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Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order

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  • Wouter J. den Haan
  • Andrew T. Levin

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

  • Wouter J. den Haan & Andrew T. Levin, 2000. "Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order," NBER Technical Working Papers 0255, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0255
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    2. 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.
    3. 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.
    4. 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.
    5. Ray Barrell, 1999. "Employment Security and European Labour Demand: A Panel Study Across 16 Industries," National Institute of Economic and Social Research (NIESR) Discussion Papers 148, National Institute of Economic and Social Research.
    6. 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.
    7. Maury, T-P. & Pluyaud, B., 2004. "Les ruptures de tendance de la productivité par employé de quelques grands pays industrialisés," Bulletin de la Banque de France, Banque de France, issue 121, pages 70-86.
    8. Gabor Pinter, 2016. "The Macroeconomic Shock with the Highest Price of Risk," Discussion Papers 1623, Centre for Macroeconomics (CFM), revised Apr 2017.
    9. 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.
    10. Tim A. Kroencke, 2017. "Asset Pricing without Garbage," Journal of Finance, American Finance Association, vol. 72(1), pages 47-98, February.
    11. 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.
    12. Marianne Baxter, 2012. "International risk-sharing in the short run and in the long run," Canadian Journal of Economics, Canadian Economics Association, vol. 45(2), pages 376-393, May.
    13. A. nazif Catik & Chris Martin, 2010. "Relative Price Adjustment and the UK Phillips Curve," Economics Bulletin, AccessEcon, vol. 30(3), pages 1737-1744.
    14. 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.
    15. West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
    16. Laurinaityte, Nora & Meinerding, Christoph & Schlag, Christian & Thimme, Julian, 2020. "GMM weighting matrices incross-sectional asset pricing tests," Discussion Papers 62/2020, Deutsche Bundesbank.
    17. repec:ebl:ecbull:v:3:y:2005:i:10:p:1-13 is not listed on IDEAS
    18. Maury, P-M. & Pluyaud, B., 2004. "The Breaks in per Capita Productivity Trends in a Number of Industrial Countries," Working papers 111, Banque de France.
    19. Hartigan, Luke, 2018. "Alternative HAC covariance matrix estimators with improved finite sample properties," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 55-73.
    20. George Kapetanios & Zacharias Psaradakis, 2016. "Semiparametric Sieve-Type Generalized Least Squares Inference," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 951-985, June.
    21. Ozgen Sayginsoy, 2005. "Powerful and Serial Correlation Robust Tests of the Economic Convergence Hypothesis," Econometrics 0503014, University Library of Munich, Germany, revised 11 Mar 2005.
    22. Motohiro Yogo, 2006. "A Consumption‐Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.

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    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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