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A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics

Year 2011, Volume: 3 Issue: 2, 13 - 21, 01.12.2011

Mehmet Caner

https://izlik.org/JA23RD22RU

Abstract

We propose a pretest, bootstrap Kolmogorov-Smirnov test, to differentiate between weak and nearly-weak asymptotics. This is based on bootstrapping Wald Continuous Updating Estimator (CUE) based test. Since Wald CUE test has different limits under weak and nearly-weak cases this can be used in a pretest. We also conduct some simulations and show that some of the asset pricing models conform to nearly-weak asymptotics.

Keywords

Bootstrap Kolmogorov-Smirnov Test

References

  • Anderson, T.W. and H. Rubin (1949). Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations. Annals of Mathematical Statistics, 20, 46-63.
  • Andrews, D.W.K. (1994). Empirical Process Methods in Econometrics. Handbook of Econometrics, 4, 2247-2294.
  • Antoine, B. and E. Renault (2007). Efficient GMM with nearly-weak identification. Working paper. Department of Economics, University of North Carolina-Chapel Hill.
  • Caner, M. (2010). Testing, Estimation in GMM and CUE with Nearly-Weak IdentiŞcation. Econometric Reviews, 29, 330-363.
  • Hahn, J. and G. Kuersteiner (2002). Discontinuities of Weak Instrument Limiting Distributions. Economics Letters, 75, 325-331.
  • Hall, P. and J.L. Horowitz (1996). Bootstrap critical values for tests based on generalized method of moments estimators. Econometrica, 64, 891-916.
  • Hansen, L.P., J. Heaton and A. Yaron (1996). Finite Sample Properties of Some Alternative GMM Estimators. Journal of Business and Economic Statistics, 14, 262-280.
  • Kleibergen, F. (2005). Testing Parameters in GMM Without Assuming That They Are IdentiŞed. Econometrica, 73, 1103-1124.
  • Mood, A.M., F.A. Graybill and D.C. Boes (1974). Introduction to the Theory of Statistics. New-York: Mc-Graw Hill.
  • Phillips, P.C.B. and J.Y. Park (1988). On the Formulation of Wald Tests of Nonlinear Restrictions. Econometrica, 56, 1065-1083.
  • Stock, J.H. and J.H. Wright (2000). GMM with Weak Identification. Econometrica, 68, 1055- 1096.

Year 2011, Volume: 3 Issue: 2, 13 - 21, 01.12.2011

Mehmet Caner

https://izlik.org/JA23RD22RU

Abstract

References

  • Anderson, T.W. and H. Rubin (1949). Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations. Annals of Mathematical Statistics, 20, 46-63.
  • Andrews, D.W.K. (1994). Empirical Process Methods in Econometrics. Handbook of Econometrics, 4, 2247-2294.
  • Antoine, B. and E. Renault (2007). Efficient GMM with nearly-weak identification. Working paper. Department of Economics, University of North Carolina-Chapel Hill.
  • Caner, M. (2010). Testing, Estimation in GMM and CUE with Nearly-Weak IdentiŞcation. Econometric Reviews, 29, 330-363.
  • Hahn, J. and G. Kuersteiner (2002). Discontinuities of Weak Instrument Limiting Distributions. Economics Letters, 75, 325-331.
  • Hall, P. and J.L. Horowitz (1996). Bootstrap critical values for tests based on generalized method of moments estimators. Econometrica, 64, 891-916.
  • Hansen, L.P., J. Heaton and A. Yaron (1996). Finite Sample Properties of Some Alternative GMM Estimators. Journal of Business and Economic Statistics, 14, 262-280.
  • Kleibergen, F. (2005). Testing Parameters in GMM Without Assuming That They Are IdentiŞed. Econometrica, 73, 1103-1124.
  • Mood, A.M., F.A. Graybill and D.C. Boes (1974). Introduction to the Theory of Statistics. New-York: Mc-Graw Hill.
  • Phillips, P.C.B. and J.Y. Park (1988). On the Formulation of Wald Tests of Nonlinear Restrictions. Econometrica, 56, 1065-1083.
  • Stock, J.H. and J.H. Wright (2000). GMM with Weak Identification. Econometrica, 68, 1055- 1096.
There are 11 citations in total.

Details

Other ID JA74KC83VM
Authors

Mehmet Caner This is me

Submission Date December 1, 2011
Publication Date December 1, 2011
IZ https://izlik.org/JA23RD22RU
Published in Issue Year 2011 Volume: 3 Issue: 2

Cite

APA Caner, M. (2011). A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics. International Econometric Review, 3(2), 13-21. https://izlik.org/JA23RD22RU
AMA 1.Caner M. A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics. IER. 2011;3(2):13-21. https://izlik.org/JA23RD22RU
Chicago Caner, Mehmet. 2011. “A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics”. International Econometric Review 3 (2): 13-21. https://izlik.org/JA23RD22RU.
EndNote Caner M (December 1, 2011) A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics. International Econometric Review 3 2 13–21.
IEEE [1]M. Caner, “A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics”, IER, vol. 3, no. 2, pp. 13–21, Dec. 2011, [Online]. Available: https://izlik.org/JA23RD22RU
ISNAD Caner, Mehmet. “A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics”. International Econometric Review 3/2 (December 1, 2011): 13-21. https://izlik.org/JA23RD22RU.
JAMA 1.Caner M. A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics. IER. 2011;3:13–21.
MLA Caner, Mehmet. “A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics”. International Econometric Review, vol. 3, no. 2, Dec. 2011, pp. 13-21, https://izlik.org/JA23RD22RU.
Vancouver 1.Mehmet Caner. A Pretest to Differentiate Between Weak and Nearly-Weak Instrument Asymptotics. IER [Internet]. 2011 Dec. 1;3(2):13-21. Available from: https://izlik.org/JA23RD22RU