| Project/Area Number |
12630099
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Public finance/Monetary economics
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| Research Institution | Keio University (2003)
Osaka University (2000-2002) |
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Principal Investigator |
MCKENZIE Colin Keio University, Faculty of Economics, Professor, 経済学部, 教授 (10220980)
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| Project Period (FY) |
2000 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2003: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2002: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2001: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2000: ¥800,000 (Direct Cost: ¥800,000)
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| Keywords | Event Study / Generated Variable / Monte Carlo / Efficiency / Hypothesis Testing / Risk / 等張回帰分析 / 構造変化の検定 / 転換社債 / 社債 / 株価 / CUSUMテスト / 操作変数方 / モンテ・カルロ実験 / バイス / 検定量 / システム推定 / シュミレーション / 操作変数法 / ガソリン価格 / ファイナンス / 分散不均一性 / 一致性 |
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| Research Abstract |
The purpose of this study is to examine some of the econometric problems that arise in event studies which are typically used to investigate what impact a particular event has on the firm's share price or the price of bonds it has issued. First, the theoretical impact of including in the model of interest a variety of generated variables was analyzed. The asymptotic impact of using a generated variable on the consistency of estimators and on the standard errors of estimators is shown to depend among other things on the number of observations in the first and second stage regressions, and the type of generated regressor used. Solutions to these problems are carefully described. Second, the small sample impact of using some generated variables was analyzed using a Monte Carlo study. It was found that some instrumental variable estimators had smaller biases than ordinary least squares based estimators, but the sizes and powers of tests associated with the coefficient of the generated variable do not seem to be affected by the presence of the generated variable. In contrast, the sizes of tests associated with the coefficient of the non generated explanatory variable are considerably distorted when the generated variable should be included in the structural equation. Third, a variety of solutions to the generated variable problem are illustrated using event study and non-event study data. These solutions include system estimation, adjusting standard errors using White or Newey-West corrections, and instrumental variable estimation. Finally, the use of bond prices in event studies for Japanese data was investigated. For event studies investigating any misspricing associated with a new bond issue, over the counter quotations are found to be more appropriate.
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