Combining Administrative and Survey Data to Improve Income Measurement

31 Pages Posted: 15 Apr 2019 Last revised: 30 Apr 2021

See all articles by Bruce D. Meyer

Bruce D. Meyer

University of Chicago - Harris School of Public Policy; National Bureau of Economic Research (NBER)

Nikolas Mittag

University of Chicago - Harris School of Public Policy

Date Written: April 2019

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.

Suggested Citation

Meyer, Bruce D. and Mittag, Nikolas, Combining Administrative and Survey Data to Improve Income Measurement (April 2019). NBER Working Paper No. w25738, Available at SSRN: https://ssrn.com/abstract=3372034

Bruce D. Meyer (Contact Author)

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

1155 East 60th Street
Chicago, IL 60637
United States
(773) 702-2712 (Phone)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
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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