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Another Look at the Identification at Infinity of Sample Selection Models

  • Arnaud Maurel
  • Xavier D'Haultfoeuille

It is often believed that without instrument, endogenous sample selection models are identified only if a covariate with a large support is available (see, e.g., Chamberlain, 1986, and Lewbel, 2007). We propose a new identification strategy mainly based on the condition that the selection variable becomes independent of the covariates for large values of the outcome. No large support on the covariates is required. Moreover, we prove that this condition is testable. We finally show that our strategy can be applied to the identification of generalized Roy models.

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Paper provided by Duke University, Department of Economics in its series Working Papers with number 11-11.

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Length: 15
Date of creation: 2011
Date of revision:
Handle: RePEc:duk:dukeec:11-11
Contact details of provider: Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
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Web page: http://econ.duke.edu/

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  1. Arthur Lewbel, 2000. "Endogenous Selection Or Treatment Model Estimation," Boston College Working Papers in Economics 462, Boston College Department of Economics, revised 13 Jun 2007.
  2. Carneiro, Pedro & Hansen, Karsten & Heckman, James, 2003. "Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice," Working Paper Series 2003:9, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  3. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
  4. Robert J. Willis & Sherwin Rosen, 1978. "Education and Self-Selection," NBER Working Papers 0249, National Bureau of Economic Research, Inc.
  5. Patrick Bayer & Shakeeb Khan & Christopher Timmins, 2008. "Nonparametric Identification and Estimation in a Generalized Roy Model," NBER Working Papers 13949, National Bureau of Economic Research, Inc.
  6. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Technical Working Papers 0306, National Bureau of Economic Research, Inc.
  7. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
  8. John K. Dagsvik & Steinar Strøm, 2004. "Sectoral Labor Supply, Choice Restrictions and Functional Form," Discussion Papers 388, Research Department of Statistics Norway.
  9. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The identifiability of the mixed proportional hazards competing risks model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 701-710.
  10. Chamberlain, Gary, 1986. "Asymptotic efficiency in semi-parametric models with censoring," Journal of Econometrics, Elsevier, vol. 32(2), pages 189-218, July.
  11. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-94, July.
  12. Andrews, Donald W K & Schafgans, Marcia M A, 1998. "Semiparametric Estimation of the Intercept of a Sample Selection Model," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 497-517, July.
  13. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-49, September.
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