countries over the period 1910-2010. We use a model of endogenous directed technological change together with a new data set on output and labor force composition across countries. We find that rich countries use labor of all skill categories more efficiently, however, in the absence or barriers to entry, poor countries would actually be more efficient at using low-skill labor. Our estimates imply that after 1950 the world technology frontier expanded much faster for college-educated workers than for those with lower skill sets. This technology diffused to many countries, allowing even poorer countries to experience relatively robust growth of high-skill-specific productivity. Their GDP growth failed to reflect that because of their labor composition; they have very few workers in the higher skilled category. Finally, we investigate the relative importance of factor endowments versus barriers to technology in explaining the current disparities of standards of living and find it to depend crucially on the value of the elasticity of substitution between skill-types. Under a lower value of 1.6, our model yields barrier estimates that are lower and relatively less important in explaining cross-country income differences: in this scenario physical and human capital account almost 70% of variance in 2010 GDP per worker in our sample. Using elasticity of 2.6, we find barriers that are higher and explain most of the variation in output. We provide some evidence that the higher value of elasticity is preferred.

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