The first column of Table 7 reports the main regression showing the relationship between the rate of wage growth and the source country characteristics. With one important exception, variables that presumably increase the cohort’s effective human capital tend to have a positive impact on the rate of wage growth, suggesting weak relative complementarity in the human capital production function. Consider, for example, the index of openness in the source country. Immigrants originating in open economies both earn more and experience faster wage growth. Moreover, the effect is numerically important: a change in the index from 31 to 80, which are the 1975 openness indices for Spain and Jamaica respectively, implies a 7 percentage point increase in the rate of wage growth.
The regressions also indicate that immigrants originating in countries with higher Gini coefficients experience slower wage growth. And, again, the effect is numerically important. In 1975, the Gini coefficient for Czechoslovakia was 21, while for Mexico it was 58. This difference in the Gini coefficient implies a 14-percentage point differential in the rate of wage growth.
Table 7 also shows that the distance between the source country and the United States, a measure of the difficulty of return migration, has a significant positive effect on the rate of wage growth. Immigrants who originate in a country that is 5,500 miles away will, on average, experience about 6 percentage points greater wage growth than immigrants who come from a country that is 500 miles away. The regression, however, shows that the political instability variable does not play a significant role in determining the rate of wage growth.
The regression also suggests immigrant clustering reduces the rate of wage growth. The estimated coefficient of the Herfindahl index suggests that a reduction in this index from .25 to .04 (or roughly from the average Herfindahl index in the immigrant population to that found among natives) would increase the rate of wage growth by about 3 percentage points. Of course, the regressions do not tell us why this correlation arises.
The clustering of immigrants, for instance, may have a direct impact on their economic opportunities simply because the increase in labor supply reduces wages (particularly if immigrants are immobile). Residential segregation, however, may also change the immigrant’s effective human capital by reducing the incentives to invest in English language proficiency, or by “tying” the immigrants to specific regions of the country. It would be of great interest to determine the channels through which immigrant clustering slows down the rate of economic progress.