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What Explains the Gap in Welfare Use Among Immigrants and Natives?

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Abstract

We investigate the gap in welfare use between immigrants and natives over a 24-year period using the Annual Social and Economic Supplement of the Current Population Survey from 1995 to 2018, spanning periods of economic recessions and recoveries, changes in welfare policy regimes, and policies towards immigrants. A novel contribution of our research is to adopt the Oaxaca–Blinder decomposition analysis to study the effects of demographic factors, macroeconomic trends and policy on welfare use gap between immigrants and natives. Our analysis leads to three main findings: one, if immigrants had the same demographic characteristics as natives their participation in means-tested programs would have been much less overall and much below those of natives. This finding holds true across broader measures of welfare receipt capturing cash and near cash programs and health insurance as well as participation in five specific safety net programs. It also holds true across periods of economic recessions and recovery. Second, we find evidence that the business cycle impacts immigrant and native welfare participation differently. Immigrant participations in Temporary Assistance to Needy Families, Supplemental Nutritional Assistance Program and State Children’s Health Insurance Program are more sensitive to the business cycle than native participations. Three, we find that changes in program eligibility explain only a modest proportion of the immigrant-native gap in welfare use. A possible explanation for this finding is that changes in eligibility rules have affected only specific immigrant populations (e.g. new immigrants) whereas our analysis pertains to all immigrants.

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Notes

  1. Low-educated are defined as individuals with a high-school or lower education.

  2. Specifically, the second outcome is whether the household received any of the five programs: TANF, SSI, SNAP, Medicaid, and SCHIP.

  3. In the case of SSI, federal law made immigrant eligibility contingent on 40 quarters of work, irrespective of their duration of stay in the US, but five states used own funds to cover other immigrants (Kaushal 2011). The Federal law also imposed work requirements on SNAP eligibility for able-bodied adults without dependents.

  4. Allen (2018) found that county level Latino population density moderated the effect of Omnibus bills on program enrollment with counties with higher densities of Latino population experiencing low enrollment. Allen and McNeely (2017) did not consider county level factors.

  5. Borjas (2011) examined trends in poverty and welfare participation among native and immigrant children.

  6. In supplementary analysis, we included housing subsidy as one of the measures of welfare, and the results were not significantly different compared to the analyses without housing subsidy.

  7. Legal immigrant children, in the country for more than 5 years, are eligible for SCHIP in all states.

  8. 38.6% of our analytic sample has county identifiers.

  9. Because the March-CPS asked for the welfare participation in the previous year, unless specified otherwise the year used in the paper always refers to one year prior to the CPS survey year. Therefore, for the state-level variables, the one-year lag is relative to the year prior to the CPS survey year.

  10. The foreign-born variable is not included in the model due to the presence of the country of origin variable.

  11. Other studies have also documented this difference (Meyer et al. 2009).

  12. For the cash and near-cash participation outcome, we used a policy score that was based on eligibility to cash and near-cash programs.

  13. For a sensitivity analysis, we conducted the same models with randomly selected 50% samples. The results remained similar to those reported.

  14. We also estimated these models using county unemployment rate and county level policies towards immigrants for the observations where county information is given in the CPS and state level variables (unemployment rate and state policies) for the rest of the state without county identifiers. These models controlled for county (state fixed effects for those that do not have county identifiers). Estimates, presented in Appendix Tables 12 and 13, were similar to those in Tables 2 and 4.

  15. We also conducted sensitivity analysis adding “omnibus laws” which are sometimes referred as “show me your papers” laws as a control in the models in Tables 2, 3 and 4. The addition of this policy did not affect our estimates.

  16. This simply changed the sign of reported coefficients. We also did the analysis defining policies as in Tables 2 and 3 and the estimates were of the same magnitude with the coefficient being of the opposite sign.

  17. We also estimated these models using county unemployment rate and county policies towards immigrants for the observations where county information is available in the CPS and used state level variables for the rest of the state for which we do not have county identifiers (see Appendix Tables 12 and 13). In this analysis, the coefficient on exclusionary policies is statistically insignificant.

  18. Detailed results for the difference on account of endowments and coefficients can be obtained from the authors.

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Appendix

Appendix

See Tables 7, 8, 9, 10, 11, 12 and 13.

Table 7 State funded safety net program eligibility for post-enactment immigrants
Table 8 State-funded public health care eligibility for post-enactment immigrants
Table 9 State welfare policy score based on program eligibility for post-enactment immigrants in 2002
Table 10 Welfare participation among households with children in 2012: comparison with Camarota 2012
Table 11 Association between specific safety net programs and welfare policies and the business cycle
Table 12 Robustness check: association between state welfare policy score and the business cycle and program participation among low-educated households with children (with county variables)
Table 13 Robustness check: decomposition results for program participation gap between low-educated native and immigrant headed households with children (with county variables)

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Huang, X., Kaushal, N. & Wang, J.SH. What Explains the Gap in Welfare Use Among Immigrants and Natives?. Popul Res Policy Rev 40, 819–860 (2021). https://doi.org/10.1007/s11113-020-09621-8

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