| Project/Area Number |
15530138
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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 |
Economic statistics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
KUNITOMO Naoto The University of Tokyo, Graduate School of Economics, Professor, 大学院・経済学研究科, 教授 (10153313)
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| Co-Investigator(Kenkyū-buntansha) |
KOBAYASHI Masahito Yokohama National University, Faculty of Economics, Professor, 大学院・経済学研究科, 教授 (60170354)
OMORI Yasuhiro The University of Tokyo, Graduate School of Economics, Associate Professor, 大学院・経済学研究科, 助教授 (60251188)
KURATA Hiroshi The University of Tokyo, Graduate School of Arts and Sciences, Associate Professor, 大学院・総合文化研究科, 助教授 (50284237)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2004: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 2003: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | Micro-econometrics / Generalized Method of Moments / Empirical Likelihood Method / Limited Information Maximum Likelihood Method / Small Sample Properties / Asymptotic Expansions / Asymptotic Theory / 制限情報最尤法 |
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| Research Abstract |
The main purpose of this project was to re-examine the existing statistical methods often used in in micro-econometric analysis and their applications.
First we have investigated the major semiparametric statistical methods for analyzing econometric analyses and financial econometric analyses. We have investigated the empirical likelihood (EL) approach. In particular, we have compared the maximum empirical likelihood (MEL) method and the generalized method of moments (GMM). The latter method has been well-known in econometric analyses and it has been the most popular semiparametric method in the past two decades within the field of econometrics. We have found that there are important situations in applications where the MEL method dominates the GMM method and we have investigated the small sample properties of these estimation methods by using the asymptotic expansion method.
Second, we have also investigated the classical method of the limited information maximum likelihood (LIML) metho
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d and found that it has an asymptotic optimality in the micro-econometric models when the number of instruments is large. We have investigated the small sample differences among the ME method, the GMM method, the LIML method and the TSLS (Two-Stage Least Squares) method in depth.
Third, there have been many new results we have obtained under the research efforts of this project on the MEL method and the LIML method. The details of the results under our research project have been reported in domestic as well as international academic meetings and have been (or will be) reported in academic papers listed in this report.
In conclusion, we have accomplished the most important objectives of this project. Four members participated in this project officially have written many papers and also stimulated a large number of researchers in the related fields and some statisticians in the academic international perspectives We thank The Ministry of Education, Science, Sports and Culture and Japan Society for the Promotion of Science for giving the generous support to our research project. Less
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