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Sensitivity Testing of Net Impact Estimates of Workforce Development Programs Using Administrative Data

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Abstract

This paper addresses the question of whether administrative data sources, such as performance monitoring data, can be used for program evaluation purposes. It argues that under certain circumstances, such data can be used. In particular, program performance data that are routinely gathered and monitored by administrators of many workforce development programs meet these circumstances. The paper goes on to demonstrate the point by using administrative data from the state of Washington to examine the net impact on earnings and employment of services provided to adults under the Workforce Investment Act (WIA).Because of a lack of consensus about appropriate net impact estimators, the strategy of this paper is to examine the sensitivity of the results to various estimation techniques. The paper describes the various estimation techniques, and it summarizes the net impact estimates that are generated for the State of Washington. For the most part, the results are fairly stable across the techniques, which the paper argues adds a degree of confidence in them. The final section of the paper offers guidance to policymakers and program administrators who may not be familiar with the technical details of various analytical approaches about how empirical results that may appear to be complex or unstable can be used for program improvement.

Suggested Citation

  • Kevin Hollenbeck, 2008. "Sensitivity Testing of Net Impact Estimates of Workforce Development Programs Using Administrative Data," Upjohn Working Papers 08-139, W.E. Upjohn Institute for Employment Research.
  • Handle: RePEc:upj:weupjo:08-139
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    References listed on IDEAS

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    1. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    2. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    3. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    4. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    5. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    6. Kevin Hollenbeck, 2003. "Net Impact Estimates of the Workforce Development System in Washington State," Upjohn Working Papers 03-92, W.E. Upjohn Institute for Employment Research.
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    Cited by:

    1. Christopher J. O'Leary & Randall W. Eberts, 2009. "Employment and Training Policy in the United States during the Economic Crisis," Upjohn Working Papers 10-161, W.E. Upjohn Institute for Employment Research.

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    More about this item

    Keywords

    incumbant; worker; on-the-job training; ojt; hollenbeck;
    All these keywords.

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J48 - Labor and Demographic Economics - - Particular Labor Markets - - - Particular Labor Markets; Public Policy
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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