Abstract
We find that the relative levels of the computationally costly q-estimator developed by Perfect and Wiles (1994) and the simple one of Chung and Pruitt (1994), when used as continuous variables, are affected by variations in several firm financial characteristics. In contrast, when the estimators are used as dichotomous variables, they classify the vast majority of firms identically with respect to the unit q breakpoint. Finally, we find that the computationally costly approach may induce sample selection bias as a result of data unavailability. Our results suggest that the simple approach is preferable except in cases when extreme precision of the q estimate is paramount and sample selection bias is not likely to be an issue.
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