Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data
Melvin Stephens and
Takashi Unayama ()
No 21248, NBER Working Papers from National Bureau of Economic Research, Inc
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.
JEL-codes: C80 E21 H53 H55 (search for similar items in EconPapers)
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Published as Melvin Stephens & Takashi Unayama, 2019. "Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 468-475, July.
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