Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data
Melvin Stephens and
Takashi Unayama ()
Additional contact information
Melvin Stephens: University of Michigan and NBER
The Review of Economics and Statistics, 2019, vol. 101, issue 3, 468-475
Survey nonresponse has risen in recent years, which has increased the share of imputed and underreported values found on commonly used data sets. While this trend has been well documented for earnings, the growth in nonresponse 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 or measurement error in benefit amounts. We document the importance of failing to account for these issues using two empirical examples.
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Access to PDF is restricted to subscribers.
Working Paper: Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data (2015)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:tpr:restat:v:101:y:2019:i:3:p:468-475
Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535
Access Statistics for this article
The Review of Economics and Statistics is currently edited by Amitabh Chandra, Olivier Coibion, Bryan S. Graham, Shachar Kariv, Amit K. Khandelwal, Asim Ijaz Khwaja, Brigitte C. Madrian and Rohini Pande
More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by Ann Olson ().