Research Highlights

When surveys aren’t enough: evidence-based policy decisions require administrative data

Generally speaking, researchers have often relied on survey statistics gleaned from the Current Population Survey (CPS) to evaluate U.S. anti-poverty programs. But a recent Upjohn Institute working paper suggests that relying solely on survey data underestimates those programs’ true impact. The paper’s authors, Bruce Meyer and Nikolas Mittag, show that relying exclusively on CPS data overlooks up to 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients.

Meyer (University of Chicago) and Mittag (CERGE-EI, Charles University) are not alone in their push to incorporate administrative data with survey data in order to promote the practice of evidence-based policy making. Researchers at the Upjohn Institute have a tradition or using administrative data in program evaluations in order to help policymakers make better-informed decisions. (See "Net Impact and Benefit-Cost Estimates of the Workforce Development System in Washington State," by Kevin Hollenbeck and Wei-Jang Huang; and “Use of Unemployment Insurance and Public Employment Services after Leaving Welfare,” by Christopher J. O’Leary, for recent examples.) In addition, several other research organizations acknowledge the appeal of supplementing survey data with administrative data to produce more accurate evaluation results, including the Federal Reserve, the Brookings Institution, the Urban Institute, and IZA.

Acknowledging the value of using administrative data in creating better-informed policy decisions, Democratic Senator Patty Murray and Republican Representative (now House Speaker) Paul Ryan introduced the Evidence-Based Policymaking Commission Act of 2014. If enacted, this bi-partisan bill would create a 15-person commission charged with assessing the government’s current methods for collecting data on federal programs and spending through the tax code. The commission would then make recommendations for making this data more accessible for research purposes by creating a clearinghouse to house both survey and administrative data. Passed by the House, the bill is currently stalled in the Senate.

Read Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net, by Bruce D. Meyer and Nikolas Mittag.

Research Highlights

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            Contact: Justin Carinci