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Theory and Applications of Micro-econometrics

微观计量经济学理论与应用

基本信息

批准号：
15530138
负责人：
KUNITOMO Naoto
金额：
$ 2.11万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15530138/
关键词：
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

项目摘要

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 … More 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

本项目的主要目的是重新审视微观计量分析中常用的现有统计方法及其应用。首先，我们研究了用于计量分析和金融计量分析的主要半参数统计方法。我们研究了经验似然(EL)方法。特别地，我们比较了最大经验似然(MEL)方法和广义矩方法(GMM)。后一种方法在计量经济学分析中已经广为人知，它是近二十年来计量经济学领域中最流行的半参数方法。我们发现在实际应用中MEL方法优于GMM方法，并且我们利用渐近展开方法研究了这些估计方法的小样本性质。其次，我们还研究了经典的有限信息最大似然方法…并发现当工具数量较大时，在微观计量经济模型中具有渐近最优性。深入研究了ME方法、GMM方法、LIML方法和TSLS(两阶段最小二乘)方法之间的小样本差异。第三，在本项目的研究工作中，我们在Mel方法和LIML方法方面取得了许多新的结果。我们的研究项目的详细结果已在国内和国际学术会议上报告，并已经(或将会)在本报告列出的学术论文中报告。总而言之，我们实现了该项目最重要的目标。参与这一项目的四名成员正式撰写了许多论文，也激发了大量相关领域的研究人员和一些国际学术视野的统计学家。我们感谢文部科学省和日本科学促进会对我们研究项目的慷慨支持。较少