1991
DOI: 10.1007/bf02408396
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Statistical inference in multiperiod event studies

Abstract: Abstract.We examine several event-study test statistics that can be used to detect abnormal performance during a multiperiod event window. We demonstrate that one of the most commonly used test statistics does not, under the assumptions made, have the distribution claimed (standard normal), and thus tests using it will be biased. The magnitude of that bias is shown to increase with the length of the event window and can generally be expected to lead to excessive rejection of the null hypothesis. We also compar… Show more

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Cited by 38 publications
(12 citation statements)
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“…All test statistics for average cumulative abnormal returns reflect the Karatiath and Spencer ( 1991) adjustment for serial correlation in the prediction errors. The test statistics for the average abnormal returns for a single event day are the standard Z test.…”
Section: Methodsmentioning
confidence: 99%
“…All test statistics for average cumulative abnormal returns reflect the Karatiath and Spencer ( 1991) adjustment for serial correlation in the prediction errors. The test statistics for the average abnormal returns for a single event day are the standard Z test.…”
Section: Methodsmentioning
confidence: 99%
“…The sign of Z in equation (6) can be opposite the sign of the mean cumulative prediction error. Further, Karafiath and Spencer (1991) show that the test statistic represented by equation (6) has greater power (i.e., lower type II error) than other well-specified tests.…”
Section: Event Study Modelmentioning
confidence: 96%
“…The market model is estimated according to a specification proposed by Karafiath and Spencer (1991) 12. Typical pre-offer and post-close periods were found by measuring the average time between offer-related events and offer announcement dates.…”
Section: Figure 2 Time Line Of Estimation Intervals (In Months) and Omentioning
confidence: 99%