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Improved Inference for the Instrumental Variable Estimator

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  • Richard Startz
  • Charles Nelson
  • Eric Zivot

Abstract

It is now well known that standard asymptotic inference techniques for instrumental variable estimation perform very poorly in the presence of weak instruments. Specifically, standard asymptotic techniques give spuriously small standard errors, leading investigators to accept apparently tight confidence regions which unfortunately may be very far from the true parameter of interest. We present an improved technique for inference on structural parameters based on reduced form estimates. The "S-statistic" produces confidence regions based on a joint test of the structural hypothesis and the identification condition. The S- statistic converges to the standard asymptotic Wald statistic as identification becomes certain, has much better size properties when the instruments are weak, and may be inverted in closed form to conveniently compute confidence regions. In addition to providing improved inference for instrumental variable estimation, the technique suggested here may be useful in other applications where weak identification is important.

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Bibliographic Info

Paper provided by Department of Economics at the University of Washington in its series Discussion Papers in Economics at the University of Washington with number 0039.

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Date of creation: May 1999
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Handle: RePEc:fth:washer:0039

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References

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  1. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
  2. Zivot, E & Startz, R & Nelson, C-R, 1997. "Valid Confidence Intervals and Inference in the Presence of Weak Instruments," Working Papers 97-17, University of Washington, Department of Economics.
  3. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
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Citations

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Cited by:
  1. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
  2. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
  3. Benoit Perron, 2000. "Semi-Parametric Weak Instrument Regressions with an Application to the Risk-return Trade-off," Econometric Society World Congress 2000 Contributed Papers 1576, Econometric Society.
  4. Dufour, J.M., 2001. "Logique et tests d'hypotheses: reflexions sur les problemes mal poses en econometrie," Cahiers de recherche 2001-15, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  5. Paul A. Bekker & Jan van der Ploeg, 2000. "Instrumental Variable Estimation Based on Grouped Data," Econometric Society World Congress 2000 Contributed Papers 1862, Econometric Society.
  6. Frank Kleibergen & Eric Zivot, 1998. "Bayesian and Classical Approaches to Instrumental Variables Regression," Econometrics 9812002, EconWPA.
  7. D. S. Poskitt & C. L. Skeels, 2005. "Small Concentration Asymptotics and Instrumental Variables Inference," Monash Econometrics and Business Statistics Working Papers 4/05, Monash University, Department of Econometrics and Business Statistics.
  8. Dollar, David & Kraay, Aart, 2003. "Institutions, trade, and growth : revisiting the evidence," Policy Research Working Paper Series 3004, The World Bank.
  9. D.S. Poskitt & C.L. Skeels, 2002. "Assessing Instrumental Variable Relevance:An Alternative Measure and Some Exact Finite Sample Theory," Department of Economics - Working Papers Series 862, The University of Melbourne.
  10. Dufour, Jean-Marie, 2001. "Logique et tests d’hypothèses," L'Actualité Economique, Société Canadienne de Science Economique, vol. 77(2), pages 171-190, juin.

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