Introduction to Modern Economic Growth 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 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: ln Wj,m = Xj,m β + γ p Sj,m + γ e Sm , where Xj,m is a vector of controls, Sj,m 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 γ p between and 10% When the average years of schooling, Sm , is also included in the regression, its coefficient γ e measures the external return to schooling in the same units For example, if γ e is estimated to be of the same magnitude as γ p , we would conclude that external returns to 493