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The performance of sample selection estimators to control for attrition bias

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Author Info
Astrid Grasdal (Department of Economics, University of Bergen, Bergen, Norway)
Abstract

Sample attrition is a potential source of selection bias in experimental, as well as non-experimental programme evaluation. For labour market outcomes, such as employment status and earnings, missing data problems caused by attrition can be circumvented by the collection of follow-up data from administrative registers. For most non-labour market outcomes, however, investigators must rely on participants' willingness to co-operate in keeping detailed follow-up records and statistical correction procedures to identify and adjust for attrition bias. This paper combines survey and register data from a Norwegian randomized field trial to evaluate the performance of parametric and semi-parametric sample selection estimators commonly used to correct for attrition bias. The considered estimators work well in terms of producing point estimates of treatment effects close to the experimental benchmark estimates. Results are sensitive to exclusion restrictions. The analysis also demonstrates an inherent paradox in the 'common support' approach, which prescribes exclusion from the analysis of observations outside of common support for the selection probability. The more important treatment status is as a determinant of attrition, the larger is the proportion of treated with support for the selection probability outside the range, for which comparison with untreated counterparts is possible. Copyright © 2001 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.628
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 10 (2001)
Issue (Month): 5 ()
Pages: 385-398
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Handle: RePEc:wly:hlthec:v:10:y:2001:i:5:p:385-398

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  1. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-73, March. [Downloadable!] (restricted)
  2. Bratberg, E. & Grasdal, A. & Risa, A.E., 2000. "Evaluating Social Policy by Experimental and Nonexperimental Methods," Norway; Department of Economics, University of Bergen 1700, Department of Economics, University of Bergen.
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  3. Newey, Whitney K., 1999. "Consistency of two-step sample selection estimators despite misspecification of distribution," Economics Letters, Elsevier, vol. 63(2), pages 129-132, May. [Downloadable!] (restricted)
  4. Ahn, Hyungtaik & Powell, James L., 1993. "Semiparametric estimation of censored selection models with a nonparametric selection mechanism," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 3-29, July. [Downloadable!] (restricted)
  5. Newey, Whitney K & Powell, James L & Walker, James R, 1990. "Semiparametric Estimation of Selection Models: Some Empirical Results," American Economic Review, American Economic Association, vol. 80(2), pages 324-28, May. [Downloadable!] (restricted)
  6. Lee, Lung-Fei, 1984. "Tests for the Bivariate Normal Distribution in Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 52(4), pages 843-63, July. [Downloadable!] (restricted)
  7. 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. [Downloadable!] (restricted)
  8. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  9. Heckman, James J & Smith, Jeffrey A, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring. [Downloadable!] (restricted)
  10. 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.
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  11. 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. [Downloadable!] (restricted)
  12. Dolton, Peter & O'Neill, Donal, 1996. "Unemployment Duration and the Restart Effect: Some Experimental Evidence," Economic Journal, Royal Economic Society, vol. 106(435), pages 387-400, March. [Downloadable!] (restricted)
  13. Chesher, Andrew & Irish, Margaret, 1987. "Residual analysis in the grouped and censored normal linear model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 33-61. [Downloadable!] (restricted)
  14. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May. [Downloadable!] (restricted)
  15. repec:att:wimass:19901 is not listed on IDEAS
  16. Burtless, Gary, 1995. "The Case for Randomized Field Trials in Economic and Policy Research," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 63-84, Spring. [Downloadable!] (restricted)
  17. Pagan, Adrian & Vella, Frank, 1989. "Diagnostic Tests for Models Based on Individual Data: A Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages S29-59, Supplemen. [Downloadable!] (restricted)
  18. 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. [Downloadable!] (restricted)
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  19. Tomas Philipson & Larry V. Hedges, 1998. "Subject Evaluation in Social Experiments," Econometrica, Econometric Society, vol. 66(2), pages 381-408, March.
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