Abstract
Hispanic immigrant poverty is nearly double that of other immigrants. Furthermore, poverty rates among Hispanic families differ substantially by ethnicity. This paper analyzes poverty rates for Hispanic and non-Hispanic immigrants, and also for individual Hispanic ethnic groups, to determine the relative importance of different covariates of poverty. The general conclusion is that low levels of education and fluency in English contribute to high Hispanic poverty rates and are also contributing factors to differences in poverty among Hispanic ethnic groups. In particular, the high poverty rate of Mexican immigrant households is associated with the low educational attainments of household heads, along with a relatively large number of children, relatively low English fluency and a relatively short tenure in the U.S. Immigrants from Guatemala and El Salvador have substantially lower poverty rates than Mexican immigrants despite a similar constellation of observable traits. Immigrants from South America have low poverty rates, largely due to strong family work effort and high educational attainments. The relatively low family work effort and high incidence of single parent families among Puerto Ricans overpowers the beneficial effects of higher rates of citizenship and English fluency.
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Notes
The exact meaning of “Hispanic” and other ethnic terms in discussed under Data below. The statistic here may be found at http://ferret.bls.census.gov/macro/032006/pov/new29_000.htm.
Persons born in Puerto Rico are U.S. citizens, and therefore not “immigrants” in the typical sense of the term. The Census separately tabulates individuals who have “immigrated” from U.S. territories, however, and the Puerto Rican immigrants provide a valuable benchmark because they have the advantage of citizenship.
Unemployment is also relevant. De Jong and Madamba (2001, p. 25) show that after including controls for human capital and fluency, Hispanic workers are significantly more likely to be unemployed and (for males only) among the working poor.
Butcher and DiNardo (2002) also use Census microdata (for 1960–1990), but in a somewhat different way. They create counterfactual wage distributions controlled for age, schooling, race/ethnicity, marital status, geography, industry, region of origin and time in the U.S. While their paper is focused on different issues, the details of their analysis verify the “tremendous importance of race and ethnicity” (2002, p. 10) in determining the wage distribution of recent immigrants.
In thinking about what “Hispanic/Latino” means to those who fill out the form, it is useful to examine the results for the “Race” question on the Census 2000 form, in which it was possible for a person to list “some other race.” In fact, 41% of persons who gave their ethnicity as Hispanic or Latino also wrote in Hispanic or Latino as their sole answer to the question about race, and another 5% listed Hispanic or Latino as one of two racial identifiers (Grieco and Cassidy 2001, p. 10). In other words, the distinction between “race” and “Hispanic ethnicity” that drives the standard Census tabulations is either misunderstood or rejected by about half of the Hispanic population.
The approach used for poverty calculation in Census 2000 is explained at http://www.ipums.umn.edu/usa/pincome/povertya.html. Throughout the paper, we use the term “family” to cover both primary families (a household head and his or her relatives) and household heads who are unrelated individuals.
The characteristics of the household head and his or her family members are ordinarily correlated: young parents generally have young children, poorly educated husbands generally have poorly educated wives, etc. If one were to include the characteristics of spouses, for example, it would be necessary to conduct separate analyses for single and married heads, and it would therefore no longer be possible to estimate the independent effect of marital status.
We have also experimented with dummy variables for educational attainment, but found the results less interpretable than the ones reported below. Educational attainment is actually reported as nine grouped grade levels. We have attributed years equal to the mid-point of the attainments for all groups except the college educated, who were assigned a value of 16 years.
As noted in footnote 6, Census 2000 allowed a person to report a multiracial identity, leading to the new nomenclature “white alone or in combination.” To further complicate the issue, Darity et al. (2002) claim that Hispanics often self-report race in ways that contrast with their phenotypes.
The Census asks about citizenship, but not, of course, whether non-citizens are illegally present. This distinction is important because ethnicities differ greatly based on this unobservable. At one end of the spectrum, Mexicans can take advantage of a long border to immigrate illegally when prevented from doing so legally, while at the other end of the spectrum, Puerto Ricans have a citizen’s right to immigrate freely.
Chiswick and Miller (2002) find that the key distinction for immigrants’ earnings is between those who speak English “not well/not at all” and those who speak it “well/very well,” and they call the latter “fluent in English.” We employ the identical distinction.
Redstone and Massey (2004) find that the Census responses are not completely reliable, but that improved data do not generate statistically significant differences in wage equations.
We report sample results rather than weighted population estimates. We have experimented extensively with weighted results and have never found them to differ from sample results in any meaningful way.
The coefficients are the actual probit estimates, not the marginal probabilities shown in Table 3. We combine the effects of the linear and squared terms of the quadratic specifications when reporting the decompositions.
It also restricted the eligibility of some who had arrived earlier.
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Sullivan, D.H., Ziegert, A.L. Hispanic Immigrant Poverty: Does Ethnic Origin Matter?. Popul Res Policy Rev 27, 667–687 (2008). https://doi.org/10.1007/s11113-008-9096-3
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DOI: https://doi.org/10.1007/s11113-008-9096-3