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Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation

Author

Listed:
  • Bruce D. Meyer
  • Nikolas Mittag
  • Robert M. Goerge

Abstract

Accurately measuring government benefit receipt in household surveys is necessary when studying disadvantaged populations and welfare programs. The Food Stamp Program is especially important given its size and recent growth. To validate survey reports, we link administrative data on participation in two states to three key household surveys. We find that between 23 and 50 percent of true food stamp recipient households do not report receipt. A substantial number of true nonrecipients are also recorded as recipients. We examine reasons for these errors, including imputation, an important source of error. Error rates vary with household characteristics, implying complicated biases in multivariate analyses, such as regressions. We directly examine biases in common survey-based estimates of program receipt by comparing them to estimates from our linked data. We find that the survey estimates understate participation among single parents, nonwhites, and low-income households and also lead to errors in multiple program receipt and time and age patterns of receipt.

Suggested Citation

  • Bruce D. Meyer & Nikolas Mittag & Robert M. Goerge, 2022. "Errors in Survey Reporting and Imputation and Their Effects on Estimates of Food Stamp Program Participation," Journal of Human Resources, University of Wisconsin Press, vol. 57(5), pages 1605-1644.
    • Handle: RePEc:uwp:jhriss:v:57:y:2022:i:5:p:1605-1644
    Note: DOI: 10.3368/jhr.58.1.0818-9704R2
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    Citations

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    Cited by:

    1. Meyer, Bruce D. & Mittag, Nikolas & Wu, Derek, 2024. "Race, Ethnicity, and Measurement Error," IZA Discussion Papers 17349, Institute of Labor Economics (IZA).
    2. Bruce D. Meyer & Nikolas Mittag & Derek Wu, 2024. "Race, Ethnicity, and Measurement Error," NBER Chapters, in: Race, Ethnicity, and Economic Statistics for the 21st Century, National Bureau of Economic Research, Inc.
    3. Ha Trong Nguyen & Huong Thu Le & Luke Connelly & Francis Mitrou, 2023. "Accuracy of self‐reported private health insurance coverage," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2709-2729, December.
    4. Evan S. Totty & Thor Watson, 2024. "Privacy Protection and Accuracy: What Do We Know? Do We Know Things?? Let's Find Out!," NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences, National Bureau of Economic Research, Inc.
    5. Dean Jolliffe & Juan Margitic & Martin Ravallion & Laura Tiehen, 2024. "Food stamps and America's poorest," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(4), pages 1380-1409, August.
    6. Ross Abram & Margherita Borella & Mariacristina De Nardi & Rory McGee & Nicolò Russo, 2024. "Health Inequality and Economic Disparities by Race, Ethnicity, and Gender," Opportunity and Inclusive Growth Institute Working Papers 099, Federal Reserve Bank of Minneapolis.
    7. Alfonso Flores‐Lagunes & Hugo B. Jales & Judith Liu & Norbert L. Wilson, 2024. "Moving policies toward racial and ethnic equality: The case of the supplemental nutrition assistance program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 573-594, March.
    8. Cameron Deal & Shea Greenberg & Gilbert Gonzales, 2024. "Sexual identity, poverty, and utilization of government services," Journal of Population Economics, Springer;European Society for Population Economics, vol. 37(2), pages 1-31, June.
    9. Pourya Valizadeh & Bart L. Fischer & Henry L. Bryant, 2024. "SNAP enrollment cycles: New insights from heterogeneous panel models with cross‐sectional dependence," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 354-381, January.
    10. Flores-Lagunes, Alfonso & Jales, Hugo B. & Liu, Judith & Wilson, Norbert L., 2023. "Moving Policies Toward Racial and Ethnic Equality: The Case of the Supplemental Nutrition Assistance Program," GLO Discussion Paper Series 1272, Global Labor Organization (GLO).
    11. Liu, Xueyue & Zuo, Sharon Xuejing, 2023. "From equality to polarization: Changes in urban China’s gender earnings gap from 1988 to 2016," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 303-337.
    12. Richiardi, Matteo & Vella, Melchior, 2024. "Mind vs matter: economic and psychologic determinants of take-up rates of social benefits in the UK," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/24, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    13. Smith, Travis A. & Gregory, Christian A., 2024. "Misreporting of SNAP receipt in the Current Population Survey (CPS): Implications for Food Security Research," 2024 Annual Meeting, July 28-30, New Orleans, LA 343913, Agricultural and Applied Economics Association.
    14. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2024. "What leads to measurement errors? Evidence from reports of program participation in three surveys," Journal of Econometrics, Elsevier, vol. 238(2).

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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