Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net
研究发现调查数据严重低估了低收入家庭的转移收入，通过关联行政数据校正后，反贫困项目的减贫效果几乎翻倍，住房援助效果增至三倍，安全网漏洞显著缩小。
We examine the consequences of survey underreporting of transfer programs for prototypical analyses of low-income populations. We link administrative data for four transfer programs to the CPS to correct its severe understatement of transfer dollars received. Using survey data sharply understates the income of poor households, distorts our understanding of program targeting, and greatly understates the effects of anti-poverty programs. Using the combined data, the poverty-reducing effect of all programs together is nearly doubled. The effect of housing assistance is tripled. Correcting survey error often reduces the share of single mothers falling through the safety net by one-half or more.