THE ECONOMIC PROGRESS OF IMMIGRANTS: Investments in Education 2

The remaining columns of the table report regressions of the change in educational attainment on the source country characteristics. For the most part, the regressions confirm the results reported in the previous section. The source country characteristics tend to affect investments in education in the same way that they affect the rate of wage growth.

Immigrants who originate in countries where the income distribution has a large Gini coefficient (and presumably there is a large rate of return to skills) acquire less schooling in the post-migration period; immigrants who originate in open economies acquire more schooling; and immigrants who originate in richer countries acquire less schooling (but this anomalous correlation is not significant).
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Investments in Education

The previous section documented that the rate of wage growth experienced by immigrants cohorts responded to source country characteristics that proxy for either the effective rate of human capital or the discounting factor. This section shows more directly that source country characteristics do indeed alter the rate of human capital accumulation by examining the determinants of investments in educational attainment in the post-migration period.

I computed the change in educational attainment experienced by each of the immigrant cohorts (by country of origin, year of arrival, and age at migration) during their first ten years in the United States. I then estimated regressions, identical to those presented in earlier sections, that describe both the extent of convergence in educational attainment across immigrant cohorts, as well as the link between investments in schooling and source country characteristics. The estimated regressions are reported in Table 8.

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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics 6

Presumably, persons who know the language would have an easier time adapting in the United States (although this effect could be attenuated by residential segregation). The 1970 U.S. Census, however, does not contain any information on English language proficiency, so that we cannot observe the initial language skills of the immigrants who arrived in the 1960s. I used the 1980 Census to calculate the probability that immigrants who arrived between 1975 and 1979 spoke English well or very well.

This statistic was calculated for each cohort by country of origin and age-at-arrival. The last two columns of Table 7 report the regression results obtained when one includes this variable into the model (and when the regression is estimated in the subsample of immigrants who migrated in 1975-79). English language proficiency at the time of entry has an independent positive impact on the rate of wage growth, but does not change the impact of most of the other variables in the model. The last column in the table shows that the impact of English language proficiency becomes insignificant if we control for the educational attainment of the cohort.
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics 5

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The one anomaly in the regression is the impact of per-capita GDP in the source country. This variable has a strong positive effect on the log entry wage, but a strong negative effect on the rate of wage growth. The negative correlation reported in the first column of Table 7, however, turns out to be very sensitive to model specification. Consider, for example, the regressions reported in columns 3 and 4, which add a vector of country-of-origin fixed effects to the specification. Most of the source country variables have the same impact as in the simpler regression, so that a decrease in income inequality within the country raises the rate of wage growth of immigrants in the United States. The coefficient of per-capita GDP, however, becomes insignificant.

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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics 4

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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.
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics 3

The distance from the country of origin to the United States (in thousands of miles).24 Boijas and Bratsberg (1996) have shown that the return migration rate of immigrants in the United States is negatively correlated with distance from the source country. This empirical finding suggests that immigrants who originate in far-away countries are more likely to view their migration to the United States as permanent, and have greater incentives to invest in U.S.-specific capital. In terms of the theoretical framework, longer distances decrease the probability of outmigration and increase the discounting factor p. Distance from the source country, therefore, should have a positive effect on the rate of wage growth.

Political conditions in the country of origin. Barro and Lee (1994) used the Banks (1986) Cross-National Time-Series Data File to calculate the number of revolutions (per year) that occurred in the various countries in the periods 1960-64, 1965-69, 1970-74, and 1975-79. Political instability in the country of origin would likely have an impact on the return migration rate, and should again affect the discounting factor. A higher degree of political instability, therefore, would presumably lead to higher rates of wage growth in the United States.

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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics 2

2. The Gini coefficient of the source country’s income distribution. Boijas (1987) has argued that immigrants originating in countries that offer a high rate of return to skills are more likely to be negatively selected, will have a smaller effective human capital stock at the time of migration, and will earn less in the United States. A higher rate of return to skills implies a more disperse distribution of income. The Gini coefficient of the source country’s income distribution should then have a negative impact on the rate of wage growth. Deininger and Squire (1996) have constructed various measures of income inequality, including the Gini coefficient, for most countries since 1960. I used these data to obtain measures of the Gini coefficients in four years: 1960, 1965, 1970, and 1975.
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Immigrant Economic Progress and Source Country Characteristics

As we have seen, there are huge differences in log entry wages across national origin groups. Many studies have found that the initial economic performance of immigrants in the United States is strongly correlated with source country characteristics. For example, Boijas (1987) reports that immigrant wages depend positively on the per-capita GDP of the source country and negatively on measures of income inequality. Similarly, Jasso and Rosenzweig (1986) report a positive correlation between immigrant wages and a variable indicating if the country of origin receives a Voice of America broadcast (presumably because these broadcasts provide information about the United States).
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Wage Convergence 9

These doubts are reinforced when we use an alternative instrument. We have three measures of the wage for the immigrants who arrived between 1960 and 1970. For these immigrants, we can observe their wage in 1970, 1980, and 1990. We can use this subsample of immigrants to estimate a convergence coefficient by regressing the 1980-90 rate of wage growth on the 1980 log wage. The data, however, also allow us to instrument the 1980 wage by the group’s 1970 wage. The resulting OLS and IV estimates are reported in the bottom panel of Table 5. The IV results show that the correlation between wage levels and wage growth remains positive even after we control for educational attainment.
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THE ECONOMIC PROGRESS OF IMMIGRANTS: Wage Convergence 8

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Finally, there is probably measurement error in the log entry wage. Any measurement error in this wage will impart a negative bias on its coefficient (towards minus one). The spurious negative correlation arises because the log entry wage appears on both sides of the equation, but with different signs. One can assess the sensitivity of the results to measurement error by using instrumental variables to eliminate the spurious correlation.

The construction of the Census data suggests two alternative instruments for the log entry wage. The regressions reported in the first panel of Table 4 use the rate of wage growth observed for the immigrant cohorts that arrived in 1960-64, 1965-69, 1970-74, or 1975-79. To eliminate the measurement error, we can use the log entry wage of the preceding immigrant cohort as an instrument for the entry wage of a particular cohort. Consider, for example, the Mexican immigrants who were 25-34 years old in 1980 and who entered the United States between 1975 and 1979. The proposed instrument would be the wage of Mexican immigrants who were 25-34 in 1980 but who entered the country between 1970 and 1974. The construction of this instrument, of course, implies that the immigrants who arrived between 1960 and 1964 do not contribute any observations to the regression (since no preceding cohort is observed for this group).
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