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Methods For Nonstationary And Nonlinear Models In Economic Time Series And Their Applications

经济时间序列非平稳非线性模型方法及其应用

基本信息

批准号：
11630028
负责人：
MAEKAWA Koichi
金额：
$ 2.3万
依托单位：
Hiroshima University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-11630028/
关键词：
SUR model unit root cointegration structural change macro economic time series time series of stock data simulation analysis nonlinear regression 非線形回帰モデル非定常時系列因果性漸近分布 SURモデル

项目摘要

This project concerns with theory and application of non-stationary and non-linear time series regression models. Our studies can be grouped in the three categories : Category (1) deals with both non-stationary and non-linearlity, (2) deals with non-stationary, (3) theory of regression which is the base of studies of (1) and (2). We obtained the following results.A) Concerning (1) Maekawa and Tee proposed a method of estimating a point of time of structural change in a time series when a time series has a unit root. Our result was presented at the annual meeting of Japan statistical association and MODSIM2001 held in Canberra, Australia and conferences. Our method is found to be better than other existing methods in the literature on this problem.B) Concerning (2) Maekawa and Hisamatsu studied SUR model with non-stationary regressors by asymptotic theory and Monte Carlo simulation and found that Zellner's two estimators were superior to OLS estimator as in the stationary case. This result is published in Handbook of applied econometrics and statistical inference (2002, Marcel Dekker, Inc.). Maekawa and Zongle He showed that usual F test for Granger's causality often detected spurious causality between two independent and irrelevant time series one of or both of which is/or random walk(s). This results was published in Economics letters, 2001.(C) Concerning (3) Kurata studied statistical properties of the GLS estimator in SUR model and a general linear regression model. Fukuchi studied subsampling method in time series regression.In addition we invited Professor J. Park at Seoul University to hear the recent development on non-stationary and non-linear time series. Maekawa visited the National University of Singapore to meet Professor Y. Tse to discuss non-stationary and non-linear tome series regression models in financial time series.

本项目主要研究非平稳、非线性时间序列回归模型的理论与应用。我们的研究可以分为三类：（1）研究非平稳和非线性，（2）研究非平稳，（3）回归理论，它是（1）和（2）研究的基础。我们得到了以下结果。A）关于（1）Maekawa和Tee提出了一种方法，当时间序列具有单位根时，估计时间序列中结构变化的时间点。我们的结果在澳大利亚堪培拉举行的日本统计协会年会和MODSIM 2001以及其他会议上发表。B）关于（2）Maekawa和Hisamatsu利用渐近理论和MonteCarlo模拟研究了非平稳回归的SUR模型，发现Zellner的两个估计上级平稳情形下的OLS估计。这一结果发表在《应用计量经济学和统计推断手册》（2002年，Marcel Dekker，Inc.）上。Maekawa和Zongle He指出，通常的格兰杰因果关系的F检验往往检测到两个独立和不相关的时间序列之间的虚假因果关系，其中一个或两个是随机游走。这一结果发表在2001年的《经济学快报》上。(C)关于（3）Kurata研究了SUR模型和一般线性回归模型中GLS估计的统计性质。Fukuchi教授研究了时间序列回归中的次抽样方法，我们还邀请了首尔大学的J.Park教授，听取了非平稳和非线性时间序列的最新发展。前川访问了新加坡国立大学，与Y教授会面。讨论金融时间序列中的非平稳非线性托姆序列回归模型。