Appendix 3: Table 18 lists the metropolitan areas used in the black regression samples for each year.
The differences in collected sample size of 1200 students and the regression sample size 1046 emanates from missing observation on certain variables in the model.
Note that the 1950 Census only asked a subset of households wage information, so the regression samples for that decade are smaller.
In addition, for the 1950 regression samples, I am able to include metro-average wages in 1940 as a covariate (this is not possible for the 1940 samples since the Census did not ask wage questions prior to 1940).
Including the foreign born slightly increases the number of metropolitan areas in the black regression samples (to 30 in 1940 and 23 in 1950), and the overall pattern of the estimates is similar.
The evidence presented so far is consistent with selection into high wage areas: including covariates or instrumenting for immigration decreases the estimated wage effects, and the coefficients on the proportion Southern black in the native white regression samples are positive.
As the treatment effects calculated for GSMs are significantly greater than 5 percentage points, augmenting the regression sample to include Employer Sponsored migrants dampens the magnitude of the estimated treatment effects.
I also estimate the annual wage regressions using two additional samples in order to further assess the sensitivity of my results to the number of metropolitan areas included in the regression samples (in the interest of brevity, I do not present these results, though they are available upon request).
The formal first-stage regressions, presented in Appendix 3: Table 19, support this conclusion, showing that predicted immigration has substantial power to explain the overall and race-specific immigrant shares of Northern labor markets in both the black and white regression samples.
