A reexamination of the power of alternative return-generating models and the effect of accounting for cross-sectional dependencies in event studies

Article Abstract:

S.J. Brown and J.B. Warner, in 1980 and 1985, analyzed the power of alternative return-generating models: the mean-adjusted returns model (model 1), the market-adjusted returns model (model 2), and the market- and risk-adjusted returns model (model 3). They concluded that model 1 detected abnormal performance as effectively as did models 2 and 3, and that tests ignoring cross-sectional dependencies among returns could be well-specified and had higher power than those that accounted for cross-sectional dependencies. A reexamination of the return generating models was conducted to elucidate their efficacy for accounting for cross-sectional dependencies in event studies. Research results revealed that Brown and Warner's findings resulted from comparing inconsistent test methods. Models 2 and 3 provided greater power than model 1, and using tests that ignored cross-sectional dependencies offered no advantage.

Models, Return on investment, Rate of return, Brown, S.J., Warner, J.B.

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An empirical comparison of probit and OLS regression hypothesis tests

Article Abstract:

Rejection regions for probit test data are poorly specified for small samples, and ordinary least squares (OLS) appear to work at least as well as probit for the cases examined here. OLS has been used in past research, but its underlying assumption in regression significance tests was violated when a dichotomous dependent variable was used. Probit and logit demonstrate theoretical appeal, with probit used more often than logit in recent classificatory studies in accounting.

Analysis, Usage, Logits, Least absolute deviations (Statistics), Least squares

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