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The Measurement of Medicaid Coverage in the SIPP: Evidence from California, 1990-1996

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  • David Card
  • Andrew K. G. Hildreth
  • Lara D. Shore-Sheppard

Abstract

This paper studies the accuracy of reported Medicaid coverage in the Survey of Income and Program Participation (SIPP) using a unique data set formed by matching SIPP survey responses to administrative records from the State of California. Overall, we estimate that the SIPP underestimates Medicaid coverage in the California population by about 10 percent. Among SIPP respondents who can be matched to administrative records, we estimate that the probability someone reports Medicaid coverage in a month when they are actually covered is around 85 percent. The corresponding probability for low-income children is even higher - at least 90 percent. These estimates suggest that the SIPP provides reasonably accurate coverage reports for those who are actually in the Medicaid system. On the other hand, our estimate of the false positive rate (the rate of reported coverage for those who are not covered in the administrative records) is relatively high: 2.5 percent for the sample as a whole, and up to 20 percent for poor children. Some of this is due to errors in the recording of Social Security numbers in the administrative system, rather than to problems in the SIPP.

Suggested Citation

  • David Card & Andrew K. G. Hildreth & Lara D. Shore-Sheppard, 2001. "The Measurement of Medicaid Coverage in the SIPP: Evidence from California, 1990-1996," NBER Working Papers 8514, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:8514
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    References listed on IDEAS

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    1. Jonathan Gruber, 2003. "Medicaid," NBER Chapters, in: Means-Tested Transfer Programs in the United States, pages 15-78, National Bureau of Economic Research, Inc.
    2. Lara D. Shore-Sheppard, 2005. "Stemming the Tide? The Effect of Expanding Medicaid Eligibility on Health Insurance," NBER Working Papers 11091, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Bruce Meyer & Robert Goerge, 2011. "Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation," Working Papers 11-14, Center for Economic Studies, U.S. Census Bureau.
    2. Kerstin Bruckmeier & Regina T. Riphahn & Jürgen Wiemers, 2021. "Misreporting of program take-up in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," Empirical Economics, Springer, vol. 61(3), pages 1567-1616, September.
    3. Jacob Alex Klerman & Jeanne S. Ringel & Elizabeth Roth, 2005. "Under-Reporting of Medicaid and Welfare in the Current Population Survey," Working Papers WR-169-3, RAND Corporation.
    4. Bruckmeier, Kerstin & Riphahn, Regina T. & Wiemers, Jürgen, 2019. "Benefit underreporting in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," IAB-Discussion Paper 201906, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    5. Jacob Alex Klerman & Jeanne S. Ringel & Beth Roth, 2005. "Under-Reporting of Medicaid and Welfare in the Current Population Survey," Working Papers 169-3, RAND Corporation.
    6. van der Klaauw, Wilbert, 2005. "Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 154-157, April.

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    More about this item

    JEL classification:

    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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