A Simulation Investigation of Firm-Specific Equation Models as Used in Accounting Information Event Studies
AbstractResearchers studying stock price reactions to accounting information releases can choose among several statistical methods/models. We investigate the empirical distribution of common statistics used in SUR and OLS estimation via monte-carlo methods on daily stock return data. We find that the SUR statistics over reject the null hypothesis far too often and in fact the commonly used SAS F-statistic rejects the null more often than other related statistics. We give some indication of the amount of correction needed and also the corrected power statistics.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9307001.
Length: 35 pages
Date of creation: 28 Jul 1993
Date of revision:
Note: LaTeX document 35 pages (some LaTeX's do not like bold math)
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Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Malatesta, Paul H., 1986. "Measuring Abnormal Performance: The Event Parameter Approach Using Joint Generalized Least Squares," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(01), pages 27-38, March.
- McDonald, Bill, 1987. "Event Studies and Systems Methods: Some Additional Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(04), pages 495-504, December.
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