Finite sample evidence of IV estimators under weak instruments

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Finite sample evidence of IV estimators under weak instruments

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Alfonso Flores-Lagunes (Department of Economics, Eller College of Management, University of Arizona, Tucson, AZ, USA)

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Alfonso Flores-Lagunes

Abstract

We present finite sample evidence on different IV estimators available for linear models under weak instruments; explore the application of the bootstrap as a bias reduction technique to attenuate their finite sample bias; and employ three empirical applications to illustrate and provide insights into the relative performance of the estimators in practice. Our evidence indicates that the random-effects quasi-maximum likelihood estimator outperforms alternative estimators in terms of median point estimates and coverage rates, followed by the bootstrap bias-corrected version of LIML and LIML. However, our results also confirm the difficulty of obtaining reliable point estimates in models with weak identification and moderate-size samples. Copyright © 2007 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 22 (2007)
Issue (Month): 3 ()
Pages: 677-694
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Handle: RePEc:jae:japmet:v:22:y:2007:i:3:p:677-694

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James G. MacKinnon & Russell Davidson, 2006. "The case against JIVE," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 827-833. [Downloadable!]
Other versions:
- Russell Davidson & James G. MacKinnon, 2004. "The Case Against JIVE," Working Papers 1031, Queen's University, Department of Economics. [Downloadable!]
- Russell Davidson & James MacKinnon, 2006. "The Case Against Jive," Departmental Working Papers 2004-02, McGill University, Department of Economics. [Downloadable!]
Angrist, J D & Imbens, G W & Krueger, A B, 1999. "Jackknife Instrumental Variables Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 57-67, Jan.-Feb.. [Downloadable!]
Other versions:
- Joshua D. Angrist & Guido W. Imbens & Alan Krueger, 1995. "Jackknife Instrumental Variables Estimation," NBER Technical Working Papers 0172, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Donald W. K. Andrews & Moshe Buchinsky, 2000. "A Three-Step Method for Choosing the Number of Bootstrap Repetitions," Econometrica, Econometric Society, vol. 68(1), pages 23-52, January.
Nelson, Charles R & Startz, Richard, 1990. "The Distribution of the Instrumental Variables Estimator and Its t-Ratio When the Instrument Is a Poor One," Journal of Business, University of Chicago Press, vol. 63(1), pages S125-40, January. [Downloadable!] (restricted)
Other versions:
- Charles R. Nelson & Richard Startz, 1988. "The Distribution of the Instrumental Variables Estimator and Its t-RatioWhen the Instrument is a Poor One," NBER Technical Working Papers 0069, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
- Nelson, C. & Startz, R., 1988. "The Distribution Of The Instrumental Variables Estimator And Its T-Ratio When The Instrument Is A Poor One," Working Papers 88-07, University of Washington, Department of Economics.
- Nelson, C. & Startz, R., 1988. "The Distribution Of The Instrumental Variables Estimator And Its T-Ratio When The Instrument Is A Poor One," Discussion Papers in Economics at the University of Washington 88-07, Department of Economics at the University of Washington.
Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September. [Downloadable!] (restricted)
Blomquist, Soren, 1996. "Estimation methods for male labor supply functions How to take account of nonlinear taxes," Journal of Econometrics, Elsevier, vol. 70(2), pages 383-405, February. [Downloadable!] (restricted)
Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
Jiahui Wang & Eric Zivot, 1998. "Inference on Structural Parameters in Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 66(6), pages 1389-1404, November.
Jinyong Hahn & Jerry Hausman, 2003. "Weak Instruments: Diagnosis and Cures in Empirical Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 118-125, May. [Downloadable!]
Hahn, Jinyong & Hausman, Jerry, 2002. "Notes on bias in estimators for simultaneous equation models," Economics Letters, Elsevier, vol. 75(2), pages 237-241, April. [Downloadable!] (restricted)

Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

Sara Lemos, 2005. "Political Variables as Instruments for the Minimum Wage," The B.E. Journal of Economic Analysis & Policy, Berkeley Electronic Press, vol. 0(1). [Downloadable!]
Other versions:
- Sara Lemos, 2004. "Political Variables as Instruments for the Minimum Wage," Labor and Demography 0403010, EconWPA. [Downloadable!]
- Lemos, Sara, 2004. "Political Variables as Instruments for the Minimum Wage," IZA Discussion Papers 1136, Institute for the Study of Labor (IZA). [Downloadable!]
- Sara Lemos, 2003. "Political Variables as Instruments for the Minimum Wage," Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31th Brazilian Economics Meeting] f08, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics]. [Downloadable!]
- Sara lemos, 2004. "Political Variables as Instruments for the Minimum Wage," Discussion Papers in Economics 04/11, Department of Economics, University of Leicester. [Downloadable!]
Russell Davidson & James G. MacKinnon, 2008. "Wild Bootstrap Tests for IV Regression," Working Papers 1135, Queen's University, Department of Economics. [Downloadable!]
Other versions:
- Russell Davidson & James G. MacKinnon, 2007. "Wild Bootstrap Tests For Iv Regression," Departmental Working Papers 2007-14, McGill University, Department of Economics. [Downloadable!]

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