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Nonparametric Instrumental Regression

  • S. Darolles
  • Y. Fan
  • J. P. Florens
  • E. Renault

The focus of this paper is the nonparametric estimation of an instrumental regression function f defined by conditional moment restrictions that stem from a structural econometric model E[Y − f (Z) | W] = 0, and involve endogenous variables Y and Z and instruments W. The function f is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyzes identification and overidentification of this model, and presents asymptotic properties of the estimated nonparametric instrumental regression function.

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Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 79 (2011)
Issue (Month): 5 (09)
Pages: 1541-1565

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Handle: RePEc:ecm:emetrp:v:79:y:2011:i:5:p:1541-1565
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  1. Jean-Pierre Florens & James Heckman & Costas Meghir & Edward Vytlacil, 2002. "Instrumental variables, local instrumental variables and control functions," CeMMAP working papers CWP15/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  2. Florens, J.P. & Mouchart, M. & Rolin, J.M., 1993. "Noncausality and Marginalization of Markov Processes," Econometric Theory, Cambridge University Press, vol. 9(02), pages 241-262, April.
  3. Peter Hall & Joel L. Horowitz, 2003. "Nonparametric methods for inference in the presence of instrumental variables," CeMMAP working papers CWP02/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin.
  5. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
  6. Xiaohong Chen & Xiaotong Shen, 1998. "Sieve Extremum Estimates for Weakly Dependent Data," Econometrica, Econometric Society, vol. 66(2), pages 289-314, March.
  7. Carrasco, Marine & Florens, Jean-Pierre, 2002. "Spectral Method for Deconvolving a Density," IDEI Working Papers 138, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2009.
  8. Amemiya, Takeshi, 1975. "The nonlinear limited-information maximum- likelihood estimator and the modified nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 3(4), pages 375-386, November.
  9. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  10. Guido W. Imbens & Whitney K. Newey, 2002. "Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity," NBER Technical Working Papers 0285, National Bureau of Economic Research, Inc.
  11. Härdle, W.K., 1992. "Applied Nonparametric Methods," Discussion Paper 1992-6, Tilburg University, Center for Economic Research.
  12. Darolles, Serge & Florens, Jean-Pierre & Gouriéroux, Christian, 1999. "Kernel Based Nonlinear Canonical Analysis," IDEI Working Papers 83, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2001.
  13. Whitney K. Newey & James L. Powell & Francis Vella, 1998. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Working papers 98-6, Massachusetts Institute of Technology (MIT), Department of Economics.
  14. Xiaohong Chen & Lars Peter Hansen & Jose A. Scheinkman, 2009. "Principal components and the long run," CeMMAP working papers CWP07/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  15. Adrian Pagan, 1985. "Two Stage and Related Estimators and Their Applications," Cowles Foundation Discussion Papers 741, Cowles Foundation for Research in Economics, Yale University.
  16. Jean-Pierre FLORENS & Michel MOUCHARD & Jean-François RICHARD, 1987. "Dynamic Error-in-Variable Models and Limited Information Analysis," Annales d'Economie et de Statistique, ENSAE, issue 6-7, pages 289-310.
  17. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc.
  18. 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.
  19. Marine Carrasco & Jean-Pierre Florens, 2000. "Efficient GMM Estimation Using the Empirical Characteristic Function," Working Papers 2000-33, Centre de Recherche en Economie et Statistique.
  20. repec:fth:inseep:9855 is not listed on IDEAS
  21. Florens, J. -P. & Mouchart, M. & Richard, J. -F., 1974. "Bayesian inference in error-in-variables models," Journal of Multivariate Analysis, Elsevier, vol. 4(4), pages 419-452, December.
  22. Richard Blundell & James Powell, 2001. "Endogeneity in nonparametric and semiparametric regression models," CeMMAP working papers CWP09/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  23. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  24. Carrasco, Marine & Florens, Jean-Pierre, 2000. "Generalization Of Gmm To A Continuum Of Moment Conditions," Econometric Theory, Cambridge University Press, vol. 16(06), pages 797-834, December.
  25. repec:fth:inseep:2000-33 is not listed on IDEAS
  26. Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July.
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