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Nonparametric tests for economic models

经济模型的非参数检验

基本信息

批准号：
14530031
负责人：
HITOMI Kohtaro
金额：
$ 0.58万
依托单位：
Kyoto Institute of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2004
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-14530031/
关键词：
semiparametric GMM statistical tests exponential tilting Granger causality 推定方法バイアス分散経験尤度推定量 Exponential Tilting estimator Empirical Likelihood Estimator 小標本 Empirical Likelihood Exponential Tilting Small sample bics numbe

项目摘要

This report investigated three topics. The first paper compares conventional GMM estimator to Empirical Likelihood(EL) and Exponential Tilting estimators when the number of moment conditions increases with the number of observations. The main findings of the experiments show the following. Small sample biases of EL and ET are considerably smaller than GMM if the number of moment conditions is less than 10% of the number of observations. When the number of the moment conditions exceed 10% of the number of observations, small sample biases of EL and ET increase almost linearly as the number of moment conditions increase and the slopes are greater than the slope of GMM. The small sample bias of bias corrected GMM (Newey and Smith 2001) is always the same or smaller than the biases of other estimators. The standard deviations of GMM and bias corrected GMM estimators are decreased as the number of moment conditions is increased. The standard deviations of EL and ET estimators, however, are increased when the number of moment conditions exceeds 10% of the number of observations.The second paper investigated Granger causality. We developed root-n consisitent nonparametric Granger causality test.Third paper analyzed a paradoxical phenomenon of semiparametric model that some semiparametric estimators are more efficient when infinite dimensional nuisance parameters are unknown. This paper examined the structure of the paradox. The necessary and sufficient condition of the paradox is presented and a simple sufficient condition is derived. In addition, two examples of semiparametric estimators are examined.

这份报告调查了三个主题。第一篇论文比较了传统GMM估计与经验似然（EL）和指数倾斜估计在矩条件数量随观测数量增加时的差异。实验的主要结果如下：当矩条件数小于观测数的10%时，EL和ET的小样本偏差明显小于GMM。当矩条件数超过观测数的10%时，EL和ET的小样本偏差几乎随矩条件数的增加而线性增加，且斜率大于GMM的斜率。偏差校正GMM （Newey and Smith 2001）的小样本偏差总是与其他估计器的偏差相同或更小。GMM和偏差校正GMM估计的标准差随着矩条件数目的增加而减小。然而，当矩条件的数量超过观测数的10%时，EL和ET估计的标准差会增加。第二篇论文研究格兰杰因果关系。我们发展了根n一致非参数格兰杰因果检验。第三篇文章分析了半参数模型的一个矛盾现象，即当无穷维扰参数未知时，某些半参数估计更有效。本文考察了这一悖论的结构。给出了悖论的充分必要条件，并导出了一个简单的充分条件。此外，还给出了两个半参数估计的例子。