1985
DOI: 10.2307/2555408
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Measuring the Effects of Regulation with Stock Price Data

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Cited by 431 publications
(257 citation statements)
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“…Event study methodology has been extensively used to assess the effects of legislation on stock prices (Schwert, 1981;Rose, 1985;Binder, 1985;Gilligan, et al, 1990). The fundamental assumption underlying the use of this approach is the efficiency of asset markets (Fama, 1976).…”
Section: Event Study Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…Event study methodology has been extensively used to assess the effects of legislation on stock prices (Schwert, 1981;Rose, 1985;Binder, 1985;Gilligan, et al, 1990). The fundamental assumption underlying the use of this approach is the efficiency of asset markets (Fama, 1976).…”
Section: Event Study Methodologymentioning
confidence: 99%
“…An extension of the model incorporates a dummy variable, Djt equal to 1 if event j occurs at time t, and 0 otherwise, to capture the effect of specific events in time (Prager, 1989 andBinder, 1985).…”
Section: Event Study Methodologymentioning
confidence: 99%
“…One way to account for the impact of regulatory announcements is to use an event study (Schwert 1981;Binder 1985;Brown and Warner 1985;Lamdin 2001). We measure the effect of a regulatory event on the day of its announcement by calculating the abnormal returns for each company.…”
Section: Estimation Proceduresmentioning
confidence: 99%
“…We apply an event study to identify the in uence of environmental information on market value. This method has been established as the standard approach to capture market reactions to events or publications (Binder, 1998). Identi cation rests on the assumption that stock price developments follow a market model.…”
Section: Previous Researchmentioning
confidence: 99%
“…However, the method has been re ned in the last years. In particular the work of Binder (1985) has helped to establish the Multivariate Regression Model (MVRM): To allow for heteroscedasticity across rms, the MVRM consists of n stacked equations, according to the number of rms in the sample, with rm speci c dummy variables, yielding the following set of GLS equations:…”
Section: Previous Researchmentioning
confidence: 99%