Combining Administrative and Survey Data to Improve Income Measurement

32 Pages Posted: 21 May 2019

See all articles by Bruce Meyer

Bruce Meyer

University of Chicago

Nikolas Mittag

University of Chicago - Harris School of Public Policy

Abstract

We describe methods of combining administrative and survey data to improve the measurement of income. We begin by decomposing the total survey error in the mean of survey reports of dollars received from a government transfer program. We decompose this error into three parts, generalized coverage error (which combines coverage and unit non-response error and any error from weighting), item non-response or imputation error, and measurement error. We then discuss these three sources of error in turn and how linked administrative and survey data can assess and reduce each of these sources. We then illustrate the potential of linked data by showing how using linked administrative variables improves the measurement of income and poverty in the Current Population Survey, focusing on the substitution of administrative for survey data for three government transfer programs. Finally, we discuss how one can examine the accuracy of the underlying links used in the combined data.

Keywords: income distribution, survey error, administrative data, linked data, data combination

JEL Classification: C18, C81, C83, D31, I32

Suggested Citation

Meyer, Bruce and Mittag, Nikolas, Combining Administrative and Survey Data to Improve Income Measurement. IZA Discussion Paper No. 12266, Available at SSRN: https://ssrn.com/abstract=3390256

Bruce Meyer (Contact Author)

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Nikolas Mittag

University of Chicago - Harris School of Public Policy ( email )

1155 East 60th Street
Chicago, IL 60637
United States

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