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Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order

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  • den Haan, Wouter J.
  • Levin, Andrew T

Abstract

This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and we demonstrate the benefits of using a model selection criterion (either AIC or BIC) to determine its lag structure. Furthermore, once data-dependent VAR prewhitening has been utilized, we find negligible or even counter-productive effects of applying standard kernel-based methods to the prewhitened residuals; that is, the performance of the prewhitened kernel estimator is virtually indistinguishable from that of the VARHAC estimator.

Suggested Citation

  • den Haan, Wouter J. & Levin, Andrew T, 2000. "Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order," University of California at San Diego, Economics Working Paper Series qt0127m2tp, Department of Economics, UC San Diego.
  • Handle: RePEc:cdl:ucsdec:qt0127m2tp
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Wouter J. Den Haan & Andrew T. Levin, 1995. "Inferences from parametric and non-parametric covariance matrix estimation procedures," International Finance Discussion Papers 504, Board of Governors of the Federal Reserve System (U.S.).
    4. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    5. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    6. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    7. Martin S. Eichenbaum & Lars Peter Hansen & Kenneth J. Singleton, 1988. "A Time Series Analysis of Representative Agent Models of Consumption and Leisure Choice Under Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 103(1), pages 51-78.
    8. Stock, James H & Watson, Mark W, 1993. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, Econometric Society, vol. 61(4), pages 783-820, July.
    9. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
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    Cited by:

    1. Ionel Birgean & Lutz Kilian, 2002. "Data-Driven Nonparametric Spectral Density Estimators For Economic Time Series: A Monte Carlo Study," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 449-476.
    2. repec:ebl:ecbull:v:3:y:2005:i:10:p:1-13 is not listed on IDEAS
    3. Tim A. Kroencke, 2017. "Asset Pricing without Garbage," Journal of Finance, American Finance Association, vol. 72(1), pages 47-98, February.
    4. Min-Hsien Chiang & Chihwa Kao, 2005. "Spectral Density Bandwidth Choice and Prewhitening in the Generalized Method of Moments Estimators for the Asset Pricing Model," Economics Bulletin, AccessEcon, vol. 3(10), pages 1-13.
    5. A. Craig Burnside, 2007. "Empirical Asset Pricing and Statistical Power in the Presence of Weak Risk Factors," NBER Working Papers 13357, National Bureau of Economic Research, Inc.
    6. Richard Heaney & Kerry Pattenden, 2005. "Change in unconditional foreign exchange rate volatility: an analysis of the GBP and USD price of the Euro from 2002 to 2003," Applied Economics Letters, Taylor & Francis Journals, vol. 12(15), pages 929-932.
    7. Craig Burnside, 2016. "Identification and Inference in Linear Stochastic Discount Factor Models with Excess Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(2), pages 295-330.
    8. Luke Hartigan, 2016. "Alternative HAC Covariance Matrix Estimators with Improved Finite Sample Properties," Discussion Papers 2016-06, School of Economics, The University of New South Wales.
    9. Karamé, Frédéric & Patureau, Lise & Sopraseuth, Thepthida, 2008. "Limited participation and exchange rate dynamics: Does theory meet the data?," Journal of Economic Dynamics and Control, Elsevier, vol. 32(4), pages 1041-1087, April.
    10. Matheron, Julien & Maury, Tristan-Pierre, 2004. "Supply-side refinements and the New Keynesian Phillips Curve," Economics Letters, Elsevier, vol. 82(3), pages 391-396, March.
    11. George Kapetanios & Zacharias Psaradakis, 2016. "Semiparametric Sieve-Type Generalized Least Squares Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 951-985, June.
    12. Ozgen Sayginsoy, 2005. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Econometrics 0503014, EconWPA, revised 11 Mar 2005.
    13. Motohiro Yogo, 2006. "A Consumption-Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.
    14. Dr Martin Weale & Dr. James Mitchell, 2002. "Aggregate versus Disaggregate Survey-Based Indicators of Economic Activity (revised January 2005)," National Institute of Economic and Social Research (NIESR) Discussion Papers 194, National Institute of Economic and Social Research.

    More about this item

    Keywords

    VAR; covariance matrix estimation;

    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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