事件研究的计量经济学Econometrics of Event Studies
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Econometrics of Event Studies事件研究的计量经济学
Econometrics of Event Studies
S.P. Kothari
Sloan School of Management, MIT
Jerold B. Warner
William E. Simon Graduate School of Business Administration
University of Rochester
October 20, 2004
This article will appear in the Handbook of Corporate Finance: Empirical Corporate
Finance (Elsevier/North-Holland), which is edited by B. Espen Eckbo.
We thank Jon Lewellen and Adam Kolasinski for insightful comments, and Irfan Safdar
and Alan Wancier for research assistance.
ABSTRACT
The number of published event studies exceeds 500, and the literature continues
to grow. We provide an overview of event study methods. Short-horizon methods are
quite reliable. While long-horizon methods have improved, serious limitations remain.
A challenge is to continue to refine long- horizon methods. We present new evidence that
properties of event study methods can vary by calendar time period and can depend on
event sample firm characteristics such as volatility. This reinforces the importance of
examining event study statistical properties for non-randomly selected samples.
Table of Contents
1. Introduction and Background
2. The Event Study Literature
2.1 The stock and flow of event studies
2.2 Changes in event study methods: the big picture
3. Characterizing Event Study Methods
3.1 An event study: the model
3.2 Statistical and economic hypotheses
3.3 Sampling distributions and test statistics
3.4 Criteria for “reliable” event study tests
3.5 Determining specification and power
3.6 A quick survey of our knowledge
4. Long-Horizon Event Studies
4.1 Background
4.2 Risk adjustment and expected returns
4.3 Approaches to Abnormal Performance Measurement
4.4 Significance tests for BHAR and Jensen-alpha measures
4.4.1 Skewness
4.4.2 Cross-correlation
4.4.3 The bottom line
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