Using State Administrative Data to Measure Program Performance

Peter Mueser, Kenneth Troske and Alexey Gorislavsky

No 702, Working Papers from Department of Economics, University of Missouri

Abstract: We use administrative data from Missouri to examine the sensitivity of earnings impact estimates for a job training program based on alternative nonexperimental methods. We consider regression adjustment, Mahalanobis distance matching, and various methods using propensity score matching, examining both cross-sectional estimates and difference-in-difference estimates. Specification tests suggest that the difference-in-difference estimator may provide a better measure of program impact. We find that propensity score matching is most effective, but the detailed implementation is not of critical importance. Our analyses demonstrate that existing data can be used to obtain useful estimates of program impact.

JEL-codes: C14 C21 C52 (search for similar items in EconPapers)
Pages: 75 pages
Date: 2007
New Economics Papers: this item is included in nep-ppm
Note: Updated from WP 05-20 (no longer available)
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Citations: View citations in EconPapers (76)

Published in Review of Economic and Statistics 2007

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Related works:
Journal Article: Using State Administrative Data to Measure Program Performance (2007)
Working Paper: Using State Administrative Data to Measure Program Performance (2003)
Working Paper: Using State Administrative Data to Measure Program Performance (2003)
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