An econometric method of correcting for unit nonresponse bias in surveys
Past approaches to correcting for unit nonresponse in sample surveys by re-weighting the data assume that the problem is ignorable within arbitrary subgroups of the population. Theory and evidence suggest that this assumption is unlikely to hold, and that household characteristics such as income systematically affect survey compliance. The authors show that this leaves a bias in the re-weighted data and they propose a method of correcting for this bias. The geographic structure of nonresponse rates allows them to identify a micro compliancefunction, which they then use to re-weight the unit-record data. An example is given for the U.S. Current Population Surveys, 1998-2004. The authors find, and correct for, a strong household income effect on response probabilities.
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- Tomas Philipson, 1997. "Data Markets and the Production of Surveys," Review of Economic Studies, Oxford University Press, vol. 64(1), pages 47-72.
- Anton Korinek & Johan Mistiaen & Martin Ravallion, 2006.
"Survey nonresponse and the distribution of income,"
The Journal of Economic Inequality,
Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 33-55, April.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Lillard, Lee & Smith, James P & Welch, Finis, 1986.
"What Do We Really Know about Wages? The Importance of Nonreporting and Census Imputation,"
Journal of Political Economy,
University of Chicago Press, vol. 94(3), pages 489-506, June.
- Lee Lillard & James P. Smith & Finis Welch, 2004. "What Do We Really Know About Wages: The Importance of Nonreporting and Census Imputation," Labor and Demography 0404005, EconWPA.
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