Unitroot and Coibtegration in econonetrics

计量经济学中的单位根和协整

基本信息

批准号：
05630013
负责人：
MORIMUNE Kimio
金额：
$ 1.02万
依托单位：
KYOTO UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1993
资助国家：
日本
起止时间：
1993 至 1994
项目状态：
已结题

项目摘要

We apply the non-stationary test of the Granger causality between the Japanese money supply and GNP in this paper. The unit root techniques and the co-integration analysis have grown rapidly in econometrics in the last ten years, and the non-stationary test for Granger causality is developed. We shed new lights on the money income causality using the non-stationary techniques.We firstly specify the uni-variate ARMA models of the money, income, GNP deflator, and the rate of interest using the Dickey and Fuller (DF) or the augmented DF (ADF) tests. Two diagnostic tests are applied to each selected ARMA regression. One is the residual DF test, and the other is the MA unit root test of residuals. After the ARMA model selection, the VAR regression is estimated with co-integrated relation using Johansen's maximum likelihood method. In this estimation, the lag length of each variable is taken to be different from each other which are kept the same in Johansen. The two causality tests are applied to the VAR one of which is the maximum likeliood and the other is the OLS method. It is found out that the income is causing money but not the opposite. Further analyzes of the causality are performed using various lag lengths in VAR but keeping the same lag length for all variables. The income to money causality is found again.The causality is examined for the shorter sample periods which are used by Oritani (1979) . There, the money is found to be non-stationary but the income is stationary. The Granger test is modified to the VAR which includes both stationary and non-stationary variables. The Granger test resulted in the income to money causality, not in the money to income causality. Comments follow on the filter used by Sims (1972) .

我们在本文中应用了日本货币供应与GNP之间的Granger因果关系的非平稳测试。在过去的十年中，单元根技术和协整分析在计量经济学中迅速增长，并且开发了格兰杰因果关系的非平稳检验。我们使用非平稳技术为货币收入因果关系开发了新的灯光。我们首先使用Dickey和Fuller（DF）或增强的DF（ADF）测试指定金钱，收入，GNP缩水器的Uni-Ari-Variate ARMA模型。对每个选定的ARMA回归进行了两个诊断测试。一个是残留DF测试，另一个是残留物的MA单位根测试。在ARMA模型选择之后，使用Johansen的最大似然法估计VAR回归。在此估计中，每个变量的滞后长度彼此不同，在约翰森中保持相同。两个因果关系测试应用于最大的VAR，另一种是OLS方法。发现收入造成了钱，但没有相反。对因果关系的进一步分析是使用VAR中的各种滞后长度进行的，但要保留所有变量的相同滞后长度。再次发现了货币因果关系的收入。在那里，这笔钱被认为是非平稳的，但收入是固定的。 Granger测试已修改为包括固定变量和非平稳变量的VAR。 Granger测试导致收入造成金钱因果关系，而不是收入因果关系。评论遵循Sims（1972）使用的过滤器。