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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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    Cited by:

    1. Marianne Baxter, 2012. "International risk‐sharing in the short run and in the long run," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(2), pages 376-393, May.
    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, Oxford University Press, vol. 14(2), pages 295-330.
    5. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    6. 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.
    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," Bank of England working papers 616, Bank of England.
    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. Pinter, Gabor, 2016. "The macroeconomic shock with the highest price of risk," Bank of England working papers 616, Bank of England.
    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. Liu, Xi & Zhang, Xueyong, 2024. "Geopolitical risk and currency returns," Journal of Banking & Finance, Elsevier, vol. 161(C).
    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.

    More about this item

    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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