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Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

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  • PERRON, Benoît

Abstract

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.

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File URL: http://hdl.handle.net/1866/468
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Bibliographic Info

Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 9901.

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Length: 56 pages
Date of creation: 1999
Date of revision:
Handle: RePEc:mtl:montde:9901

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Keywords: instrumental variables; weak instruments; local-to-zero analysis; LM tests; Wald tests; risk emium; exctations; semi-rametric models; kernels; neural networks;

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References

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  1. Charles R. Nelson & Richard Startz & Eric Zivot, 1996. "Valid Confidence Intervals and Inference in the Presence of Weak Instruments," Econometrics 9612002, EconWPA.
  2. Backus, David K. & Gregory, Allan W. & Zin, Stanley E., 1989. "Risk premiums in the term structure : Evidence from artificial economies," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 371-399, November.
  3. 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.).
  4. Froot, Kenneth A & Thaler, Richard H, 1990. "Foreign Exchange," Journal of Economic Perspectives, American Economic Association, vol. 4(3), pages 179-92, Summer.
  5. Richard Startz & Charles Nelson & Eric Zivot, 1999. "Improved Inference for the Instrumental Variable Estimator," Discussion Papers in Economics at the University of Washington 0039, Department of Economics at the University of Washington.
  6. DUFOUR, Jean-Marie & JASIAK, Joanna, 1998. "Finite-Sample Inference Methods for Simultaneous Equations and Models with Unobserved and Generated Regressors," Cahiers de recherche 9812, Universite de Montreal, Departement de sciences economiques.
  7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  8. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  9. 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.
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  12. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
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  14. 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.
  15. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
  16. In Choi & Peter C.B. Phillips, 1989. "Asymptotic and Finite Sample Distribution Theory for IV Estimators and Tests in Partially Identified Structural Equations," Cowles Foundation Discussion Papers 929, Cowles Foundation for Research in Economics, Yale University.
  17. David K. Backus & Allan W. Gregory, 1992. "Theoretical Relations Between Risk Premiums and Conditional Variances," Working Papers 92-18a, New York University, Leonard N. Stern School of Business, Department of Economics.
  18. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
  19. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February.
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  21. Pagan, Adrian & Ullah, Aman, 1988. "The Econometric Analysis of Models with Risk Terms," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 87-105, April.
  22. Phillips, P.C.B., 1989. "Partially Identified Econometric Models," Econometric Theory, Cambridge University Press, vol. 5(02), pages 181-240, August.
  23. Masry, Elias & Tjøstheim, Dag, 1995. "Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality," Econometric Theory, Cambridge University Press, vol. 11(02), pages 258-289, February.
  24. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
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  28. repec:cup:etheor:v:11:y:1995:i:3:p:560-96 is not listed on IDEAS
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Cited by:
  1. 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.
  2. DUFOUR, Jean-Marie, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," Cahiers de recherche 10-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.

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