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A discrete choice decomposition analysis of racial and ethnic differences in children's health insurance coverage

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  • Pylypchuk, Yuriy
  • Selden, Thomas M.

Abstract

This paper presents a multivariate decomposition analysis of racial and ethnic differences in children's health insurance using the 2004-2005 Medical Expenditure Panel Survey. We present two methodological contributions. First, we adapt a recently-developed matching decomposition method for use with sample-weighted data. Second, we develop a fully nonparametric approach that implements decomposition through weight adjustments. Accounting for the black-white wealth gap: a nonparametric approach. Journal of the American Statistical Association 97, 663-673]. Differences in observed characteristics explain large percentages of racial and ethnic coverage differences. Important contributors include poverty levels, parent education, family structure (for black children), and immigration-related factors (for Hispanic children). We also examine racial and ethnic differences in parent offers of employer-sponsored insurance and in children's coverage conditional on having a parent offer. Comparison of our linear, nonlinear, and nonparametric results suggests researchers may face a trade-off between robustness and precision when selecting among decomposition methodologies for discrete outcomes.

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  • Pylypchuk, Yuriy & Selden, Thomas M., 2008. "A discrete choice decomposition analysis of racial and ethnic differences in children's health insurance coverage," Journal of Health Economics, Elsevier, vol. 27(4), pages 1109-1128, July.
    • Handle: RePEc:eee:jhecon:v:27:y:2008:i:4:p:1109-1128
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    1. Yuriy Pylypchuk & James B. Kirby, 2017. "The role of marriage in explaining racial and ethnic disparities in access to health care for men in the US," Review of Economics of the Household, Springer, vol. 15(3), pages 807-832, September.
    2. Bowblis, John R. & Yun, Myeong-Su, 2010. "Racial and Ethnic Disparities in the Use of Drug Therapy," IZA Discussion Papers 4853, Institute of Labor Economics (IZA).
    3. Stewart Williams, Jennifer Anne, 2009. "Using non-linear decomposition to explain the discriminatory effects of male-female differentials in access to care: A cardiac rehabilitation case study," Social Science & Medicine, Elsevier, vol. 69(7), pages 1072-1079, October.
    4. Meliyanni Johar & Elizabeth Savage & Olena Stavrunova & Glenn Jones & Michael Keane, 2012. "Geographic Differences in Hospital Waiting Times," The Economic Record, The Economic Society of Australia, vol. 88(281), pages 165-181, June.
    5. Johar, Meliyanni & Jones, Glenn & Keane, Micheal P. & Savage, Elizabeth & Stavrunova, Olena, 2013. "Discrimination in a universal health system: Explaining socioeconomic waiting time gaps," Journal of Health Economics, Elsevier, vol. 32(1), pages 181-194.
    6. Tiffany R. Hsiou & Yuriy Pylypchuk, 2012. "Comparing And Decomposing Differences In Preventive And Hospital Care: Usa Versus Taiwan," Health Economics, John Wiley & Sons, Ltd., vol. 21(7), pages 778-795, July.
    7. Zhang, Hao & Bago d’Uva, Teresa & van Doorslaer, Eddy, 2015. "The gender health gap in China: A decomposition analysis," Economics & Human Biology, Elsevier, vol. 18(C), pages 13-26.
    8. Carolina Caetano & Gregorio Caetano & Juan Carlos Escanciano, 2023. "Regression discontinuity design with multivalued treatments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 840-856, September.
    9. Gloria Moroni, 2018. "Explaining Divorce Gaps in Cognitive and Noncognitive Skills of Children," Discussion Papers 18/16, Department of Economics, University of York.
    10. Linda Dynan, 2009. "The Contribution of Economists to Understanding Racial Health Disparities in the US," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 37(3), pages 213-223, September.

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