DETECTING LONG-RUN ABNORMAL STOCK RETURNS - THE EMPIRICAL POWER AND SPECIFICATION OF TEST STATISTICS

We analyze the empirical power and specification of test statistics in event studies designed to detect long-run (one- to five-year) abnorma l stock returns. We document that test statistics based on abnormal re turns calculated using a reference portfolio, such as a market index, are misspecified (empirical rejection rates exceed theoretical rejecti on rates) and identify three reasons for this misspecification. We cor rect for the three identified sources of misspecification by matching sample firms to control firms of similar sizes and book-to-market rati os. This control firm approach yields well-specified rest statistics i n virtually all sampling situations considered.