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Exactly Distribution-free Inference in Instrumental Variables Regression with Possibly Weak Instruments

This paper introduces a rank-based test for the instrumental variables regression model that dominates the Anderson-Rubin test in terms of finite sample size and asymptotic power in certain circumstances. The test has correct size for any distribution of the errors with weak or strong instruments. The test has noticeably higher power than the Anderson-Rubin test when the error distribution has thick tails and comparable power otherwise. Like the Anderson-Rubin test, the rank tests considered here perform best, relative to other available tests, in exactly-identified models.

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File URL: http://cowles.econ.yale.edu/P/cd/d15a/d1501.pdf
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Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1501.

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Length: 29 pages
Date of creation: Mar 2005
Date of revision:
Publication status: Published in Journal of Econometrics (2008), 42(1): 183-200
Handle: RePEc:cwl:cwldpp:1501
Note: CFP 1253.
Contact details of provider: Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/

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Order Information: Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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  1. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
  2. Joshua D. Angrist & Alan B. Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," NBER Working Papers 3572, National Bureau of Economic Research, Inc.
  3. Moreira, Marcelo J., 2009. "Tests with correct size when instruments can be arbitrarily weak," Journal of Econometrics, Elsevier, vol. 152(2), pages 131-140, October.
  4. Andrews, Donald W.K. & Soares, Gustavo, 2007. "Rank Tests For Instrumental Variables Regression With Weak Instruments," Econometric Theory, Cambridge University Press, vol. 23(06), pages 1033-1082, December.
  5. Esther Duflo, 2000. "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment," NBER Working Papers 7860, National Bureau of Economic Research, Inc.
  6. Dufour, Jean-Marie & Jasiak, Joann, 2001. "Finite Sample Limited Information Inference Methods for Structural Equations and Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(3), pages 815-43, August.
  7. Esther Duflo & Emmanuel Saez, 2003. "The Role Of Information And Social Interactions In Retirement Plan Decisions: Evidence From A Randomized Experiment," The Quarterly Journal of Economics, MIT Press, vol. 118(3), pages 815-842, August.
  8. Joshua Angrist & Eric Bettinger & Erik Bloom & Elizabeth King & Michael Kremer, 2001. "Vouchers for Private Schooling in Colombia: Evidence from a Randomized Natural Experiment," NBER Working Papers 8343, National Bureau of Economic Research, Inc.
  9. Donald W.K. Andrews & Marcelo J. Moreira & James H. Stock, 2004. "Optimal Invariant Similar Tests for Instrumental Variables Regression," Cowles Foundation Discussion Papers 1476, Cowles Foundation for Research in Economics, Yale University.
  10. Guido W. Imbens & Paul R. Rosenbaum, 2005. "Robust, accurate confidence intervals with a weak instrument: quarter of birth and education," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(1), pages 109-126.
  11. Greevy, Robert & Silber, Jeffrey H. & Cnaan, Avital & Rosenbaum, Paul R., 2004. "Randomization Inference With Imperfect Compliance in the ACE-Inhibitor After Anthracycline Randomized Trial," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 7-15, January.
  12. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  13. Joshua D. Angrist & William N. Evans, 1996. "Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size," NBER Working Papers 5778, National Bureau of Economic Research, Inc.
  14. Andrews, Donald W.K. & Marmer, Vadim, 2008. "Exactly distribution-free inference in instrumental variables regression with possibly weak instruments," Journal of Econometrics, Elsevier, vol. 142(1), pages 183-200, January.
  15. Levitt, Steven D, 1997. "Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on Crime," American Economic Review, American Economic Association, vol. 87(3), pages 270-90, June.
  16. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, 07.
  17. DUFOUR, Jean-Marie, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," Cahiers de recherche 10-2003, Centre interuniversitaire de recherche en ├ęconomie quantitative, CIREQ.
  18. Donald W. K. Andrews & Marcelo J. Moreira & James H. Stock, 2006. "Optimal Two-Sided Invariant Similar Tests for Instrumental Variables Regression," Econometrica, Econometric Society, vol. 74(3), pages 715-752, 05.
  19. McCabe, B. P. M., 1989. "Misspecification tests in econometrics based on ranks," Journal of Econometrics, Elsevier, vol. 40(2), pages 261-278, February.
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