Background: The high costs of implementing surveys are increasingly leading research teams to either cut back on surveys or to rely on administrative records. Yet no policy should be based on a single set of estimates, and every approach has its weaknesses. A mixture of approaches, each with its own biases, should provide the analyst with a better understanding of the underlying phenomenon. This claim is illustrated with a comparison of employment effect estimates of two conditional cash transfer programs in New York City using survey and administrative unemployment insurance (UI) data. Objectives: This article explores whether using administrative data and survey data produce different impact estimates and investigates the source of differential effects between data sources. Research design: The results of a survey nonresponse bias analysis and an analysis of characteristics of non-UI-covered job characteristics using data collected on 6,000 families who enrolled in either the Family Rewards or Work Rewards evaluation are presented. Results: In both evaluations, survey data showed positive employment effects, while administrative data showed no statistically significant employment effects. Family Rewards increased employment mostly in non-UI-covered jobs, while the positive survey impact estimates in Work Rewards were partially due to survey nonresponse bias. Conclusions: Despite cost pressures leading researchers to collect and analyze only administrative records, the results suggest that survey and administrative records data both suffer from different kinds of sample attrition, and researchers may need to triangulate data sources to draw accurate conclusions about program effects. Developing more economical data collection practices is a major priority.

中文翻译：

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在政策评估中使用多个数据源的重要性：纽约市两个有条件现金转移计划的经验教训。

背景：实施调查的高昂成本越来越导致研究团队减少调查或依靠行政记录。但是，任何政策都不能基于一组估计，每种方法都有其缺点。每种方法都有其自身的偏见，应使分析人员对潜在现象有更好的了解。通过使用调查和行政失业保险（UI）数据对纽约市两个有条件现金转移计划的就业效果估计值进行比较，来说明此索赔。目标：本文探讨使用行政数据和调查数据是否会产生不同的影响估计，并调查数据源之间差异影响的来源。研究设计：呈现了调查无应答偏差分析的结果，以及使用收集的关于6,000个参加家庭奖励或工作奖励评估的家庭的数据对未UI覆盖的工作特征进行分析的结果。结果：在两项评估中，调查数据均显示出积极的就业影响，而行政数据显示无统计学意义的就业影响。家庭奖励计划增加了就业机会，主要是在非用户界面覆盖的工作中，而工作奖励计划中积极的调查影响估计部分归因于调查的无回应偏差。结论：尽管成本压力导致研究人员只能收集和分析行政记录，但结果表明，调查和行政记录数据均遭受不同类型的样本损耗，研究人员可能需要对数据源进行三角剖分，以得出有关程序效果的准确结论。开发更经济的数据收集方法是主要优先事项。