Research / BFI Working PaperApr 15, 2019

Combining Administrative and Survey Data to Improve Income Measurement

Bruce Meyer, Nikolas Mittag

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.

More Research From These Scholars

BFI Working Paper Aug 30, 2021

The Consumption, Income, and Well-Being of Single Mother Headed Families 25 Years After Welfare Reform

Jeehoon Han, Bruce Meyer, James X. Sullivan
Topics:  Economic Mobility & Poverty
BFI Working Paper Jun 5, 2019

The Use and Misuse of Income Data and Extreme Poverty in the United States

Carla Medalia, Victoria Mooers, Bruce Meyer, Derek Wu
Topics:  Economic Mobility & Poverty
BFI Working Paper Jun 21, 2022

The Size and Census Coverage of the U.S. Homeless Population

Bruce Meyer, Angela Wyse, Kevin Corinth
Topics:  Economic Mobility & Poverty