All Events Induce Variance: Analyzing Abnormal Returns When Effects Vary Across Firms

41 Pages Posted: 10 Feb 2003

See all articles by Scott E. Harrington

Scott E. Harrington

University of Pennsylvania - Wharton School

David Shrider

University of South Carolina - Darla Moore School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: November 2002

Abstract

Widely used test statistics for non-zero mean abnormal returns in short-horizon event studies ignore cross-firm variation in event effects. Cross-sectional regression analyses of abnormal returns often either ignore heteroskedasticity in model disturbances or ignore plausible implications of unexplained variation in effects for the structure of heteroskedasticity. We use a simple model of event effects and simulations patterned after Brown and Warner (1980, 1985) and Boehmer, Musumeci, and Poulsen (BMP, 1991) to highlight the resulting biases and the importance of using test procedures that appropriately allow for cross-sectional variation. We demonstrate analytically how cross-sectional variation produces "event-induced" variance increases and biases popular tests for non-zero mean abnormal returns. Our simulations provide evidence of that bias and of test power for several theoretically robust tests for non-zero means, including the standardized cross-sectional test statistic suggested by BMP, which we show equals the mean standardized prediction error divided by a heteroskedasticity-consistent standard error, and cross-sectional regression tests that condition on relevant regressors. We also analyze and provide evidence of bias and power for alternative tests for non-zero slopes in abnormal return regression models with heteroskedastic errors attributable to cross-firm variation in event effects and market model disturbance variances. Neither OLS nor WLS has good properties. WLS with robust standard errors and maximum likelihood estimation assuming non-proportional heteroskedasticity may represent useful supplements to OLS with robust standard errors.

Keywords: abnormal returns, event-induced variance, event study methodology, heteroskedasticity

JEL Classification: G10, G14

Suggested Citation

Harrington, Scott E. and Shrider, David, All Events Induce Variance: Analyzing Abnormal Returns When Effects Vary Across Firms (November 2002). Available at SSRN: https://ssrn.com/abstract=332041 or http://dx.doi.org/10.2139/ssrn.332041

Scott E. Harrington (Contact Author)

University of Pennsylvania - Wharton School ( email )

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HOME PAGE: http://scottharringtonphd.com/

David Shrider

University of South Carolina - Darla Moore School of Business ( email )

1705 College St
Francis M. Hipp Building
Columbia, SC 29208
United States

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