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Valid Confidence Intervals and Inference in the Presence of Weak Instruments

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Author Info

  • Charles R. Nelson

    (The University of Washington)

  • Richard Startz

    (The University of Washington)

  • Eric Zivot

    (The University of Washington)

Abstract

We investigate confidence intervals and inference for the instrumental variables model with weak instruments. Wald-based confidence intervals perform poorly in that the probability they reject the null is far greater than their nominal size. In the worst case, Wald-based confidence intervals always exclude the true paremeter value. Confidence intervals based on the LM, LR, and Anderson-Rubin statistics perform far better than the Wald. The Anderson-Rubin statistic always has the correct size, but LM and LR statistics have somewhat greater power. Performance of the LM and LR statistics is improved by a degrees-of- freedom correction in the overidentified ccase. We show that the practice of "pre-testing" by looking at the significance of the first - stage regression leads to extremely poor results when the instruments are very weak.

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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 9612002.

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Length: 49 pages
Date of creation: 02 Dec 1996
Date of revision:
Handle: RePEc:wpa:wuwpem:9612002

Note: Type of Document - Adobe .pdf file; prepared on Mac; pages: 49; figures: 8, included in paper
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Web page: http://128.118.178.162

Related research

Keywords: confidence intervals; instrumental variables; pre-testing; weak instruments;

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References

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  1. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-76, July.
  2. Bowden,Roger J. & Turkington,Darrell A., 1990. "Instrumental Variables," Cambridge Books, Cambridge University Press, number 9780521385824, October.
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  4. Maddala, G S, 1974. "Some Small Sample Evidence on Tests of Significance in Simultaneous Equations Models," Econometrica, Econometric Society, vol. 42(5), pages 841-51, September.
  5. Dufour, J.M., 1995. "Some Impossibility Theorems in Econometrics with Applications to Instrumental Variables, Dynamic Models and Cointegration," Cahiers de recherche 9539, Universite de Montreal, Departement de sciences economiques.
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  8. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income, and Interest Rates: Reinterpreting the Time Series Evidence," NBER Working Papers 2924, National Bureau of Economic Research, Inc.
  9. Alastair R. Hall & Glenn D. Rudebusch & David W. Wilcox, 1994. "Judging instrument relevance in instrumental variables estimation," Finance and Economics Discussion Series 94-3, Board of Governors of the Federal Reserve System (U.S.).
  10. Fuhrer, Jeffrey C. & Moore, George R. & Schuh, Scott D., 1995. "Estimating the linear-quadratic inventory model Maximum likelihood versus generalized method of moments," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 115-157, February.
  11. Peter C.B. Phillips, 1982. "Exact Small Sample Theory in the Simultaneous Equations Model," Cowles Foundation Discussion Papers 621, Cowles Foundation for Research in Economics, Yale University.
  12. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-87, October.
  13. Rotemberg, Julio J, 1984. "Interpreting the Statistical Failures of Some Rational Expectations Macroeconomic Models," American Economic Review, American Economic Association, vol. 74(2), pages 188-93, May.
  14. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  15. D. Klepinger & S. Lundberg & R. Plotnick, . "Instrument selection: The case of teenage childbearing and women's educational attainment," Institute for Research on Poverty Discussion Papers 1077-95, University of Wisconsin Institute for Research on Poverty.
  16. Jiahui Wang & Eric Zivot, 1996. "Inference on a Structural Parameter in Instrumental Variables Regression with Weak Instruments," Econometrics 9610005, EconWPA.
  17. repec:att:wimass:9312 is not listed on IDEAS
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