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Do Estimated Impacts on Earnings Depend on the Source of the Data Used to Measure Them? Evidence From Previous Social Experiments

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  • Burt S. Barnow
  • David Greenberg

Abstract

Background: Impact evaluations draw their data from two sources, namely, surveys conducted for the evaluation or administrative data collected for other purposes. Both types of data have been used in impact evaluations of social programs. Objective: This study analyzes the causes of differences in impact estimates when survey data and administrative data are used to evaluate earnings impacts in social experiments and discusses the differences observed in eight evaluations of social experiments that used both survey and administrative data. Results: There are important trade-offs between the two data sources. Administrative data are less expensive but may not cover all income and may not cover the time period desired, while surveys can be designed to avoid these problems. We note that errors can be due to nonresponse or reporting, and errors can be balanced between the treatment and the control groups or unbalanced. We find that earnings are usually higher in survey data than in administrative data due to differences in coverage and likely overreporting of overtime hours and pay in survey data. Evaluations using survey data usually find greater impacts, sometimes much greater. Conclusions: The much lower cost of administrative data make their use attractive, but they are still subject to underreporting and other problems. We recommend further evaluations using both types of data with investigative audits to better understand the sources and magnitudes of errors in both survey and administrative data so that appropriate corrections to the data can be made.

Suggested Citation

  • Burt S. Barnow & David Greenberg, 2015. "Do Estimated Impacts on Earnings Depend on the Source of the Data Used to Measure Them? Evidence From Previous Social Experiments," Evaluation Review, , vol. 39(2), pages 179-228, April.
  • Handle: RePEc:sae:evarev:v:39:y:2015:i:2:p:179-228
    DOI: 10.1177/0193841X14564154
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    3. Quinn Moore & Irma Perez-Johnson & Robert Santillano, 2018. "Decomposing Differences in Impacts on Survey- and Administrative-Measured Earnings From a Job Training Voucher Experiment," Evaluation Review, , vol. 42(5-6), pages 515-549, October.
    4. Andersson, Fredrik W. & Holzer, Harry J. & Lane, Julia & Rosenblum, David & Smith, Jeffrey A., 2013. "Does Federally-Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts Using Longitudinal Data on Workers and Firms," IZA Discussion Papers 7621, Institute of Labor Economics (IZA).
    5. Kaitlin Anderson & Gema Zamarro & Jennifer Steele & Trey Miller, 2021. "Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations," Evaluation Review, , vol. 45(1-2), pages 70-104, February.
    6. Burt S. Barnow & Jeffrey Smith, 2015. "Employment and Training Programs," NBER Chapters, in: Economics of Means-Tested Transfer Programs in the United States, Volume 2, pages 127-234, National Bureau of Economic Research, Inc.
    7. Judith Scott-Clayton & Qiao Wen, 2019. "Estimating Returns to College Attainment: Comparing Survey and State Administrative Data–Based Estimates," Evaluation Review, , vol. 43(5), pages 266-306, October.
    8. Annalisa Mastri & Dana Rotz & Elias S. Hanno, "undated". "Comparing Job Training Impact Estimates Using Survey and Administrative Data," Mathematica Policy Research Reports 157778d936f848ddb0b4e8e32, Mathematica Policy Research.
    9. Reuben Ford & Douwêrê Grékou & Isaac Kwakye & Taylor Shek-wai Hui, 2018. "The Sensitivity of Impact Estimates to Data Sources Used: Analysis From an Access to Postsecondary Education Experiment," Evaluation Review, , vol. 42(5-6), pages 575-615, October.
    10. Sheena McConnell & Peter Z. Schochet & Dana Rotz & Ken Fortson & Paul Burkander & Annalisa Mastri, 2021. "The Effects of Employment Counseling on Labor Market Outcomes for Adults and Dislocated Workers: Evidence from a Nationally Representative Experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(4), pages 1249-1287, September.

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