Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data
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- Melvin Stephens
- University of Michigan and NBER
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- Takashi Unayama
- Hitotsubashi University
書誌事項
- 公開日
- 2019-07
- 資源種別
- journal article
- DOI
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- 10.1162/rest_a_00769
- 公開者
- MIT Press - Journals
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説明
<jats:p> 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. </jats:p>
収録刊行物
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- The Review of Economics and Statistics
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The Review of Economics and Statistics 101 (3), 468-475, 2019-07
MIT Press - Journals
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詳細情報 詳細情報について
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- CRID
- 1360005521471839616
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- ISSN
- 15309142
- 00346535
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- 資料種別
- journal article
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- データソース種別
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- Crossref
- KAKEN
- OpenAIRE
