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Cross-Sectional Data with a Common Shock and Generalized Method of Moments

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  • Serguey Khovansky

    (D’Amore-McKim School of Business, Northeastern University, USA)

Abstract

This note outlines possible issues that arise when a common shock exists in such data which models are estimated using Generalized Method of Moments. It provides a theoretical foundation of the issue, an approach to its solution and a reference to an empirical application.

Suggested Citation

  • Serguey Khovansky, 2018. "Cross-Sectional Data with a Common Shock and Generalized Method of Moments," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(5), pages 151-152, March.
    • Handle: RePEc:adp:jbboaj:v:5:y:2018:i:5:p:151-152
    DOI: 10.19080/BBOAJ.2018.05.555674
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    References listed on IDEAS

    as
    1. Khovansky, Serguey & Zhylyevskyy, Oleksandr, 2013. "Impact of idiosyncratic volatility on stock returns: A cross-sectional study," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3064-3075.
    2. Donald W. K. Andrews, 2005. "Cross-Section Regression with Common Shocks," Econometrica, Econometric Society, vol. 73(5), pages 1551-1585, September.
    3. Khovansky, Serguey & Zhylyevskyy, Oleksandr, 2017. "On the consistency of a cross-sectional GMM estimator in the presence of an observable stochastic common data shock," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 196-202.
    4. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    Full references (including those not matched with items on IDEAS)

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