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Robust Two-Pass Cross-Sectional Regressions: A Minimum Distance Approach

Author

Listed:
  • Seung C. Ahn
  • Christopher Gadarowski
  • M. Fabricio Perez

Abstract

We examine the asymptotic and finite-sample properties of the two-pass (TP) cross-sectional regressions estimators when factors and asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive the heteroskedasticity- and/or autocorrelation-consistent (HAC) standard errors and the optimal TP estimator. A HAC model specification test statistic is also derived. Our Monte Carlo simulation results reveal the importance of controlling for autocorrelation. The HAC standard errors produce the most reliable inferences under autocorrelation. The HAC specification test is a viable alternative if the number of asset returns is small and the number of time-series observations is large. (JEL: C12, C13, C3) Copyright The Author, 2012. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Seung C. Ahn & Christopher Gadarowski & M. Fabricio Perez, 2012. "Robust Two-Pass Cross-Sectional Regressions: A Minimum Distance Approach," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 669-701, September.
    • Handle: RePEc:oup:jfinec:v:10:y:2012:i:4:p:669-701
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbs006
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    Cited by:

    1. Sainan Jin & Liangjun Su & Yonghui Zhang, 2015. "Nonparametric testing for anomaly effects in empirical asset pricing models," Empirical Economics, Springer, vol. 48(1), pages 9-36, February.
    2. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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