7
HISPANICS IN THE U.S. LABOR MARKET

Brian Duncan, V. Joseph Hotz, and Stephen J. Trejo

As the first two chapters of this volume have noted, Hispanics constitute a large and rapidly growing segment of the U.S. population. Much of the public debate and controversy concerning Hispanics focuses on their integration and success in the U.S. labor market. In this chapter, we summarize some of what is currently known about these issues. We focus on employment and earnings as measures of labor market success. We also examine the educational attainment of Hispanics, given its crucial role in labor market success. We consider four different but complementary perspectives.

We begin by examining Hispanics and their subgroups that currently reside in the United States, on the basis of data from the 2000 Census of Population. We focus on how foreign-born versus U.S.-born Hispanics differ in an important indicator of human capital, namely their educational attainment. We then document the differences that exist among Hispanics, their subgroups, whites, and blacks in employment and earnings. Finally, we ask how much of these differences can be accounted for by differences in years of schooling, English language proficiency, and potential work experience. Two conclusions emerge from this analysis. First, we confirm the findings in Chapter 6 as well as numerous other studies that Hispanics have markedly lower levels of educational attainment than do whites or blacks and that these educational deficits are more pronounced for the foreign-born. Second, while the employment and earnings of Hispanics tend to lag behind those of whites, almost all of the differences relative to whites can be accounted for by a relatively small number of measures of human capital, namely, years of schooling, English proficiency, and potential work experience.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 228
Hispanics and the Future of America 7 HISPANICS IN THE U.S. LABOR MARKET Brian Duncan, V. Joseph Hotz, and Stephen J. Trejo As the first two chapters of this volume have noted, Hispanics constitute a large and rapidly growing segment of the U.S. population. Much of the public debate and controversy concerning Hispanics focuses on their integration and success in the U.S. labor market. In this chapter, we summarize some of what is currently known about these issues. We focus on employment and earnings as measures of labor market success. We also examine the educational attainment of Hispanics, given its crucial role in labor market success. We consider four different but complementary perspectives. We begin by examining Hispanics and their subgroups that currently reside in the United States, on the basis of data from the 2000 Census of Population. We focus on how foreign-born versus U.S.-born Hispanics differ in an important indicator of human capital, namely their educational attainment. We then document the differences that exist among Hispanics, their subgroups, whites, and blacks in employment and earnings. Finally, we ask how much of these differences can be accounted for by differences in years of schooling, English language proficiency, and potential work experience. Two conclusions emerge from this analysis. First, we confirm the findings in Chapter 6 as well as numerous other studies that Hispanics have markedly lower levels of educational attainment than do whites or blacks and that these educational deficits are more pronounced for the foreign-born. Second, while the employment and earnings of Hispanics tend to lag behind those of whites, almost all of the differences relative to whites can be accounted for by a relatively small number of measures of human capital, namely, years of schooling, English proficiency, and potential work experience.

OCR for page 228
Hispanics and the Future of America We next examine the early life-cycle patterns of schooling and work for Hispanics relative to blacks and whites, using data on cohorts who reached adulthood during the late 1980s and 1990s. In this analysis, we focus on two issues arising from the role that the Hispanic educational deficit plays in accounting for their relative employment and earnings differentials. First, we examine exactly what sorts and amounts of work experience Hispanics accumulated during early adulthood. We know that they accumulated less education over their early adulthood. But do they compensate by accumulating more work experience to offset some of their educational deficit? Second, we examine whether Hispanics realized the same financial returns from their accumulated work experience and schooling. Previous studies of other minority groups suggest that they do not realize the same gain from an additional year of schooling or work experience as do whites. Whether these differences reflect evidence of labor market discrimination or unmeasured differences in the quality of schooling and the amount of actual work experience is less certain. But at issue is whether observed measures of human capital have different impacts on the degree of labor market success by race or ethnicity. In the final section of the chapter, we focus on how the labor market attainment of Hispanics in the United States has changed over time and across generations. Analyzing whether there has been secular and generational progress among Hispanics in the United States is important for at least three reasons. First, our analysis was performed on Hispanics during a period of substantial change in the structure of the U.S. labor market, which tended to be decidedly less favorable for less-skilled workers in the United States. As a result, it is important to assess, if only somewhat speculatively, how important this restructuring was for the lower levels of labor market attainment experienced by Hispanics. Second, knowing how things have changed is an essential ingredient for forecasting what will happen to the labor market attainment of this growing and increasingly important segment of the U.S. population. Third, assessing how things have changed across generations is essential because of the immigrant nature of Hispanics. The immigrants of today will be the parents and grandparents of future generations of Hispanics, and it is of critical importance to understand the degree of their intergenerational assimilation into the U.S. labor market. THE CURRENT SCENE: THE LABOR MARKET ATTAINMENT OF HISPANICS Human Capital Time and time again, researchers have found that indicators of labor market disadvantage for U.S. Hispanics, such as earnings deficits or em-

OCR for page 228
Hispanics and the Future of America TABLE 7-1 Average Years of Schooling, by Gender, Ethnicity, and Nativity Ethnicity Men, by Nativity Women, by Nativity All Foreign-Born U.S.-Born All Foreign-Born U.S.-Born Whites     13.6     13.6 Blacks     12.4     12.8 All Hispanics 10.5 9.5 12.2 10.8 9.8 12.4 Mexicans 9.8 8.5 12.1 10.1 8.6 12.2 Puerto Ricans 11.7 11.2 12.4 12.0 11.4 12.7 Cubans 12.7 12.4 13.6 12.9 12.5 14.2 NOTE: The samples include individuals ages 25 to 59. See Appendix Table A7-1 for standard errors and sample sizes, as well as for analogous calculations for other Hispanic subgroups. SOURCE: 2000 Census, 5% Public Use Microdata Samples (PUMS). ployment gaps with respect to white workers, are in large part explained by relatively low levels of human capital.1 Accordingly, we begin by describing, in broad terms, the labor market skills possessed by Hispanic Americans and how these skills compare with those of non-Hispanics. One of the most important and easiest to observe dimensions of human capital is educational attainment, and Chapter 6 has documented the obstacles faced by Hispanic children in U.S. schools. Table 7-1 shows the substantial gaps in completed education that exist for Hispanic adults. Based on microdata from the 2000 census, the table reports average years of schooling—by gender, ethnicity, and nativity—for individuals between the ages of 25 and 59.2 In addition to presenting statistics for Hispanics as an aggregate group, we display separate results for Mexicans, Puerto Ricans, and Cubans, the three Hispanic national-origin groups with the largest U.S.-born populations.3 We also present comparable statistics for non- 1   See, for example, Altonji and Blank (1999); Antecol and Bedard (2002, 2004); Bean and Stevens (2003); Bean and Tienda (1987); Bean, Trejo, Capps, and Tyler (2001); Carlson and Swartz (1988); Carnoy, Daley, and Hinojosa-Ojeda (1993); Cotton (1985); Darity, Guilkey, and Winfrey (1995); DeFreitas (1991); Grogger and Trejo (2002); Gwartney and Long (1978); McManus, Gould, and Welch (1983); Reimers (1983); Smith (1991, 2001); Trejo (1996, 1997, 2003). 2   We focus on individuals in this age range because they are old enough that virtually all of them have completed their schooling, yet they are young enough that observed labor market outcomes reflect their prime working years. 3   Appendix Table A7-1 reports standard errors and sample sizes for the estimates in Table 7-1, as well as analogous calculations for other Hispanic subgroups. Throughout this chapter, appendix tables provide further details of the tables and charts presented in the text. All statistics reported in this chapter make use of the relevant sampling weights.

OCR for page 228
Hispanics and the Future of America Hispanic whites and non-Hispanic blacks, with both of these latter groups restricted to individuals who were born in the United States.4 U.S.-born whites provide a yardstick for measuring Hispanic outcomes against those of the primary native majority group in American society, whereas U.S.-born blacks are an important native minority group that is instructive to compare with Hispanics. Table 7-1 shows that educational patterns are very similar for men and women. For Hispanics overall, immigrants average less than 10 years of schooling, but mean educational attainment rises sharply to over 12 years for U.S.-born Hispanics. Despite this sizeable improvement associated with nativity, U.S.-born Hispanics trail the average educational attainment of whites by more than a year, and they even trail the educational attainment of blacks. Consequently, Hispanic educational attainment is low not only in comparison with advantaged groups in American society such as whites, but also in comparison with disadvantaged minority groups such as blacks. Among the Hispanic subgroups, Mexicans and Puerto Ricans display the same general patterns as Hispanics overall, with substantial schooling growth between immigrants and the U.S.-born, yet a large educational deficit relative to whites that persists even for the U.S.-born. Average education levels among the foreign-born, however, are much lower for Mexicans than for Puerto Ricans (8.5 years versus more than 11 years, respectively), but Mexicans experience bigger gains for the U.S.-born, thereby shrinking to a half year or less the educational gap between U.S.-born Mexicans and Puerto Ricans. Cubans stand out from the other groups with notably high levels of educational attainment. In terms of average schooling, Cuban immigrants exceed U.S.-born Mexicans and approach the level of U.S.-born Puerto Ricans, and U.S.-born Cubans equal (for men) or surpass (for women) the educational attainment of whites. More detailed tabulations reveal that the schooling deficits (relative to whites) of U.S.-born Hispanics, in general, and of Mexican Americans and Puerto Rican Americans, in particular, emanate from differences at the extremes of the education distribution. U.S.-born Mexicans and Puerto Ricans are much more likely to be without a high school diploma and much less likely to earn a bachelor’s degree than are non-Hispanic whites (Bean et al., 2001). For Hispanic immigrants, a critical aspect of their human capital is that much of it was acquired outside the United States. The foreign schooling 4   We identify Hispanics and Hispanic subgroups using the census information regarding country of birth, Hispanic origin, and ancestry. Among non-Hispanics, we identify whites and blacks using the census information on race. For Hispanics and blacks, we employ the full 5 percent samples of the population available in census microdata, but to lighten the computational burden we randomly sample whites (at a 1 in 10 rate) so as to end up with a 0.5 percent sample of the white population.

OCR for page 228
Hispanics and the Future of America and work experience that Hispanic immigrants bring with them transfer imperfectly to the U.S. labor market, in that U.S. employers typically place a lower value on human capital acquired abroad than on that acquired here (Chiswick, 1978; Schoeni, 1997). As a result, even after conditioning on age, education, and other observable indicators of human capital, labor market outcomes are likely to differ between foreign-born Hispanics and U.S.-born Hispanics (or between foreign-born Hispanics and U.S.-born whites), because of differences in the returns to human capital for foreign-born and U.S.-born workers. For this reason, nativity plays a key role in shaping the labor market success of Hispanics, and it is essential that labor market analyses of U.S. Hispanics distinguish between immigrants and the U.S.-born. English language proficiency is an important dimension of human capital closely related to nativity. Census microdata provide self-reported information on English ability, and we display some of this information in Figure 7-1.5 All respondents were asked whether they “speak a language other than English at home,” and only those who answered affirmatively were asked how well they speak English, with possible responses of “very well,” “well,” “not well,” or “not at all.” For the tabulations presented in Figure 7-1, English monolinguals are presumed to speak English “very well” and are grouped together with bilinguals who indicated the highest level of English proficiency. By this accounting, only a third of Hispanic immigrants speak English very well, but the proportion approaches 90 percent for U.S.-born Hispanics. Even among U.S. natives, however, the English proficiency of Hispanics falls somewhat short of the 99 percent rates observed for blacks and whites. Given the substantial penalties that the U.S. labor market assesses for English deficiencies (Bleakley and Chin, 2004; Grenier, 1984; McManus et al., 1983; Mora, 1998), the language gaps observed in Figure 7-1 can explain a considerable portion of Hispanic employment and earnings deficits, especially for immigrants, but also to some extent for U.S.-born Hispanics. In addition, English language proficiency varies across Hispanic subgroups. Among immigrants, Mexicans have the lowest rate of English proficiency (with 26 percent speaking the language very well), whereas the corresponding rate is around 50 percent for Cubans and still higher for Puerto Ricans. Differences are much less pronounced for U.S.-born Hispanics, with rates just under 90 percent for Mexicans and Puerto Ricans and a somewhat higher rate for Cubans. A key feature of Hispanic immigration is that much of it is undocumented. Given the clandestine nature of undocumented immigration, this 5   More detailed information is reported in Appendix Table A7-2.

OCR for page 228
Hispanics and the Future of America FIGURE 7-1 Percentage speaking English very well, by gender, ethnicity, and nativity. NOTE: The samples include individuals ages 25 to 59. In these tabulations, those who speak only English are presumed to speak English “very well.” See Appendix Table A7-2 for further details. SOURCE: 2000 census, 5% PUMS. population is difficult to observe, but some credible information is available nonetheless. Passel, Capps, and Fix (2004) estimate that Latin Americans made up 80 percent of the undocumented immigrants living in the United States as of March 2002, with Mexicans alone accounting for 57 percent of the undocumented population. Moreover, these same authors estimate that undocumented immigrants represent a quarter of the total foreign-born population in the United States, and Passel (2004) indicates that the share of undocumented immigrants is much higher among foreign-born Hispan-

OCR for page 228
Hispanics and the Future of America ics, particularly for recent immigrants. Indeed, Passel (2004) reports that over 80 percent of all Mexican immigrants who arrived in the United States after 1990 were undocumented as of March 2002. Does undocumented status, by itself, hurt the labor market opportunities of Hispanic immigrants? If so, by how much? Most sources of information about U.S. immigrants, including the decennial census and Current Population Survey data that we analyze in this chapter, do not identify undocumented immigrants, so our analyses will not be able to control for the legal status of Hispanic immigrants. Other studies, however, have exploited unique surveys to shed light on this issue. Massey (1987), for example, compared the U.S. wages earned by legal and illegal immigrants originating in four Mexican communities. He reports that undocumented Mexican immigrants earn substantially less, on average, then legal Mexican immigrants, but he also shows that this wage gap is explained by the lower human capital possessed by undocumented immigrants, particularly with regard to English proficiency and U.S. work experience. After controlling for observable determinants of earnings, Massey finds that legal status per se has little direct effect on U.S. wages for the Mexican immigrants in his sample. Donato and Massey (1993), however, obtained a different result when they conducted a similar analysis of later and more extensive data from 13 Mexican communities. In these later data, undocumented status reduced wages by about 20 percent, even after controlling for observables. Perhaps the best evidence on the labor market impact of undocumented status comes from a survey that tracked the experiences of initially undocumented immigrants before and after they were granted permanent legal resident status through the amnesty provisions of the 1986 Immigration Reform and Control Act. Despite using somewhat different approaches, Rivera-Batiz (1999) and Kossoudji and Cobb-Clark (2002) reach similar conclusions. First, holding observable skills constant, estimates suggest that legalization raised the wages of these workers by about 5–10 percent relative to what their wages would have been had the workers remained undocumented. Second, by increasing the incentives for these workers to invest in human capital, legalization also may have induced greater skill acquisition and thereby boosted wages through this indirect channel. Clearly, legal status is an important factor underlying the huge earnings deficits for Hispanic immigrants (relative to U.S.-born whites) that we document below, and this is especially true for recent immigrants from Mexico and Central America. Nevertheless, undocumented immigration assumes a minor role in the Hispanic labor market story compared with the leading role played by human capital. Indeed, we show below that, even without controlling for legal status, all or most of the earnings deficits of Hispanic immigrants can be explained by their low levels of education and English proficiency.

OCR for page 228
Hispanics and the Future of America TABLE 7-2 Annual Employment Rates (Percentages), by Gender, Ethnicity, and Nativity Ethnicity Men, by Nativity Women, by Nativity All Foreign-Born U.S.-Born All Foreign-Born U.S.-Born Whites     91.8     80.2 Blacks     77.4     77.7 All Hispanics 86.8 87.5 85.6 67.0 61.2 76.3 Mexicans 87.8 88.5 86.5 64.7 56.1 76.4 Puerto Ricans 80.0 76.6 83.8 67.7 60.8 75.5 Cubans 87.3 86.8 89.1 74.7 72.5 82.5 NOTE: The samples include individuals ages 25 to 59. See Appendix Table A7-3 for standard errors, as well as for analogous calculations for other Hispanic subgroups. SOURCE: 2000 census, 5% PUMS. Employment The success of Hispanics in the U.S. labor market heavily depends on their propensity to work and the kinds of jobs they are able to secure. We now turn to a discussion of these issues, highlighting the important influence of human capital. Table 7-2 reports annual employment rates for whites, blacks, and Hispanics, by gender and nativity. The annual employment rate is defined as the percentage of individuals who worked at all during the calendar year preceding the census.6 For men, the overall Hispanic employment rate of 87 percent is somewhat lower than the 92 percent rate for U.S.-born whites but well above the 77 percent rate for U.S.-born blacks. Among Hispanic men, Mexicans and Cubans are employed at similar rates, and these rates vary only modestly with nativity, whereas the lower rates observed for Puerto Ricans (80 percent, overall) are markedly higher for the U.S-born (84 percent) than the foreign-born (77 percent).7 For Hispanic women, Table 7-2 highlights the important role that nativity plays in employment determination. For every national-origin 6   See Appendix Table A7-3 for further details. Another possible measure of labor supply is annual hours of work. Compared with the employment rate, this measure has the advantage of reflecting the intensity as well as the incidence of work. It turns out, however, that the relevant patterns for annual hours are similar to those for employment, so we present only the results for employment. 7   Appendix Table A7-3 shows that Dominican men also have relatively low employment rates. Unlike the situation for Puerto Ricans, however, employment rates are similar for foreign-born and U.S.-born Dominicans.

OCR for page 228
Hispanics and the Future of America group, employment rates are at least 10 percentage points lower for immigrants than for U.S. natives, with this immigrant-native gap reaching 20 percentage points for Mexicans. Among U.S.-born women, the employment rates of 76 percent for Mexicans and Puerto Ricans are close to the corresponding rates for blacks (78 percent) and whites (80 percent), and the 83 percent rate for Cubans is highest of all. How much does the human capital deficit of U.S. Hispanics contribute to their employment gap? The next two graphs address this question, with results for men presented in Figure 7-2 and those for women in Figure 7-3. FIGURE 7-2 Male employment deficits relative to U.S.-born whites, by ethnicity and nativity. NOTE: The samples include individuals ages 25 to 59. All of the reported differentials control for geographic location and age. See Appendix Table A7-4 for further details. SOURCE: 2000 census, 5% PUMS.

OCR for page 228
Hispanics and the Future of America FIGURE 7-3 Female employment deficits relative to U.S.-born whites, by ethnicity and nativity. NOTE: The samples include individuals ages 25 to 59. All of the reported differentials control for geographic location and age. See Appendix Table A7-4 for further details. SOURCE: 2000 census, 5% PUMS. To highlight ethnic differences, these graphs show the percentage point gap between the employment rate of each group and the corresponding rate for U.S.-born whites. A positive gap implies that whites have a higher employment rate than the group in question, whereas a negative gap indicates the opposite.8 The top panel of each figure displays the employment gaps that 8   The employment gaps shown in Figures 7-2 and 7-3 are based on the estimates reported in Appendix Table A7-4. In the graphs, however, the estimates in Table A7-4 have been first multiplied by 100 to transform them into percentage point differentials, and then their signs have been reversed so that they represent employment deficits, rather than differences, relative to U.S.-born whites.

OCR for page 228
Hispanics and the Future of America remain after using regression analysis to control for the influence of geographic location and age.9 The bottom panel of each figure shows what happens to the estimated employment gaps when the underlying regressions also control for completed years of schooling and English language proficiency.10 The main lesson from these figures is that the human capital disadvantage of Hispanics can account for most of their employment deficit. Indeed, after conditioning on educational attainment and English proficiency, Hispanic employment gaps (relative to U.S.-born whites) tend to vanish. For example, after adjusting for age and geographic location, Mexican men have employment deficits of 5–6 percentage points, but controlling for human capital lowers the deficit to 2 percentage points for U.S.-born Mexican Americans and creates a large employment advantage for Mexican immigrants. Foreign-born Mexican women provide an even more striking case, as controlling for education and language cuts their employment deficit from 25 percentage points down to just 3 percentage points. Puerto Ricans are an exception to this pattern, however. For immigrants, both men and women, and for U.S.-born men, large Puerto Rican employment gaps shrink substantially after conditioning on human capital, but even the adjusted gaps remain sizeable.11 Do Hispanic workers fill particular roles in the U.S. economy? Table 7-3 examines one facet of this question: the propensity to be self-employed. Among individuals ages 25–59 who were employed during the census reference week, Table 7-3 reports the percentage that mainly worked in their own business (whether incorporated or not).12 Overall, Hispanic self-employment rates lie between the corresponding rates of blacks and whites, with substantial variation across Hispanic subgroups. Cubans, both men and women, are self-employed at relatively high rates, with the rate for 9   Separate least-squares regressions were run for men and women. The dependent variable is a dummy variable indicating whether the respondent worked at all during the calendar year preceding the census. These regressions allow intercepts to differ across ethnicity/nativity groups (with U.S.-born whites as the reference group), but the coefficients of the control variables are restricted to be the same for all groups. The control variables include indicators for geographic location and age. The geographic indicators are dummy variables identifying the nine census divisions, eight states that are home to a large proportion of the Hispanic population in the United States (Arizona, California, Florida, Illinois, New Jersey, New Mexico, New York, and Texas), and whether the respondent resides in a metropolitan area. The age indicators are dummy variables identifying the five-year age group (i.e., 25–29, 30–34, …, 55–59) to which each respondent belongs. 10   The controls for English proficiency are a set of dummy variables identifying whether respondents speak a language other than English at home, and, if so, how well such individuals report being able to speak English: “very well,” “well,” “not well,” or “not at all.” 11   Appendix Table A7-4 shows that U.S.-born Dominican men display a similar pattern. 12   See Appendix Table A7-5 for further details.

OCR for page 228
Hispanics and the Future of America Ethnicity/Nativity Employment Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) Controls for: Geographic location Yes Yes Yes Yes Yes Yes Age Yes Yes Yes Yes Yes Yes Education No Yes Yes No Yes Yes English proficiency No No Yes No No Yes NOTE: The reported figures are estimated coefficients from least-squares regressions in which the dependent variable is a dummy variable indicating whether the respondent worked at all during the calendar year preceding the survey. Standard errors are shown in parentheses. The samples include individuals ages 25 to 59. SOURCE: 2000 census, 5% PUMS.

OCR for page 228
Hispanics and the Future of America APPENDIX TABLE A7-5 Self-Employment Rates, by Gender, Detailed Ethnicity, and Nativity Ethnicity Men, by Nativity Women, by Nativity All Foreign-Born U.S.-Born All Foreign-Born U.S.-Born Whites     0.139     0.081       (0.0008)     (0.0007) Blacks     0.058     0.034       (0.0005)     (0.0004) All Hispanics 0.082 0.084 0.079 0.066 0.080 0.050   (0.0005) (0.0007) (0.001) (0.0006) (0.0008) (0.001) Mexicans 0.075 0.074 0.077 0.061 0.076 0.048   (0.0006) (0.0008) (0.001) (0.0007) (0.0011) (0.001) Puerto Ricans 0.056 0.057 0.055 0.040 0.042 0.038   (0.002) (0.002) (0.002) (0.001) (0.002) (0.002) Cubans 0.159 0.169 0.127 0.074 0.076 0.071   (0.003) (0.004) (0.007) (0.003) (0.003) (0.005) Dominicans 0.102 0.105 0.073 0.061 0.066 0.024   (0.004) (0.004) (0.011) (0.003) (0.003) (0.006) Salvadorans/Guatemalans 0.076 0.076 0.068 0.106 0.109 0.029   (0.002) (0.002) (0.012) (0.003) (0.003) (0.008) Other Central Americans 0.076 0.075 0.089 0.078 0.079 0.068   (0.003) (0.003) (0.011) (0.003) (0.003) (0.010) Colombians 0.109 0.113 0.071 0.116 0.123 0.053   (0.004) (0.004) (0.011) (0.004) (0.005) (0.010) Peruvians/Ecuadorans 0.102 0.106 0.063 0.086 0.092 0.035   (0.004) (0.004) (0.011) (0.004) (0.004) (0.008) Other South Americans 0.145 0.150 0.103 0.114 0.120 0.072   (0.005) (0.005) (0.013) (0.005) (0.006) (0.011) Other Hispanics 0.103 0.140 0.099 0.065 0.104 0.061   (0.002) (0.009) (0.002) (0.002) (0.008) (0.002) NOTE: Standard errors are shown in parentheses. The samples include individuals ages 25 to 59 who were employed during the census reference week. SOURCE: 2000 census, 5% PUMS.

OCR for page 228
Hispanics and the Future of America APPENDIX TABLE A7-6 Self-Employment Differentials, by Gender, Detailed Ethnicity, and Nativity Ethnicity/Nativity Self-Employment Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) U.S.-born blacks −.075 −.074 −.074 −.042 −.042 −.042   (.001) (.001) (.001) (.001) (.001) (.001) All Hispanics: All −.052 −.048 −.061 −.020 −.020 −.029   (.001) (.001) (.002) (.001) (.001) (.002) Foreign-born −.050 −.044 −.055 −.006 −.006 −.014   (.002) (.002) (.002) (.001) (.002) (.002) U.S.-born −.056 −.054 −.066 −.036 −.036 −.039   (.002) (.002) (.002) (.002) (.002) (.002) Mexicans: All −.059 −.055 −.066 −.029 −.029 −.037   (.002) (.002) (.002) (.002) (.002) (.002) Foreign-born −.057 −.051 −.060 −.015 −.015 −.024   (.002) (.002) (.003) (.002) (.002) (.003) U.S.-born −.061 −.060 −.071 −.041 −.041 −.044   (.002) (.002) (.003) (.002) (.002) (.002) Puerto Ricans: All −.073 −.072 −.087 −.033 −.033 −.039   (.004) (.004) (.004) (.003) (.003) (.003) Foreign-born −.082 −.080 −.097 −.034 −.034 −.041   (.005) (.005) (.006) (.005) (.005) (.005) U.S.-born −.065 −.063 −.076 −.031 −.031 −.034   (.005) (.005) (.006) (.004) (.004) (.004) Cubans: All. 010 .011 −.003 −.011 −.011 −.018   (.006) (.006) (.006) (.005) (.005) (.005) Foreign-born .012 .013 .000 −.013 −.013 −.020   (.006) (.006) (.007) (.006) (.006) (.006) U.S.-born .005 .004 −.008 −.003 −.003 −.006   (.011) (.011) (.011) (.009) (.009) (.009) Dominicans: All −.029 −.026 −.039 −.009 −.010 −.022   (.007) (.007) (.007) (.006) (.006) (.006) Foreign-born −.028 −.025 −.036 −.006 −.006 −.016   (.008) (.008) (.008) (.006) (.006) (.006) U.S.-born −.029 −.028 −.044 −.036 −.036 −.039   (.024) (.024) (.024) (.017) (.017) (.017)

OCR for page 228
Hispanics and the Future of America Ethnicity/Nativity Self-Employment Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) Salvadorians/Guatemalans: All −.054 −.049 −.062 .018 .017 .003   (.005) (.005) (.005) (.004) (.005) (.005) Foreign-born −.054 −.049 −.060 .021 .021 .011   (.005) (.005) (.005) (.005) (.005) (.005) U.S.-born −.050 −.049 −.062 −.049 −.049 −.052   (.028) (.028) (.028) (.022) (.022) (.022) Other Central Americans: All −.056 −.054 −.067 −.006 −.006 −.016   (.007) (.007) (.007) (.006) (.006) (.006) Foreign-born −.058 −.055 −.067 −.005 −.005 −.013   (.007) (.007) (.007) (.006) (.006) (.006) U.S.-born −.035 −.035 −.046 −.009 −.009 −.011   (.022) (.022) (.022) (.017) (.017) (.017) Colombians: All −.029 −.028 −.043 .037 .037 .025   (.008) (.008) (.008) (.006) (.006) (.006) Foreign-born −.028 −.027 −.041 .043 .043 .033   (.008) (.008) (.008) (.006) (.006) (.007) U.S.-born −.035 −.036 −.049 −.011 −.011 −.014   (.024) (.024) (.024) (.019) (.019) (.019) Peruvians/Ecuadorans: All −.031 −.030 −.045 .008 .008 –.004   (.007) (.007) (.007) (.006) (.006) (.006) Foreign-born −.030 −.029 −.042 .013 .013 .004   (.007) (.007) (.007) (.006) (.006) (.007) U.S.-born −.044 −.044 −.057 −.033 −.033 −.035   (.024) (.024) (.024) (.019) (.019) (.019) Other South Americans: All. 006 .006 −.011 .032 .032 .023   (.008) (.008) (.008) (.007) (.007) (.007) Foreign-born .008 .008 −.008 .037 .037 .030   (.009) (.009) (.009) (.008) (.008) (.008) U.S.-born −.010 −.011 −.023 −.002 −.002 −.004   (.025) (.025) (.025) (.020) (.020) (.020) Other Hispanics: All −.038 −.037 −.046 −.027 −.027 −.030   (.005) (.005) (.005) (.004) (.004) (.004) Foreign-born .000 .000 −.014 .022 .022 .016   (.014) (.014) (.015) (.012) (.012) (.012) U.S.-born −.043 −.041 −.050 −.032 −.032 −.034   (.005) (.005) (.005) (.004) (.004) (.004)

OCR for page 228
Hispanics and the Future of America Ethnicity/Nativity Self-Employment Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) Controls for: Geographic location Yes Yes Yes Yes Yes Yes Age Yes Yes Yes Yes Yes Yes Education No Yes Yes No Yes Yes English proficiency No No Yes No No Yes NOTE: The reported figures are estimated coefficients from least-squares regressions in which the dependent variable is a dummy variable indicating whether the respondent is self-employed. Standard errors are shown in parentheses. The samples include individuals ages 25 to 59 who were employed during the census reference week. SOURCE: 2000 census, 5% PUMS.

OCR for page 228
Hispanics and the Future of America APPENDIX TABLE A7-7 Annual Earnings Differentials, by Gender, Detailed Ethnicity, and Nativity Ethnicity/Nativity Log Earnings Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) U.S.-born blacks −.440 −.347 −.348 −.050 .026 .026   (.004) (.004) (.004) (.004) (.004) (.004) All Hispanics: All −.492 −.171 −.094 −.333 −.043 .016   (.004) (.004) (.005) (.005) (.005) (.006) Foreign-born −.588 −.169 −.045 −.492 −.083 .002   (.004) (.004) (.007) (.006) (.006) (.008) U.S.-born −.307 −.175 −.133 −.124 .004 .025   (.006) (.005) (.006) (.007) (.006) (.007) Mexicans: All −.542 −.141 −.057 −.397 −.027 .032   (.004) (.005) (.006) (.006) (.006) (.007) Foreign-born −.658 −.119 .024 −.633 −.053 .044   (.005) (.006) (.008) (.008) (.008) (.011) U.S.-born −.334 −.174 −.129 −.162 −.004 .019   (.007) (.007) (.007) (.008) (.008) (.009) Puerto Ricans: All −.380 −.218 −.162 −.172 −.028 .014   (.011) (.010) (.011) (.012) (.012) (.013) Foreign-born −.463 −.251 −.162 −.279 −.101 −.037   (.015) (.014) (.015) (.018) (.017) (.018) U.S.-born −.297 −.183 −.138 −.076 .036 .060   (.015) (.015) (.015) (.017) (.017) (.017) Cubans: All −.242 −.169 −.087 −.021 .025 .083   (.016) (.015) (.016) (.020) (.019) (.020) Foreign-born −.315 −.215 −.097 −.097 −.018 .053   (.018) (.017) (.018) (.022) (.022) (.022) U.S.-born .007 −.008 .036 .200 .150 .168   (.033) (.032) (.032) (.039) (.038) (.038) Dominicans: All −.637 −.363 −.263 −.475 −.178 −.085   (.019) (.019) (.019) (.022) (.021) (.022) Foreign-born −.672 −.379 −.246 −.532 −.212 −.112   (.020) (.020) (.020) (.023) (.022) (.023) U.S.-born −.267 −.175 −.115 .047 .122 .152   (.065) (.063) (.063) (.070) (.068) (.068)

OCR for page 228
Hispanics and the Future of America Ethnicity/Nativity Log Earnings Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) Salvadorians/Guatemalans: All −.599 −.112 −.008 −.500 .055 .153   (.013) (.012) (.013) (.017) (.017) (.018) Foreign-born −.610 −.111 .026 −.520 .051 .154   (.013) (.013) (.014) (.018) (.017) (.018) U.S.-born −.205 −.056 .001 −.048 .090 .119   (.078) (.076) (.076) (.089) (.086) (.086) Other Central Americans: All −.470 −.216 −.124 −.357 −.123 −.045   (.019) (.018) (.019) (.022) (.021) (.022) Foreign-Born −.502 −.224 −.100 −.405 −.148 −.064   (.020) (.019) (.019) (.023) (.022) (.023) U.S.-born −.143 −.121 −.080 .092 .101 .122   (.063) (.061) (.061) (.070) (.068) (.068) Colombians: All −.403 −.311 −.221 −.341 −.211 −.122   (.021) (.021) (.021) (.024) (.024) (.024) Foreign-born −.432 −.325 −.205 −.395 −.248 −.153   (.022) (.022) (.022) (.025) (.025) (.025) U.S.-born −.150 −.178 −.129 .176 .143 .167   (.068) (.066) (.066) (.080) (.078) (.078) Peruvians/Ecuadorans: All −.458 −.318 −.226 −.307 −.163 −.078   (.019) (.019) (.019) (.024) (.024) (.024) Foreign-born −.493 −.339 −.218 −.357 −.196 −.105   (.020) (.019) (.020) (.025) (.025) (.025) U.S.-born −.040 −.044 .006 .155 .142 .165   (.070) (.068) (.068) (.079) (.077) (.077) Other South Americans: All −.194 −.189 −.113 −.155 −.152 −.085   (.024) (.023) (.023) (.029) (.028) (.029) Foreign-born −.227 −.213 −.115 −.205 −.185 −.114   (.025) (.024) (.024) (.031) (.030) (.031) U.S.-born. 069 .012 .055 .163 .075 .095   (.072) (.070) (.070) (.081) (.079) (.079) Other Hispanics: All −.319 −.184 −.152 −.168 −.033 −.013   (.013) (.013) (.013) (.015) (.015) (.015) Foreign-born −.165 −.116 −.035 −.114 −.085 −.033   (.041) (.039) (.039) (.048) (.047) (.047) U.S.-born −.331 −.192 −.160 −.168 −.027 −.011   (.014) (.013) (.014) (.016) (.015) (.016)

OCR for page 228
Hispanics and the Future of America Ethnicity/Nativity Log Earnings Differentials, Relative to U.S.-Born Whites Men Women (1) (2) (3) (1) (2) (3) Controls for: Geographic location Yes Yes Yes Yes Yes Yes Age Yes Yes Yes Yes Yes Yes Education No Yes Yes No Yes Yes English proficiency No No Yes No No Yes NOTE: The reported figures are estimated coefficients from least-squares regressions in which the dependent variable is the natural logarithm of annual earnings. Standard errors are shown in parentheses. The samples include individuals ages 25 to 59 who worked during the calendar year preceding the survey. SOURCE: 2000 census, 5% PUMS.

OCR for page 228
Hispanics and the Future of America APPENDIX TABLE A7-8 Average Years of Schooling, by Gender, Ethnicity, and Generation Ethnicity Men, by Generation Women, by Generation All 1st 2nd 3rd+ All 1st 2nd 3rd+ Whites       13.6       13.6         (.007)       (.007)         [110,226]       [115,031] Blacks       12.7       12.9         (.02)       (.02)         [12,820]       [17,395] All Hispanics 10.7 9.7 12.5 12.4 10.9 9.9 12.6 12.4   (.02) (.03) (.04) (.03) (.02) (.03) (.04) (.03)   [26,190] [16,772] [3,539] [5,879] [27,489] [16,627] [4,150] [6,712] Mexicans 10.1 8.8 12.2 12.3 10.3 8.7 12.2 12.2   (.03) (.04) (.06) (.04) (.03) (.04) (.05) (.04)   [16,316] [10,051] [2,009] [4,256] [16,064] [8,852] [2,344] [4,868] Puerto Ricans 11.9 11.2 12.5 12.7 12.1 11.6 12.7 12.8   (.06) (.10) (.08) (.15) (.06) (.09) (.07) (.14)   [2,348] [1,232] [800] [316] [2,975] [1,551] [1,044] [380] Cubans 12.8 12.5 14.1 12.2 13.0 12.6 14.3 13.8   (.09) (.11) (.15) (.51) (.09) (.11) (.17) (.43)   [1,116] [853] [229] [34] [1,116] [868] [208] [40] Central/South Americans 11.2 11.0 13.5 12.4 11.5 11.2 13.9 13.4   (.06) (.07) (.15) (.26) (.06) (.06) (.14) (.18)   [4,352] [3,935] [277] [140] [4,931] [4,428] [324] [179] Other Hispanics 12.5 11.7 13.4 13.1 12.3 11.2 13.2 13.1   (.07) (.13) (.17) (.07) (.06) (.13) (.14) (.06)   [2,058] [701] [224] [1,133] [2,403] [928] [230] [1,245] NOTE: Standard errors are shown in parentheses, and sample sizes are shown in brackets. The samples include individuals ages 25 to 59. SOURCE: March 1998–2002, CPS data.

OCR for page 228
Hispanics and the Future of America APPENDIX TABLE A7-9 Annual Earnings Differentials, by Gender, Ethnicity, and Generation Ethnicity/Generation Log Earnings Differentials, Relative to 3rd+ Generation Whites Men Women (1) (2) (3) (1) (2) (3) 3rd+ generation blacks −.424 −.409 −.309 −.072 −.064 .027   (.012) (.012) (.011) (.012) (.012) (.011) All Hispanics: All generations −.539 −.499 −.138 −.356 −.340 −.016   (.011) (.011) (.011) (.013) (.013) (.013) 1st generation −.644 −.606 −.133 −.521 −.509 −.052   (.013) (.013) (.014) (.017) (.017) (.017) 2nd generation −.382 −.314 −.177 −.120 −.085 .053   (.026) (.026) (.025) (.029) (.029) (.028) 3rd+ generation −.300 −.271 −.124 −.160 −.147 .008   (.022) (.022) (.021) (.024) (.024) (.023) Mexicans: All generations −.592 −.544 −.103 −.424 −.405 .003   (.013) (.013) (.014) (.017) (.017) (.017) 1st generation −.719 −.668 −.070 −.668 −.650 −.007   (.016) (.016) (.017) (.023) (.023) (.024) 2nd generation −.444 −.381 −.190 −.174 −.142 .048   (.033) (.033) (.032) (.037) (.037) (.036) 3rd+ generation −.337 −.307 −.131 −.210 −.197 −.007   (.024) (.024) (.024) (.027) (.027) (.026) Puerto Ricans: All generations −.402 −.376 −.189 −.192 −.175 −.023   (.035) (.035) (.034) (.037) (.037) (.036) 1st generation −.478 −.481 −.225 −.279 −.278 −.093   (.048) (.047) (.046) (.054) (.054) (.052) 2nd generation −.357 −.306 −.182 −.135 −.102 .030   (.059) (.058) (.057) (.059) (.059) (.058) 3rd+ generation −.236 −.162 −.054 −.081 −.051 .051   (.095) (.095) (.092) (.097) (.097) (.095) Cubans: All generations −.312 −.304 −.211 −.124 −.116 −.060   (.046) (.046) (.045) (.056) (.056) (.055) 1st generation −.379 −.391 −.263 −.210 −.215 −.112   (.053) (.052) (.051) (.064) (.064) (.063) 2nd generation −.061 .021 −.012 .073 .125 .041   (.102) (.102) (.099) (.122) (.122) (.119) 3rd+ generation −.366 −.320 −.172 .365 .390 .355   (.266) (.264) (.257) (.271) (.271) (.264)

OCR for page 228
Hispanics and the Future of America Ethnicity/Generation Log Earnings Differentials, Relative to 3rd+ Generation Whites Men Women (1) (2) (3) (1) (2) (3) Central/South Americans: All generations −.545 −.509 −.200 −.365 −.353 −.049   (.024) (.024) (.023) (.028) (.028) (.027) 1st generation −.576 −.546 −.207 −.423 −.414 −.073   (.025) (.025) (.024) (.030) (.030) (.029) 2nd generation −.251 −.129 −.091 .072 .129 .148   (.091) (.091) (.088) (.100) (.100) (.097) 3rd+ generation −.315 −.298 −.178 .055 .056 .107   (.135) (.134) (.131) (.142) (.142) (.138) Other Hispanics: All generations −.338 −.314 −.162 −.211 −.202 −.028   (.039) (.039) (.038) (.043) (.043) (.042) 1st generation −.509 −.494 −.251 −.454 −.450 −.177   (.059) (.059) (.058) (.067) (.067) (.066) 2nd generation −.394 −.309 −.265 −.026 .011 .102   (.109) (.108) (.105) (.119) (.119) (.116) 3rd+ generation −.148 −.134 −.046 −.043 −.036 .066   (.058) (.058) (.056) (.063) (.063) (.061) Controls for: Survey year Yes Yes Yes Yes Yes Yes Geographic location Yes Yes Yes Yes Yes Yes Age No Yes Yes No Yes Yes Education No No Yes No No Yes NOTE: The reported figures are estimated coefficients from least squares regressions in which the dependent variable is the natural logarithm of annual earnings. Standard errors are shown in parentheses. The samples include individuals ages 25 to 59 who worked during the calendar year preceding the survey. SOURCE: March 1998–2002, CPS data.