Convergence Between Black Immigrants and Black Natives Across ...

w i,g1,2 = p 0 + p 1 x i + a i p 2 ¯x g1 +(1 a i )p 2 ¯x g2 + v i,g1,2 . (13)
where a i again measures degree of assimilation. Given previous results, we would expect a to be
strongly negatively correlated with age of immigration.
Econometric Model
As before, we recover p 2 from running the baseline regression on natives 28
w i,g1 = p 0 + p 1 x i + p 2 ¯x g1 + v i,g1 (14)
We then estimate the following regression separately by each age of immigration
w i,g1,2 = b 0 + b 1 x i + b 2 ¯x g1 + b 3 ¯x g2 + v i,g1,2 (15)
For each age of immigration group we are left with the following two conditions that can be used for
identification:
a j p 2 b 2 j = 0 (16)
(1 a j )p 2 b 3 j = 0 (17)
where a j is a scalar that varies by age of immigration. Each regression will be estimated separately
for blacks, Hispanics, Asians, and whites. The definition of group 1 members remains the same. Members
of group 2 will be based solely on metropolitan area. Each immigrant will belong to one of both groups
and the weights on both groups depend on age of immigration. As before, variables in x i include education
(high school, some college, college, more than college), and a quadratic in potential experience. ¯x g1 and ¯x g2
includes the group averages of these variables.
7.2 Estimation
Case 1: Group 2 Members Are only Affected by own Characteristics
From (11) we see that a j is overidentified as p 2 and b 2 j are vectors and a j is a scalar. a j is recovered by
running a weighted regression of b 2 j on p 2 . The regression is run without a constant and the weights are the
absolute value of the t-statistics of the parameters contained in b 2 j .
28 Individuals with less than 100 peers in their metropolitan area were dropped in all regressions.
18