Economic Assimilation of Mexicans and Central Americans in the United States¹

The integration of immigrants in their host country is a multidimensional and complex process. The economic aspect of this process is often assessed by focusing on how immigrants’ incomes and employment statuses compare to those of similar natives. These metrics are important. On the one hand, they affect the material and psychological well-being of immigrants, and they can affect assimilation in other aspects of life, such as political attitudes and civic engagement. Moreover, the gains from migration are larger if immigrants achieve earnings comparable to those of natives (Clemens et al., 2016). On the other hand, the economic success of immigrants contributes to more-open and positive attitudes of natives toward immigration (Alesina et al., 2018).

The United States has historically been a place where immigrants, attracted by economic opportunities, have been able to succeed economically even when starting at a disadvantage (Chiswick, 1978). While differences among national groups exist and are large, both in terms of the initial earnings gaps and convergence rates, the overall narrative is that immigrants who arrived in the United States before the 1980s generally achieved convergence to the economic status of natives. Similarly, the evidence on earlier immigrants is that they assimilated economically and, when compared to similar natives, those who stayed in the United States did not have a significant initial earnings gap (Abramitsky et al., 2014).

Some studies, however, since the work of Borjas (1985), have pointed out that the recent history of immigrant assimilation has changed. These studies find a worsening in the initial earnings gap for immigrants who arrived in the 1980s and 1990s, which appears to have put this assimilation at risk. More recently, Borjas (2015) argues that not just the initial gap, but the rate of economic assimilation too, measured by the average earnings convergence of immigrants, has been declining for the cohorts that arrived in the 1980s and 1990s. These papers paint a picture of a progressive increase in the initial gap and a decline in the “catching up” of recent immigrants relative to natives. This finding is a worrying sign because it implies that immigrants arrive with a larger initial disadvantage and do not make up for it.

As groups of immigrants from different origins are present in very different proportions, depending on the cohort of arrival, a changing earnings gap and the trajectory of the average immigrant over time can be caused by a composition effect. Borjas (2015) has shown that this is partly the case. As migrants of different nationalities have different education levels, age, and initial skills, the changing composition of subsequent cohorts may give the impression of a changing earnings gap and average convergence. A situation in which the initial gap and convergence are stable over time for each national group but where the immigrant composition has changed over time in terms of place of origin is very different from a scenario in which all immigrants are increasingly lagging behind at arrival and in their assimilation toward the economic status of natives. The first scenario implies stable levels of assimilation for each group even if the composition of immigrants is changing. The second scenario would imply a decrease in assimilation and could mean that recent immigrants have faced more difficulties, discrimination, or barriers to participation in the labor market, which would call for an effort to identify the causes of such deterioration.

In this paper, we focus on Mexicans and Central Americans and update the existing literature on assimilation to include very recent cohorts not yet analyzed in the literature. There are three main reasons why it is important to focus on this group of immigrants and to closely examine their economic integration.

First, while not identical, Mexican and Central American immigrants are similar to each other in terms of their demographics, especially with respect to educational attainment, labor market specialization, and income. An authoritative report on the integration of immigrants by the National Academy of Sciences, Engineering, and Medicine (NASEM; see NASEM, 2015, Chapter 6) noticed strong similarities in terms of schooling and share of undocumented immigrants between Mexicans and Central Americans.

In our data, considering workers between 25 years and 64 years of age, the percentage of high school dropouts is very similar between Mexicans (49%) and Central Americans (47%), the percentage of self-employed is similar (13% and 14%, respectively), and also the percentage of females is similar (36% and 39%, respectively). These two groups stand out among all immigrants as being less educated, working in low-paid jobs, and comprising mainly males.

Second, they represent the most economically disadvantaged group of immigrants in the United States. Different from many other groups of immigrants, their average schooling is significantly lower than that of natives. Previous studies have identified Mexicans and Central Americans as encompassing the most problematic cases in terms of integration and economic performance (see NASEM, 2015, Chapter 6). Hence, improvement in their ability to integrate would also imply a reduction in inequality and poverty in the United States.

Third, Mexico and Central America comprise a relevant geographic region of origin because immigrants from this region constitute an extremely large share of total immigrants. In fact, this region of the world has the largest representation among US immigrants, larger than Southeast Asia, Europe, or Africa.

In our data, about 36% of adult working immigrants as of 2017 were Mexicans and Central Americans and, together, they represented about 5.4% of the US population between 25 and 64 years of age, which is the group that we analyze in this paper.

In this study, we follow the labor market assimilation of different arrival cohorts over time, starting with the cohort that arrived in 1965–1969 and ending with the one that arrived in 2005–2011. First, we contribute to the literature by documenting whether these immigrants, who are usually characterized as having low educational attainment and being employed in manual-intensive, low-paying jobs, have performed poorly in the labor market by examining how their labor market performance compares to the performance of natives of the same age and then of natives of the same age and education. This analysis allows us to examine whether the economic integration of this group of immigrants has slowed/worsened over time.

Our second contribution includes an analysis of immigrant integration in terms of their employment probability. Mexicans and Central Americans have been employed in many low-skilled jobs, and previous studies indicate that immigrants from this region work at high rates, usually higher than natives (e.g., Blau and Kahn, 2007; NASEM, 2015; Orrenius and Zavodny, 2018). Rarely, however, has the employment probability been the focus of analysis in studies that examine the convergence of different cohorts of immigrants over time. We show that recent Mexican and Central American immigrants have outperformed their native counterparts in terms of the employment rate within 10 years of arrival.

The third contribution is a descriptive, but informative, analysis that investigates how sector, location, and skill level are associated with the initial economic gaps and subsequent convergence.

There are also limitations to our analysis. First, we condition our data samples on male workers. We focus on men in order to maintain consistency with the existing literature (e.g., Borjas, 1985, 2015; Villareal and Tamborini, 2018), which is justified by the need to focus on individuals whose working history is more continuous and representative of the main breadwinners in the immigrant family (Blau and Kahn, 2007). Mexican and Central American women have a much lower employment rate than men, and their role and presence in the working population have changed over time. By focusing on men, we obviate the need to examine issues related to gender as they pertain to the assimilation of women in the labor market. Second, this paper focuses only on the economic integration of the first generation of immigrants, albeit over time. Several studies (such as those by Duncan and Trejo, 2011a, b, 2015), which have focused on Mexicans and Mexican Americans, compare the economic outcomes of the first, second, and third generations. While those studies are important and complement this one, the evidence of a lower starting point in terms of earnings for the first generation suggests that a more detailed examination of the economic assimilation of this group is particularly relevant. Finally, we do not conduct any causal analyses. We do, however, investigate whether the sector of employment, the location, and the local economic environment are related to the initial gaps and assimilation rates of these immigrants. We also discuss the potential role of changing composition, language proficiency, legal status, and the role of recessions in the assimilation of new cohorts of Mexicans and Central Americans. While certainly not conclusive, this more-detailed analysis is informative and useful.

Our analysis reveals four main findings. First, Mexicans and Central Americans have had an earnings gap relative to similar natives of around 40% upon arrival, and only cut it in half in the first 2–3 decades, without much progress after that.

Second, we find that both the initial gap and the speed of convergence have not worsened for recent cohorts of arrival. In fact, the most recent cohorts that arrived in 1995–99 and 2005–11 have fared quite well relative to similar natives, both in terms of the initial gaps and in convergence. However, given that natives with low levels of education and experience have done relatively poorly in US labor markets, and because Mexicans and Central Americans tend to be poorly educated, new immigrants’ earnings have not performed very strongly overall, only in comparison with similar natives.

Third, when looking at the employment probability, the picture is more positive. Mexicans and Central Americans have had almost no employment gap at arrival. Furthermore, over time, they have managed to outperform natives in terms of employment both relative to the average US native and, even more so, relative to US natives with similar schooling. Moreover, the rate at which recent cohorts have assimilated in terms of the employment rate has been much higher than previous cohorts. This superior performance of low-skilled immigrants with respect to employment distinguishes the United States from Europe and most other countries, where the reverse is true (see Battisti et al., 2018).

Finally, when decomposing Mexicans and Central Americans by their sector of employment, we find that the initial gaps are smaller and the assimilation faster for those in the construction sector, while their performance is the worst in the agricultural sector. We also find a somewhat smaller gap and faster assimilation in urban (as opposed to rural) areas. By examining the evolution of observable characteristics of the recent-arrival cohorts, especially the 1995–99 and 2005–11 cohorts, they appear to be comparable to earlier cohorts in terms of the share of Central Americans and their English language ability. Although they have a slightly higher education level and larger share of nonwhites, these differences do not appear particularly large and seem unlikely to be the primary drivers of the improved performance of these more-recent cohorts. Furthermore, these recent cohorts are composed of a larger share of undocumented immigrants and noncitizens.

Our calculations on Integrated Public Use Microdata Series (IPUMS) data show that while the cohort of Mexicans and Central Americans that arrived in 1965–70 included 77% of noncitizens, the one that arrived in 2005–2011 included 97% noncitizens.

Our results, which focus on Mexicans and Central Americans, present a more-positive outlook than what is shown by Borjas (2015). The aggregate impression of worse initial gaps and slower convergence of the more-recent cohorts shown in that paper could be partly an artifact of the changing composition of immigrants. Furthermore, that analysis does not account for the more-recent cohorts that arrived in the 1990s and the 2000s, which seem to have performed particularly well despite the Great Recession. The overall message of our analysis is more hopeful, yet qualified. The Mexicans and Central Americas who have arrived in the past 15 years have started out in a better position, and they show stronger convergence rates relative to previous cohorts. The caveat is that, as most of them only have a high school education or less, earnings convergence toward that of similar natives is not necessarily good news because low-educated workers have been lagging behind in terms of earnings over the past few decades. Nevertheless, this immigrant group has done well in terms of employment probability, outperforming natives within a decade of arrival.

The remainder of the paper develops as follows. In Section 2, we relate this paper and its contributions to the existing literature on the assimilation of immigrants. In Section 3, we introduce the data and some aggregate statistics. In Section 4, we present the empirical models and discuss the interpretation of the key coefficient estimates. Section 5 describes the main results on earnings and employment rate assimilation; Section 6 describes the differences in assimilation by sector of employment and location and discusses the role of composition, language proficiency, and legal status; and Section 7 provides some concluding remarks.

The literature on the assimilation of immigrants in the United States is large and interdisciplinary. As summarized in the authoritative report by NASEM (2015), researchers have studied many of its aspects, ranging from assimilation in terms of politics and civics (see NASEM, 2015, Chapter 4), location (see NASEM, 2015, Chapter 5), educational achievement (see NASEM, 2015, Chapter 6), family structure (see NASEM, 2015, Chapter 8), and health (see NASEM, 2015, Chapter 9), to more-specific economic outcomes, such as earnings, employment, and occupation. Much of the existing literature has examined the first, second, and third generations of immigrants (e.g., Trejo, 2003; Duncan and Trejo, 2015; Abramitsky et al., 2021), covering assimilation over the very long run. Our study focuses on the specific economic aspect of assimilation measured by earnings and employment probability and considers only the first generation of immigrants, following them over time since arrival.

More directly related to this type of analysis, and hence to our contribution, is the seminal work of George Borjas (1985), who showed that in order to analyze the earnings convergence of immigrants, one has to follow a cohort of arrival over time and differentiate across arrival cohorts. The economic literature has followed such an approach. This approach is a significant improvement over the cross-sectional analysis of immigrants (first explored by Chiswick, 1978), which compares different groups who have been in the country for different periods of time and confounds changes in the initial gaps and changes in assimilation rates across cohorts.

Even the cohort analysis, however, must be considered with caution. The composition of subsequent cohorts of immigrants in the United States has been quite different in terms of origin and education, their initial earnings gaps have changed, and the average earnings convergence may have varied over time due to compositional changes. Typically, this literature looks at the aggregate set of immigrants and compares it to the average set of natives. If the composition of immigrants and the performance of different groups of natives change over time, wage dynamics relative to all workers of a certain skill group can be confounded by changes in assimilation rates. Additionally, as the cohort approach does not use longitudinal data, changes in the cohort composition over time due to differential attrition from return migration can generate stronger “cohort” convergence relative to the individual convergence of immigrants (see Lubotsky, 2007; Abramitsky et al., 2014).

Only a few studies have used longitudinal data to follow recent individual immigrants in terms of their assimilation. Using data from the Survey of Income and Program Participation (SIPP), which is linked to tax records, Villareal and Tamborini (2018) have shown that recent arrival cohorts have not performed worse than earlier ones and that the race of immigrants affects their assimilation, with black and Hispanic immigrants at a disadvantage. In their study, the authors follow individuals over time, capturing more closely the individual wage dynamics. However, the small size of the sample, the fact that they consider all the immigrant groups together, and the fact that they do not compare immigrants to natives with similar age and education make their study less informative about the economic assimilation of economically disadvantaged groups of immigrants, such as those that are considered in our analysis.

Similar studies on the assimilation of immigrants have recently boomed in Europe. This literature usually emphasizes the employment gap of immigrants, especially refugees, and their slow convergence. Evidence from the United Kingdom (Clark and Lindley, 2006), Norway (Bratsberg et al., 2017), and a set of 13 European Union countries (Ho and Turk-Ariss, 2018) finds a significant initial employment gap of immigrants relative to natives, especially when considering refugees and immigrants from low-income sources. While some convergence is observed, it is far from complete even after 20 years. Several recent papers have examined the policies that have been successful in promoting the economic convergence of immigrants.

Using causal inference through regression discontinuity and quasiexperimental evidence on assignment to policies, some recent papers have established that language training (Lochmann et al., 2019), active labor market policies (Sarvimäki and Hämäläinen, 2016), and improvements in the processing time of asylum requests (Hainmueller et al., 2016) have improved the labor market assimilation and performance of immigrants.

In this paper, we use an approach similar to that of Borjas (2015), but our new contribution is the focus on the more-homogeneous group of Mexicans and Central Americans.

While we provide some rationale in the Introduction section as to why it makes sense to group Mexicans and Central American together, we have also conducted the analysis on Mexicans only, who make up the largest group. When focusing on Mexicans only, the main findings with respect to the initial gaps and convergence are similar to what is shown in this paper.

The data we use were obtained from the Integrated Public Use Microdata Series (IPUMS) (Ruggles et al., 2019) and contain samples similar to those used by Borjas (2015). However, we update our analysis up to the year 2017 and document – for the first time – assimilation in the more recent 7 years for which IPUMS data are available. These data include the decennial US Census samples spanning the period between 1970 and 2000, as well as the pooled 2009–2011 (which we refer to as 2010) and 2017 American Community Survey (ACS) samples.

Our samples differ slightly from those used by Borjas (2015) because of errata in the 2009–2011 ACS sample, which had not been corrected at the time of Borjas's (2015) analysis. In particular, on July 1, 2015 (which is after the date that Borjas (2015) had conducted his analysis), the IPUMS adjusted the CPI on the source variables (incwage and incbus00) that are used to construct the main outcome variable (incearn) used in the analysis. In addition, on May 25, 2017, the IPUMS made another adjustment to the source variable incwage. Nevertheless, replication exercises using these corrected data reveal coefficients that are either identical or very close (all are within 0.01) to those reported by Borjas (2015); so, we are confident that the updated samples we use reflect estimates that are comparable to those in his analysis.

The sample of individuals used in the earnings analysis only includes males between the ages of 25 years and 64 years who have between 1 years and 40 years of potential work experience, have worked at least 1 week during the previous year, are not living in group quarters or attending school at the time of the survey, and have arrived in the United States at the age of 18 years or older. For the employment rate analysis, the same criteria are used, but individuals who did not work and those who did not generate earnings are also included in the sample as we are constructing the employment rate (employment probability) for this group. We classify individuals as employed if they had worked at least 1 week during the previous year. For the earnings analysis, all dollar amounts have been adjusted to real 1999 dollars using the consumer price index (CPI) for “Current, not seasonally-adjusted, US city average for all items for all urban consumers”.

This CPI can be found using the “Multi Screen Data Search” tool at https://www.bls.gov/cpi/data.htm. Since the census samples report earnings from the previous year, we also use the CPI from the previous year to adjust the earnings reported in the census samples. However, the ACS surveys reflect information about the previous 12 months (not the previous calendar year). Following Borjas (2015), we also use the previous year's CPI to adjust the reported earnings from the ACS samples.

Table A1 and Figure 1 update the stylized facts shown in Borjas (2015) relative to all immigrants, adding the cohort that arrived in 2005–2011 and expanding the sample to 2017. Table A1 shows the estimates of the log earnings gap relative to US natives of the same age for each cohort entering in each of the following years: 1970, 1980, 1990, 2000, and 2010; moreover, we add the year 2017 from the ACS data, which allows one more cohort and a longer period of analysis for previous cohorts. Figure 1 shows those gaps in a chart, tracking each arrival cohort over 30 years of stay in the United States. The figure shows the initial gaps and the 30-year convergences for each arrival cohort using dotted lines for the early cohorts, dashed for the intermediate, and a solid line for the most recent, with increasing thickness going from early to recent. We first standardize the initial gaps to zero in Figure 1(A) and then show the actual estimated initial gaps in log points in Figure 1(B). These initial figures (Figure 1A and B) and Table A1 provide a benchmark for the average immigrant in terms of the earnings gaps upon arrival to the United States and the average convergence over time. Panel B of Figure 1 also reveals a progressively larger initial gap and a slower convergence rate for the more-recent cohorts. In particular, the cohorts that arrived in 1985–89 and 1995–99, which are the two most recent cohorts considered by Borjas (2015), show large initial gaps and slow convergence rates relative to the previous two cohorts. These figures, however, compare cohorts of immigrants that varied drastically in terms of country of origin and education levels over time. Specifically, these results compare the average immigrant to the average US native and do not account for education or country of origin; so they only provide a limited understanding of economic assimilation as it relates to the more-vulnerable immigrants.

Figure 1

In order to estimate the rate of earnings and the employment convergence of Mexican and Central American immigrants, we start by estimating the following model separately for each cross section τ, while restricting the sample to include only native-born workers and immigrants from Mexico and Central America: (1) Yℓτ=β0+βCℓ+ΓXℓτ+εℓτ {Y_{\ell \tau }} = {\beta _0} + {\boldsymbol \beta} {{\boldsymbol C}_\ell } + {\bf \Gamma} {{\boldsymbol X}_{\ell \tau }} + {\varepsilon _{\ell \tau }}

In Eq. (1), Y_ℓτ ∈ (lnw_ℓτ, Emp_ℓτ) represents the measure of labor market performance of interest. The variable lnw_ℓτ is the natural log of the weekly earnings of an individual measured in year (cross section) τ, Emp_ℓτ is a dummy variable that identifies whether an individual was employed during the previous year, X_ℓτ is a third-order polynomial for the individual's age, C_ℓ is a vector of fixed effects representing each immigrant cohort in the sample being considered and one fixed effect – omitted in the regression – representing native workers, and ɛ_ℓτ is the error term.

We define “employed” as working for at least 1 week during the previous year.

Next, we pool the data from all cross sections and allow for the comparison of different cohorts of immigrants with natives of similar age and education. We estimate the following model while including natives and immigrants from Mexico and Central America: (2) Yℓτ=β0+ΩXℓτ+αyℓτ+ΣCℓ+θyℓτCℓ+Sℓτ+νℓτ {Y_{\ell \tau }} = {\beta _0} + {\boldsymbol \Omega} {\boldsymbol{X}_{\ell \tau }} + {\boldsymbol \alpha} {\boldsymbol{y}_{\ell \tau }} + \Sigma {\boldsymbol{C}_\ell } + {\boldsymbol \theta} {y_{\ell \tau }}{\boldsymbol{C}_\ell } + {\boldsymbol{S}_{\ell \tau }} + {\nu _{\ell \tau }}

In Eq. (2), X_ℓτ is a third-order polynomial for the age of each individual, y_ℓτ is a third-order polynomial that identifies the number of years that the immigrants have been in the United States, capturing the potentially nonlinear effect of US work experience, C_ℓ is a vector of dummy variables identifying each immigrant cohort, and y_ℓτC_ℓ identifies a linear cohort-specific US work-experience trend. The term S_ℓτ is a vector of education–age–survey year fixed effects.

We include four education groups (high school dropouts, high school graduate, some college, and college diploma) and eight age groups broken into 5-year intervals between the ages of 25 years and 64 years.

All the tables that show results from Eq. (2) report the cohort-of-arrival-specific initial gap and the 10-year estimated relative growth. These statistics are estimated first without the age–education–year effects (S_ℓτ), so as to capture the earnings gaps and growth of Mexicans and Central Americans relative to the average native of the same age, and then estimated with the age–education–year fixed effects (S_ℓτ), so as to capture the gaps and convergences relative to similarly aged and educated natives. The difference between these two specifications captures the part of the gaps and convergences explained by the composition of immigrants across education groups and the different performance levels of those education groups over time, common to native and immigrants. All the standard errors in Eqs. (1) and (2) are clustered at the cohort level.

The assimilation of low-skilled immigrants is a very important issue often dominating the debate about immigration. Several receiving countries claim that immigrants are, and remain, a burden to the receiving country because they do not have skills that can be integrated in the labor market, and hence, their employment rate is low and their earnings lag behind those of similar natives. In the United States, there are anecdotes and research works showing that immigrants who arrived in the 1980s and 1990s have had a harder time assimilating in the labor market.

In this paper, we analyze whether such a characterization is true when extending the analysis to cohorts of arrival in the 1990s and 2000s and when focusing on Mexican and Central American immigrants, traditionally a group of low-educated immigrants earning low wages. This group of immigrants is large, comprising almost 6% of the US labor force; hence, their success is very important to the US economy and society as a whole. While we do find a significant initial earnings gap and only incomplete convergence after 30 years of stay, we also find that recent cohorts arriving after 1995 have not performed worse than earlier ones that arrived in the 1970s and 1980s. Moreover, we find that, in terms of their employment probability, Mexicans and Central Americans outperform natives of similar age within 20–30 years in the country. In particular, focusing on the arrival cohorts of 1995–99 and 2005–11, we find that they seem to perform particularly well relative to similar US citizens.

Our findings differ from studies that consider all immigrants together and find a worsening in the quality of recent cohorts. Once we focus on a homogeneous, if disadvantaged, group of immigrants, such as the Mexicans and Central Americans, we find recent cohorts performing well relative to earlier ones.

We also show that those employed in the construction sector and those living in urban areas seem to start with higher earnings and have stronger earnings progression than the others. Immigrants employed in agriculture, instead, are associated with a larger initial gap, slower convergence, and low levels of education.

When considering ideas that could inspire policy, given the high demand for labor in the construction sector and the good opportunities that it affords immigrants, one could think of visas linked to these types of jobs. Our findings also suggest that there is no basis in the data to claim that new immigrants are of lower labor-market quality relative to earlier ones. Considering specific countries of origin, subsequent cohorts of immigrants have actually performed similarly or better in the United States. As recent cohorts are composed of a larger share of nonwhite and undocumented immigrants, the fact that their relative performance has not worsened may be an encouraging sign in terms of employment opportunities provided by the US labor market up to 2017, the final year of our analysis. However, the poor earnings performance of low-skilled workers, in general, has had a disproportionate impact on Mexican and Central Americans, who are heavily represented in those groups.