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Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix

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Listed:
  • Lee, Wei-Ming
  • Kuan, Chung-Ming
  • Hsu, Yu-Chin

Abstract

We propose new over-identifying restriction (OIR) tests that are robust to heteroskedasticity and serial correlations of unknown form. The proposed tests do not require consistent estimation of the asymptotic covariance matrix and hence avoid choosing the bandwidth in nonparametric kernel estimation. Instead, they rely on the normalizing matrices that can eliminate the nuisance parameters in the limit. Compared with the conventional OIR test, the proposed tests require only a consistent, but not necessarily optimal, GMM estimator. Our simulations demonstrate that these tests are properly sized and may have power comparable with that of the conventional OIR test.

Suggested Citation

  • Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
  • Handle: RePEc:eee:econom:v:181:y:2014:i:2:p:181-193
    DOI: 10.1016/j.jeconom.2014.04.002
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    References listed on IDEAS

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    1. Andrews, Donald W. K., 1987. "Asymptotic Results for Generalized Wald Tests," Econometric Theory, Cambridge University Press, vol. 3(03), pages 348-358, June.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Lobato I. N., 2001. "Testing That a Dependent Process Is Uncorrelated," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1066-1076, September.
    4. Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory For Heteroskedasticity-Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1130-1164, December.
    5. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 631-653.
    6. Kuan, Chung-Ming & Lee, Wei-Ming, 2006. "Robust M Tests Without Consistent Estimation of the Asymptotic Covariance Matrix," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1264-1275, September.
    7. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    8. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
    9. Wei-Ming Lee & Yu-Chin Hsu & Chung-Ming Kuan, 2014. "Robust Hypothesis Tests for M-Estimators with Possibly Non-differentiable Estimating Functions," IEAS Working Paper : academic research 14-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Oct 2014.
    10. Inoue, Atsushi & Shintani, Mototsugu, 2006. "Bootstrapping GMM estimators for time series," Journal of Econometrics, Elsevier, vol. 133(2), pages 531-555, August.
    11. Nicholas M. Kiefer & Timothy J. Vogelsang & Helle Bunzel, 2000. "Simple Robust Testing of Regression Hypotheses," Econometrica, Econometric Society, vol. 68(3), pages 695-714, May.
    12. Peter C. B. Phillips & Yixiao Sun & Sainan Jin, 2006. "Spectral Density Estimation And Robust Hypothesis Testing Using Steep Origin Kernels Without Truncation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(3), pages 837-894, August.
    13. Vogelsang, Timothy J., 2001. "Testing in GMM Models without Truncation," Working Papers 01-12, Cornell University, Center for Analytic Economics.
    14. Kiefer, Nicholas M. & Vogelsang, Timothy J., 2002. "Heteroskedasticity-Autocorrelation Robust Testing Using Bandwidth Equal To Sample Size," Econometric Theory, Cambridge University Press, vol. 18(06), pages 1350-1366, December.
    15. Hall, Alastair R. & Inoue, Atsushi & Peixe, Fernanda P.M., 2003. "Covariance Matrix Estimation And The Limiting Behavior Of The Overidentifying Restrictions Test In The Presence Of Neglected Structural Instability," Econometric Theory, Cambridge University Press, vol. 19(06), pages 962-983, December.
    16. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    17. Alastair R. Hall, 2000. "Covariance Matrix Estimation and the Power of the Overidentifying Restrictions Test," Econometrica, Econometric Society, vol. 68(6), pages 1517-1528, November.
    18. Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-1070, September.
    19. Lee, Wei-Ming, 2007. "Robust M tests using kernel-based estimators with bandwidth equal to sample size," Economics Letters, Elsevier, vol. 96(3), pages 295-300, September.
    20. repec:wop:calsdi:96-17 is not listed on IDEAS
    21. Nicholas M. Kiefer & Timothy J. Vogelsang, 2002. "Heteroskedasticity-Autocorrelation Robust Standard Errors Using The Bartlett Kernel Without Truncation," Econometrica, Econometric Society, vol. 70(5), pages 2093-2095, September.
    22. Wouter Denhaan & Andrew T. Levin, 1996. "VARHAC Covariance Matrix Estimator (GAUSS)," QM&RBC Codes 64, Quantitative Macroeconomics & Real Business Cycles.
    23. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    24. Bunzel H. & Kiefer N. M. & Vogelsang T. J., 2001. "Simple Robust Testing of Hypotheses in Nonlinear Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1088-1096, September.
    25. Sun, Yixiao & Kim, Min Seong, 2012. "Simple and powerful GMM over-identification tests with accurate size," Journal of Econometrics, Elsevier, vol. 166(2), pages 267-281.
    26. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
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    Cited by:

    1. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.

    More about this item

    Keywords

    GMM; Kernel function; KVB approach; Over-identifying restrictions; Robust test;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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