Working Paper: NBER ID: w25738
Authors: Bruce D. Meyer; Nikolas Mittag
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: No keywords provided
JEL Codes: C81; D31; I32; I38
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| linking administrative records to household surveys (C81) | improve the accuracy of income and poverty estimates (C80) |
| linked administrative data (C80) | more accurate estimation of total survey error (TSE) (C83) |
| administrative data substitution for survey responses (C83) | alteration of reported poverty rates and income distributions (I32) |
| correcting for underreporting of transfer receipt (C83) | reduction in poverty rates according to the Current Population Survey (CPS) (I32) |
| using administrative measures (H83) | increase in reduction of poverty rates (I32) |
| survey errors (C83) | distorted understanding of poverty and program effectiveness (I32) |
| administrative records (H83) | more accurate measure of program receipt (C83) |