Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data
Estimating the Impacts of Program Benefits: Using Instrumental Variables with Underreported and Imputed Data
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DOI：
10.1162/rest_a_00769
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发表时间：
2015-06
影响因子：
8
通讯作者：
Melvin Stephens;T. Unayama
中科院分区：
文献类型：
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作者：
Melvin Stephens;T. Unayama
摘要近年来，调查不予答复的情况有所增加，这增加了在常用数据集上发现的推算和漏报的值的比例。虽然这一趋势在收入方面已经有了很好的记录，但对政府转账问题不予回应的增长却远远没有受到关注。我们通过分析证明，当使用工具变量方法纠正福利金额的内生性或测量错误时，对转移收益的低估和归因可能会导致项目影响估计被大大夸大。我们用两个经验性的例子证明了未能解释这些问题的重要性。
Abstract 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.