Methodology and Data

This brief borrows its methodology from George Borjas.13 We compare the wage of immigrants with the wage of native‐​born Americans in the 25 to 64 age group of workers who are not enrolled in school. We control for age, age squared, birth in a Hispanic country, sex, and race. We take special note of the immigrant’s year of arrival. We divide up the immigrants into entry cohorts based on the 5‐​year periods when they arrived: 1995 to 1999, 2000 to 2004, 2005 to 209, 2010 to 2014, and 2015 to 2017. Weekly wages are expressed in 2017 dollars, adjusted using the personal consumption expenditures index. Data on the age, weekly wage, Hispanic origin, education, year of arrival, and other factors come from the pooled 1994 to 2017 Annual Social and Economic Supplement of the Current Population Survey (ASEC).14 We change Borjas’s methodology in two ways. First, we include both men and women, where he restricts his sample to men only. Second, we add additional controls for sex, race, education level, industry and occupation, and common state time trends, where he only controlled for age and entry cohort.

Figures 1–4 in the Results section of this brief show gradual wage convergence between immigrants by legal status and native‐​born Americans based on their 5‐​year period of arrival. The numbers in Figures 1–4 are based on the output of regression tables included in the Appendix (Tables 1A–4A). The regressions use state‐​by‐​year fixed effects and industry‐​by‐​occupation fixed effects with standard errors clustered at the state level.

We identify illegal immigrants in the ASEC by using the residual estimation technique employed by George Borjas in another research paper.15 His technique narrows samples in the ASEC by excluding certain foreign‐​born workers on the basis of their own demographic characteristics that are highly correlated with legal immigration status. The remaining workers are likely to be illegal immigrants. The residual technique we use to identify illegal immigrants excludes foreign‐​born people who arrived before 1980, citizens, recipients of government benefits, veterans or those currently in the Armed Forces, government workers, people born in Cuba or Puerto Rico, those working in occupations that require government licenses, and those married to legal immigrants or citizens.

Results

Every figure in this section divides immigrants by the period of years in which they entered the United States, labeled as “Immigrant Year of Entry” on the x‐​axis. The bars show the relative wages of immigrant workers to native workers for each year of entry. For instance, immigrants who entered in the 1995–1999 period had wages that were 13.5 percent below those of natives during their first 0 to 5 years in the United States (Figure 1). The wages of those same immigrants who entered in the same years were only 8.6 percent below those of identical natives after living in the United States for 6 to 10 years. After 21 to 23 years of living in the United States, the wages for immigrants who arrived during 1995–1999 were only 1.5 percent below those of similar native‐​born Americans. Immigrant arrivals divided up by their years of entry generally show a similar pace of wage convergence with native‐​born workers based on how long they have lived here. The exception to that are immigrants who arrived in the 2015–2017 range of years as they started with wages that were only 9.8 percent below those of native‐​born Americans, an improvement over the 13.5-point difference that new immigrant arrivals faced in 1995–1999. The wages of other groups of immigrants divided by their years of entry converged in a similar way. Immigrants arriving in the 2015–2017 period were initially better integrated in the U.S. labor market than immigrants who arrived in earlier years of entry.

Figure 2 shows the wage difference between legal immigrants only and all natives, controlling for age introduced as a fourth‐​order polynomial, sex, race, Hispanic origin, and the aforementioned fixed effects. Compared with all immigrants and illegal immigrants, legal immigrants start with much lower wages relative to native‐​born Americans. The lower relative wage for legal immigrants is due to several factors such as their relatively higher levels of education—meaning they are being compared to Americans who are also highly educated—and their admission to the United States through one of the many family‐​based green card categories that do not select immigrants on the basis of an existing employment offer in the United States. Another potential explanation is that immigrants compete with other immigrants in the labor market more than they compete with native‐​born Americans. The large number of legal immigrants arriving in these periods could be slowing their wage growth and, thus, might explain their initially low wages relative to native‐​born Americans who, by and large, are not competing with immigrant workers.16 However, those factors do not prevent legal immigrants from eventually closing the wage gap as those who arrived in 1995–1999 had wages only 2.4 percent below those of native‐​born Americans after living in the United States for 16 to 20 years. Wages converged for other groups of immigrants in a similar way.

Figure 3 shows the wage difference between illegal immigrants only and all natives, controlling for age introduced as a fourth‐​order polynomial, sex, race, Hispanic origin, and the aforementioned fixed effects. They start off with the lowest wage gap of all the immigrant groups analyzed in this brief. After 11 to 15 years of living in the United States, wages for illegal immigrants who arrived in the 1995–1999 period were equal to those of native‐​born workers. After 21 to 23 years in the United States, their wages were 2.7 percent higher than similar native‐​born Americans. Wage convergence for other groups of illegal immigrants show a similar pattern. New illegal immigrants in the United States who arrived in the 2015–2017 period started out with wages that were only 2.4 percent below those of similar native‐​born Americans.

Illegal Immigration Status and Wage Convergence

Illegal immigrant workers have lower wages than legal immigrant workers. Figure 4 presents estimates of the wage gap between legal immigrants and illegal immigrants, controlling for age introduced as a fourth‐​order polynomial, sex, race, Hispanic origin, and the aforementioned fixed effects. Many, but not all, illegal immigrant workers close the wage gap with legal immigrant workers after 11 to 23 years in the United States.

Over the entire period of 1995–2017, we estimate that illegal immigrant workers have average wages 11.3 percent below those of legal immigrant workers. We estimate this average wage gap using a common econometric technique known as the Oaxaca‐​Blinder decomposition, a method originally developed to analyze the difference between male and female wages.17 The Oaxaca‐​Blinder decomposition technique compares average wages between illegal and legal workers by estimating a separate wage regression for each group. The difference in the conditional mean wages in those two regressions represents the average wage gap between illegal and legal workers over the span of 1995–2017 in absolute terms. The result of the Oaxaca‐​Blinder decomposition method contrasts with the cohort point estimates in Figure 4 and Table 4A, which denote the differences in average wages relative to immigrants’ arrival cohort. That wage penalty of 11.3 percent implies that legalizing illegal immigrants, who comprise about 31.3 percent of foreign‐​born workers, would close much of the wage gap between all immigrants and natives.18 In other words, legalizing illegal immigrants will boost wage assimilation in the United States.

Conclusion

The gap between native and immigrant wages narrows over time, closes in many cases, and sometimes even flips signs. Immigrant‐​native wage convergence in recent decades is similar to the degree of wage convergence that occurred during the Age of Mass Migration in the 19th and early 20th centuries. From 1995–2017, illegal immigrant wages were about 11.3 percent below those of legal immigrants, suggesting that their lack of legal status explains a large percentage of the overall wage gap between all immigrants and all natives. Immigrant wages are converging with those of natives, and legalizing illegal immigrants would likely narrow the gaps even further.

Appendix

Notes

1 National Academies of Sciences, Engineering, and Medicine, The Economic and Fiscal Consequences of Immigration (Washington: The National Academies Press, 2017), pp. 104–14.

2 National Academies, The Economic and Fiscal Consequences of Immigration, p. 105.

3 National Academies, The Economic and Fiscal Consequences of Immigration, p. 105.

4 Barry R. Chiswick, “The Effect of Americanization on the Earnings of Foreign‐​Born Men,” Journal of Political Economy 86, no. 5 (1978): 897–921.

5 George Borjas, “The Slowdown in the Economics Assimilation of Immigrants: Aging and Cohort Effects Revisited Again,” Journal of Human Capital 9, no. 4 (2016): 483–517.

6 National Academies, The Economic and Fiscal Consequences of Immigration, pp. 111–12.

7 Ran Abramitsky and Leah Boustan, “Immigration in American Economic History,” Journal of Economic Literature 55, 4 (2017): 1311–45; Ran Abramitzky, Leah Platt Boustan, and Katherine Eriksson, “A Nation of Immigrants: Assimilation and Economic Outcomes in the Age of Mass Migration,” Journal of Political Economy 122, no. 3 (2014): 467–506.

8 Jeffrey S. Passel and D’Vera Cohn, “Overall Numbers of U.S. Unauthorized Immigrants Holds Steady Since 2009,” Pew Research Center, September 20, 2016, http://​www​.pewhis​pan​ic​.org/​2​0​1​6​/​0​9​/​2​0​/​o​v​e​r​a​l​l​-​n​u​m​b​e​r​-​o​f​-​u​-​s​-​u​n​a​u​t​h​o​r​i​z​e​d​-​i​m​m​i​g​r​a​n​t​s​-​h​o​l​d​s​-​s​t​e​a​d​y​-​s​i​n​c​e​-​2009/; Illegal immigrants comprise 31.3 percent of all immigrant workers when we use the residual statistical technique employed by Borjas’s “The Labor Supply of Undocumented Immigrants” to analyze the Annual Social and Economic Supplement of the Current Population Survey.

9 8 U.S. Code § 1324a.

10 Matthew Freedman, Emily Owens, and Sarah Bohn, “Immigration, Employment Opportunities, and Criminal Behavior,” American Economic Journal: Economic Policy 10, no. 2 (2018): 117–51; Katharine Donato, Jorge Durand, and Douglas Massey, “Stemming the Tide? Assessing the Deterrent Effects of the Immigration Reform and Control Act,” Demography 29, no. 2 (1992): 139–57; Katharine Donato and Douglas Massey, “Effect of the Immigration Reform and Control Act on the Wages of Mexican Migrants,” Social Science Quarterly 74, no. 3 (1993): 523–41; Elaine Sorensen and Frank Bean, “The Immigration Reform and Control Act and the Wages of Mexican Origin Workers: Evidence from Current Population Surveys,” Social Science Quarterly 75, no. 1 (1994): 1–17; Cynthia Bansak and Steven Raphael, “Immigration Reform and the Earnings of Latino Workers: Do Employer Sanctions Cause Discrimination?,” Industrial and Labor Relations Review 54, no. 2 (2001): 275–95; Sherrie Kossoudju and Deborah Cobb‐​Clark, “Coming Out of the Shadows: Learning about Legal Status and Wages from the Legalized Population,” Journal of Labor Economics 20, no. 3 (2002): 598–628; Douglas S. Massey, Jorge Durand, and Nolan J. Malone, Beyond Smoke and Mirrors: Mexican Immigration in an Era of Economic Integration (New York: Russell Sage Foundation, 2002), pp. 119–21.

11 Catalina Amuedo‐​Dorantes, Cynthia Bansak, and Steven Raphael, “Gender Differences in the Labor Market: Impact of IRCA,” American Economic Review 97, no. 2 (2007): 412–16; Francisco Rivera‐​Batiz, “Undocumented Workers in the Labor Market: An Analysis of Earnings of Legal and Illegal Mexican Immigrants in the United States,” Journal of Population Economics 12, no. 1 (1999): 91–116; Sherrie A. Kossoudji and Deborah A. Cobb‐​Clark, “IRCA’s Impact on the Occupational Concentration and Mobility of Newly‐​Legalized Mexican Men,” Journal of Population Economics 13, no. 1 (2000): 81–98; Sherrie A. Kossoudji and Deborah A. Cobb‐​Clark, “Coming Out of the Shadows: Learning about Legal Status and Wages from the Legalized Population,” Journal of Labor Economics 20, no. 3 (2002): 598–628; Ying Pan, “The Impact of Legal Status on Immigrants’ Earnings and Human Capital: Evidence from the IRCA 1986,” Journal of Labor Research 33 (2012); Silvia Helena Barcellos, “Legalization and the Economic Status of Immigrants,” RAND Corporation Working Paper no. 754, 2010, https://​www​.rand​.org/​p​u​b​s​/​w​o​r​k​i​n​g​_​p​a​p​e​r​s​/​W​R​7​5​4​.html; Scott R. Baker, “Effects of the 1986 Immigration Reform and Control Act on Crime,” SSRN Working Paper, 2011, doi:10.2139/ssrn.1829368.

12 Magnus Lofstrom, Laura Hill, and Joseph Hayes, “Did Employer Sanctions Lose Their Bite? Labor Market Effects of Immigrant Legalization,” IZA Discussion Paper no. 4972, 2010, Institute of Labor Economics, Bonn.

13 George J. Borjas, “The Slowdown in the Economic Assimilation of Immigrants: Aging and Cohort Effects Revisited Again,” Journal of Human Capital 9, no. 4 (Winter 2015): 483–517.

14 Sarah Flood et al., Integrated Public Use Microdata Series, Current Population Survey: Version 5.0 [dataset], Minneapolis: University of Minnesota, 2017, https://​doi​.org/​1​0​.​1​8​1​2​8​/​D​0​3​0​.V5.0.

15 George J. Borjas, “The Labor Supply of Undocumented Immigrants,” NBER Working Paper no. 22102, March 2016, p. 10, http://​www​.nber​.org/​p​a​p​e​r​s​/​w​22102.

16 George J. Borjas, Immigration Economics, (Cambridge, MA: Harvard University Press, 2014), p. 120; Gianmarco I. P. Ottaviano and Giovanni Peri, “Rethinking the Effect of Immigration on Wages,” Journal of the European Economic Association 10, no. 1 (2012): 152–97.

17 Ronald Oaxaca, “Male‐​Female Wage Differentials in Urban Labor Markets,” International Economic Review 14, no. 3 (1973): 693–709; Alan S. Blinder, “Wage Discrimination: Reduced Form and Structural Estimates,” Journal of Human Resources 8, no. 4 (1973): 436–55.

18 Illegal immigrants comprise 31.3 percent of all immigrant workers when we use the residual statistical technique employed by Borjas’s “The Labor Supply of Undocumented Immigrants” to analyze the ASEC.