Correcting for Cross-Sectional and Time-Series Dependence in Accounting Research

49 Pages Posted: 31 Jul 2008 Last revised: 24 Oct 2010

See all articles by Ian D. Gow

Ian D. Gow

University of Melbourne

Gaizka Ormazabal

University of Navarra, IESE Business School

Daniel J. Taylor

Wharton School, University of Pennsylvania

Date Written: August 4, 2009

Abstract

We review and evaluate the methods commonly used in the accounting literature to correct for cross-sectional and time-series dependence. While much of the accounting literature studies settings where variables are cross-sectionally and serially correlated, we find that the extant methods are not robust to both forms of dependence. Contrary to claims in the literature, we find that the Z2-statistic and Newey-West corrected Fama-MacBeth do not correct for both cross-sectional and time-series dependence. We show that extant methods produce misspecified test statistics in common accounting research settings, and that correcting for both forms of dependence substantially alters inferences reported in the literature. Specifically, several findings in the cost of equity capital literature, the cost of debt literature, and the conservatism literature appear not to be robust to the use of well-specified test statistics.

Keywords: cross-sectional dependence, time-series dependence, autocorrelation, Fama-MacBeth, Newey-West, cluster-robust standard errors, cost of capital, credit ratings, conservatism

JEL Classification: C12, C15, C23, M41

Suggested Citation

Gow, Ian D. and Ormazabal, Gaizka and Taylor, Daniel, Correcting for Cross-Sectional and Time-Series Dependence in Accounting Research (August 4, 2009). Accounting Review, Forthcoming. Available at SSRN: https://ssrn.com/abstract=1175614

Ian D. Gow

University of Melbourne ( email )

185 Pelham Street
Carlton, Victoria 3053
Australia

Gaizka Ormazabal

University of Navarra, IESE Business School ( email )

Avenida Pearson 21
Barcelona, 08034
Spain

Daniel Taylor (Contact Author)

Wharton School, University of Pennsylvania ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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