Background: Differences in earnings measured using either survey or administrative data raise the question of which is preferred for program impact evaluations. This is especially true when the population of interest has varying propensities to be represented in either source. Objectives: We aim to study differences in impacts on earnings from a job training voucher experiment in order to demonstrate which source is most appropriate to interpret findings. Research design: Using study participants with survey-reported earnings, we decompose mean earnings differences across sources into those resulting from (1) differences in reported employment and (2) differences in reported earnings for those who are employed in both sources. We study factors related to these two sources of differences and demonstrate how impact estimates change when adjusting for them. Results: We find that differences in mean earnings are driven by differences in reported employment, but that differences in impacts are driven by differences in reported earnings for those employed in both data sources. Employment and worker characteristics explain much of the research group differences in earnings among the employed. Out-of-state employment, self-employment, and employment in low unemployment insurance (UI) coverage occupations contribute importantly to research group differences in survey- and UI-based employment levels. Employment in more than one job contributes to treatment group differences in earnings among the employed. All of these factors contribute substantially to the difference between survey- and UI-based earnings impact estimates. Conclusion: Findings underscore the relevance of UI coverage to estimated earnings impacts and suggest assessing employment impacts using both UI- and survey-based measures.

中文翻译：

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从工作培训券实验中分解对调查和行政测量收入的影响差异。

背景：使用调查或行政数据衡量的收入差异提出了一个问题，即计划影响评估应优先考虑哪个问题。当感兴趣的人群具有在任一来源中表示的不同倾向时，尤其如此。目标：我们的目的是研究工作培训券实验对收入的影响差异，以证明哪种来源最适合解释调查结果。研究设计：使用研究参与者的调查报告的收入，我们将不同来源的平均收入差异分解为（1）报告的就业差异和（2）两个来源的受雇者的报告收入差异所导致的收入差异。我们研究了与这两个差异来源有关的因素，并说明了影响估计在进行调整时如何变化。结果：我们发现，平均收入的差异是由报告的就业差异驱动的，而影响的差异是由两种数据来源的受雇人员的报告收入的差异驱动的。就业和工人特征解释了许多研究小组在受雇者之间的收入差异。州外就业，自雇和低失业保险（UI）覆盖职业的就业对研究组基于调查和基于UI的就业水平的差异做出了重要贡献。从事一项以上工作会导致治疗组的就业者收入差异。所有这些因素在很大程度上造成了基于调查和基于用户界面的收益影响估计之间的差异。结论：研究结果强调了用户界面覆盖率与估计的收入影响的相关性，并建议使用基于用户界面和基于调查的方法来评估就业影响。