IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Using State Administrative Data to Measure Program Performance

This paper uses administrative data from Missouri to examine the sensitivity of job training program impact estimates based on alternative nonexperimental methods. In addition to simple regression adjustment, we consider Mahalanobis distance matching and a variety of methods using propensity score matching. In each case, we consider estimates based on levels of post-program earnings as well as difference-in-difference estimates based on comparison of pre and post-program earnings. Specification tests suggest that the difference-in-difference estimator may provide a better measure of program impact. We find that propensity score matching is generally most effective, but the detailed implementation of the method is not of critical importance. Our analyses demonstrate that existing data available at the state level can be used to obtain useful estimates of program impact.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: https://economics.missouri.edu/working-papers/2003/wp0309_mueser.pdf
Download Restriction: no

Paper provided by Department of Economics, University of Missouri in its series Working Papers with number 0309.

as
in new window

Length: 15 pgs.
Date of creation: 20 May 2003
Date of revision:
Handle: RePEc:umc:wpaper:0309
Note: Paper updated as WP 05-20
Contact details of provider: Postal:
118 Professional Building, Columbia, MO 65211

Phone: (573) 882-0063
Fax: (573) 882-2697
Web page: http://economics.missouri.edu/

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Heckman, James J & Smith, Jeffrey A, 1999. "The Pre-programme Earnings Dip and the Determinants of Participation in a Social Programme. Implications for Simple Programme Evaluation Strategies," Economic Journal, Royal Economic Society, vol. 109(457), pages 313-48, July.
  2. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
  3. Ben B. Hansen, 2004. "Full Matching in an Observational Study of Coaching for the SAT," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 609-618, January.
  4. Orley Ashenfelter & David Card, 1984. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," NBER Working Papers 1489, National Bureau of Economic Research, Inc.
  5. Card, David & Sullivan, Daniel G, 1988. "Measuring the Effect of Subsidized Training Programs on Movements in and out of Employment," Econometrica, Econometric Society, vol. 56(3), pages 497-530, May.
  6. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20035, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
  7. Dan A. Black & Jeffrey Smith, 2003. "How Robust is the Evidence on the Effects of College Quality? Evidence From Matching," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20033, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
  8. Charles F. Manski, 1996. "Learning about Treatment Effects from Experiments with Random Assignment of Treatments," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 709-733.
  9. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
  10. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  11. Markus Frölich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
  12. Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
  13. Guido W. Imbens, 2003. "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," NBER Technical Working Papers 0294, National Bureau of Economic Research, Inc.
  14. Imbens, Guido & Abadie, Alberto, 2008. "On the Failure of the Bootstrap for Matching Estimators," Scholarly Articles 3043415, Harvard University Department of Economics.
  15. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
  16. Burt S. Barnow, 1987. "The Impact of CETA Programs on Earnings: A Review of the Literature," Journal of Human Resources, University of Wisconsin Press, vol. 22(2), pages 157-193.
  17. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2006. "Evaluating the Differential Effects of Alternative Welfare-to-Work Training Components: A Re-Analysis of the California GAIN Program," NBER Working Papers 11939, National Bureau of Economic Research, Inc.
  18. Lorraine Dearden & Javier Ferri & Costas Meghir, 1998. "The effect of school quality on educational attainment and wages," IFS Working Papers W98/03, Institute for Fiscal Studies.
  19. Dyke, Andrew & Heinrich, Carolyn J. & Mueser, Peter R. & Troske, Kenneth, 2005. "The Effects of Welfare-to-Work Program Activities on Labor Market Outcomes," IZA Discussion Papers 1520, Institute for the Study of Labor (IZA).
  20. Bassi, Laurie J, 1984. "Estimating the Effect of Training Programs with Non-Random Selection," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 36-43, February.
  21. James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000. "Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 115(2), pages 651-694.
  22. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
  23. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  24. Friedlander, Daniel & Robins, Philip K, 1995. "Evaluating Program Evaluations: New Evidence on Commonly Used Nonexperimental Methods," American Economic Review, American Economic Association, vol. 85(4), pages 923-37, September.
  25. 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.
  26. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc.
  27. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
  28. Joshua D. Angrist & Jinyong Hahn, 1999. "When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects," NBER Technical Working Papers 0241, National Bureau of Economic Research, Inc.
  29. James J. Heckman, 1989. "Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," NBER Working Papers 2861, National Bureau of Economic Research, Inc.
  30. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
  31. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
  32. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:umc:wpaper:0309. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Valerie Kulp)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.