Using Two-Sample Methods to Correct for Reporting Bias in Surveys
Bruce Meyer and
James Sullivan ()
No 902, Working Papers from Harris School of Public Policy Studies, University of Chicago
Benefit receipt in major household surveys is often underreported. This understatement has major implications for our understanding of the economic circumstances of disadvantaged populations, program takeup, the distributional effects of government programs, and studies of other program effects. We provide a new econometric method for estimating the determinants of reporting that uses two data sources with overlapping demographic characteristics rather than requiring matched individual data. This method compares the characteristics of those who report receipt in the survey to the characteristics of recipients in the administrative data to determine the influence of those characteristics on reporting. Our estimates using this two sample estimation procedure indicate that observable characteristics are related to underreporting in the case of the Food Stamp Program (FSP). We then show how these results can be used to correct for underreporting bias in studies of FSP participation or the distributional effects of the FSP. Our results also have implications for studies that use FSP receipt as an explanatory variable.
Keywords: food stamp program; benefits; reporting (search for similar items in EconPapers)
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