Human Capital Externalities
The previous section illustrated how a natural form of human capital externalities can emerge in the presence of capital-skill complementarities combined with labor market imperfections.
This is not the only channel through which human capital externalities may arise.406
Many economists believe that the human capital stock of the workforce creates a direct non- pecuniary (technological) spillover on the productivity of each worker. In The Economy of Cities, Jane Jacobs, for example, argued for the importance of human capital externalities, and suggested that the concentration of economic activity in cities is partly a result of these externalities and also acts as an engine of economic growth because it facilitates the exchange of ideas among workers and entrepreneurs. In the growth literature, a number of well-known papers, including Robert Lucas’ (1988) paper and Azariadis and Drazen (1990), suggest that such technological externalities are important and play a major role in the process of economic growth. Human capital externalities are interesting in their own right, since if such external effects are present, the competitive price system may be inefficient (since it will fail to internalize these externalities, particularly if they take place across firm boundaries). Human capital externalities are also important for our understanding of the sources of income differences across countries. Our discussion of the contribution of physical and human capital to cross-country income differences in Chapter 3 showed that differences in human capital are unlikely to account for a large fraction of cross-country income differences, unless external effects are important.
At this point, it is therefore useful to briefly review the empirical evidence on the extent of human capital externalities. Early work in the area, in particular, the paper by James Rauch (1993) tried to measure the extent of human capital externalities by estimating quasi- Mincerian wage regressions, with the major difference that average human capital of workers in the local labor market is also included on the right-hand side.
More specifically, Rauch estimated models of the following form:
where
is a vector of controls, Sjmi is the years of schooling of individual j living/working in labor market m, and Sm is the average years of schooling of workers in labor market m. Without this last term, this equation would be similar to the standard Mincerian wage regressions discussed above, and we would expect an estimate of the private return to schooling Yp between 6 and 10%. When the average years of schooling, Sm, is also included in the regression, its coefficient γe measures the external return to schooling in the same units. For example, if γe is estimated to be of the same magnitude as γp, we would conclude that external returns to schooling are as important as private returns (which would correspond to very large externalities).
Rauch estimated significant external returns, with the magnitude of the external returns often exceeding the private returns. External returns of this magnitude would imply that human capital differences could play a much more important role as a proximate source of cross-country differences in income per capita than implied by the computations in Chapter 407
3. However, Rauch’s regressions exploited differences in average schooling levels across cities, which could reflect many factors that also directly affect wages. For example, wages are much higher in New York City than Ames, Iowa, but this is not only the result of the higher average education of New Yorkers. A more convincing estimate of external returns necessitates a source of exogenous variation in average schooling.
Acemoglu and Angrist (2000) exploited differences in average schooling levels across states and cohorts resulting from changes in compulsory schooling and child labor laws.
These laws appear to have had a large effect on schooling, especially at the high school margin. Exploiting changes in average schooling in state labor markets driven by these law changes, Acemoglu and Angrist estimate external returns to schooling that are typically around 1 or 2 percent and statistically insignificant (as compared to private returns of about 10%). These results suggest that there are relatively small human capital externalities in local labor markets. This result is confirmed by a study by Duflo (2004) using Indonesian data and by Ciccone and Perri (2006). Moretti (2002) also estimates human capital externalities, and he finds larger effects. This may be because he focuses on college graduation, but also partly reflects the fact that the source of variation that he exploits, changes in age composition and the presence of land-grant colleges, may have other effects on average earnings in area. Overall, the evidence appears to suggest that local human capital externalities are not very large, and calibration exercises as those in Chapter 3 that ignore these externalities are unlikely to lead to significant downward bias in the contribution of human capital to cross-country income differences.The qualification “local” in the above discussion has to be emphasized, however. The estimates discussed above focus on local externalities originally emphasized by Jacobs. Nevertheless, if a few very talented scientists and engineers, or other very skilled workers, generate ideas that are then used in other parts of the country or even in the world economy, there may exist significant global human capital externalities. Such global external effects would not be captured by the currently available empirical strategies. Whether such global human capital externalities are important is an interesting area for future research.
10.8.