IN an article published in this review (Antman & Duncan, 2015), we document how racial identity responds to state affirmative action policy. A coding error was recently brought to our attention that resulted in 0.55% of our sample being misclassified in terms of their African ancestry.1 We regret and apologize for this error. Although the error affected only a tiny percent of the overall sample, the correction changes the conclusion of how individuals with multiracial African ancestry respond to state affirmative action bans, from a negative and statistically significant effect to a positive and statistically significant effect. The corrected table 3 shows the updated results. The coefficients for college-aged individuals with African ancestry reported in table 5 are also now positive, but are no longer statistically significant at conventional levels. Correcting the error does not change the conclusions for individuals with only African ancestry or no African ancestry. None of the Asian ancestry classifications, and thus none of the results for individuals with Asian ancestry (table 4 and the last two columns of table 5), were affected by the coding error. There are no meaningful changes to the summary statistics in table 2 except in the column for those with multiracial black ancestry. The most notable change is the fraction of individuals with multiracial black ancestry who self-identify as black: 49.37% in the original table and 90.86% in the updated table.2 (For further explanation and a complete set of updated results, see Antman & Duncan, 2019.) We continue to find that racial identity responds to state affirmative action policy, albeit with a different conclusion for multiracial blacks, and we are now able to distinguish stronger effects for multiracial individuals with more distant connections to their minority group.This is the original abstract: We link data on racial self-identification with changes in state-level affirmative action policies to ask whether racial self-identification responds to economic incentives. We find that after a state bans affirmative action, multiracial individuals who face an incentive to identify under affirmative action are about 30% less likely to identify with their minority group. In contrast, multiracial individuals who face a disincentive to identify under affirmative action are roughly 20% more likely to identify with their minority group once affirmative action policies are banned.We modify this original abstract as follows: We link data on racial self-identification with changes in state-level affirmative action policies to ask whether racial self-identification responds to economic incentives. We find that after a state bans affirmative action, multiracial individuals who face an incentive to identify under affirmative action are about 2% to 5% more likely to identify with their minority group. In contrast, multiracial individuals who face a disincentive to identify under affirmative action are roughly 20% more likely to identify with their minority group once affirmative action policies are banned.

We link data on racial self-identification with changes in state-level affirmative action policies to ask whether racial self-identification responds to economic incentives. We find that after a state bans affirmative action, multiracial individuals who face an incentive to identify under affirmative action are about 30 percent less likely to identify with their minority groups. In contrast, multiracial individuals who face a disincentive to identify under affirmative action are roughly 20 percent more likely to identify with their minority groups once affirmative action policies are banned.

Using microdata from the 2000 Census, we analyze how the employment rates of foreign-born and US-born men vary with education. After a period of adjustment during the first few years upon arrival, the overall employment rate of immigrant men quickly approaches that of US natives. Among those with the lowest education levels, immigrants exhibit substantially higher rates of employment than comparable natives. This pattern is consistent with a simple theoretical model of migrant selectivity that jointly considers a potential migrant's decisions regarding where to locate and whether to work.

In tracking the later-generation descendants of immigrants, measurement biases can arise from “ethnic attrition” (e.g., US-born individuals who do not self-identify as Mexican despite having ancestors who immigrated from Mexico). We present evidence that such ethnic attrition is sizeable and selective for the third-generation populations of key Hispanic and Asian immigrant groups. In addition, our results suggest that ethnic attrition generates biases that vary across national origin groups in direction as well as magnitude, and that correcting for these biases will raise the socioeconomic standing of the US-born descendants of most Hispanic immigrants relative to their Asian counterparts.

Numerous studies find that U.S.-born Hispanics differ significantly from non-Hispanic whites on important measures of human capital, including health. Nevertheless, almost all studies rely on subjective measures of ethnic self-identification to identify immigrants' U.S.-born descendants. This can lead to bias due to “ethnic attrition,” which occurs whenever a U.S.-born descendant of a Hispanic immigrant fails to self-identify as Hispanic. This paper shows that Mexican American ethnic attritors are generally more likely to display health outcomes closer to those of non-Hispanic whites. This biases conventional estimates of Mexican American health away from suggesting patterns of assimilation and convergence with non-Hispanic whites.