Full Citation

Title: ESTIMATING THE IMPACTS OF PROGRAM BENEFITS: USING INSTRUMENTAL VARIABLES WITH UNDERREPORTED AND IMPUTED DATA

Citation Type: Working Paper

Publication Year: 2015

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Abstract: Survey non-response has risen in recent years which has increased the share of imputed and underreported values found on commonly used datasets. While this trend has been well-documented for earnings, the growth in non-response to government transfers questions has received far less attention. We demonstrate analytically that the underreporting and imputation of transfer benefits can lead to program impact estimates that are substantially overstated when using instrumental variables methods to correct for endogeneity and/or measurement error in benefit amounts. We document the importance of failing to account for these issues using two empirical examples.

Url: https://www.nber.org/papers/w21248.pdf

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Authors: Stephens, Melvin, Jr.; Unayama, Takashi

Series Title: NBER WORKING PAPER SERIES

Publication Number: 21248

Institution: NBER

Pages: 30

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Data Collections: IPUMS CPS

Topics: Population Data Science

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