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Identification and Estimation of Triangular Simultaneous Equations Models without Additivity

  • Whitney Newey
  • Guido Imbens

This paper is about identification and estimation in a triangular nonparametric structural model with instrumental variables and non-additive errors. Identification and estimation is based on a control function consisting of the conditional distribution function of the endogenous variable given the instruments. We allow for a structural disturbance of arbitrary, unknown dimension while identifying interesting structural effects, such as quantile and average effects. We consider a two-step approach to estimation. We find that the convergence rate for the second-step structural estimator depends on the strength of the instrument.

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Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 594.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:594
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  1. Darolles, Serge & Fan, Yanqin & Florens, Jean-Pierre & Renault, Eric, 2003. "Non Parametric Instrumental Regression," IDEI Working Papers 228, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2010.
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  6. Milgrom, Paul & Shannon, Chris, 1994. "Monotone Comparative Statics," Econometrica, Econometric Society, vol. 62(1), pages 157-80, January.
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  8. Angrist, Joshua D & Graddy, Kathryn & Imbens, Guido W, 2000. "The Interpretation of Instrumental Variables Estimators in Simultaneous Equations Models with an Application to the Demand for Fish," Review of Economic Studies, Wiley Blackwell, vol. 67(3), pages 499-527, July.
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  19. Susan Athey & Scott Stern, 1998. "An Empirical Framework for Testing Theories About Complimentarity in Organizational Design," NBER Working Papers 6600, National Bureau of Economic Research, Inc.
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  23. Benkard, C. Lanier & Bajari, Patrick, 2001. "Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach," Research Papers 1691, Stanford University, Graduate School of Business.
  24. J.D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
  25. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-30, November.
  26. Chamberlain, Gary, 1986. "Asymptotic efficiency in semi-parametric models with censoring," Journal of Econometrics, Elsevier, vol. 32(2), pages 189-218, July.
  27. Andrew Chesher, 2002. "Local identification in nonseparable models," CeMMAP working papers CWP05/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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  29. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
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  31. 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.
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  33. Mitali Das, 2000. "Instrumental Variables Estimation of Nonparametric Models with Discrete Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1008, Econometric Society.
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