Combining Administrative and Survey Data to Improve Income Measurement

Bruce D. Meyer () and Nikolas Mittag ()
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Bruce D. Meyer: University of Chicago
Nikolas Mittag: CERGE-EI

No 12266, IZA Discussion Papers from Institute of Labor Economics (IZA)

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: administrative data; survey error; income distribution; linked data; data combination (search for similar items in EconPapers)
JEL-codes: C18 C81 C83 D31 I32 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2019-03
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published - published in: A. Y. Chun, M. Larson, J. Reiter and G. Durrant (eds.), Administrative Records for Survey Methodology, Wiley, 2021, 297 - 322

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