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) .

本文对日本货币供应量与国民生产总值之间的格兰杰因果关系进行非平稳检验。近十年来，单位根技术和协整分析在计量经济学中迅速发展，并且发展了格兰杰因果关系的非平稳检验。我们使用非平稳技术对货币收入因果关系有了新的认识。我们首先使用 Dickey 和 Fuller (DF) 或增强模型指定货币、收入、GNP 平减指数和利率的单变量 ARMA 模型DF（ADF）测试。对每个选定的 ARMA 回归应用两个诊断测试。一是残差DF检验，二是残差MA单位根检验。选择 ARMA 模型后，使用 Johansen 最大似然法通过协整关系估计 VAR 回归。在此估计中，每个变量的滞后长度被视为彼此不同，而 Johansen 中的滞后长度保持相同。对VAR应用两种因果关系检验，其中一种是最大似然法，另一种是OLS方法。结果发现，收入会产生金钱，但不会产生相反的效果。使用 VAR 中的各种滞后长度进行因果关系的进一步分析，但对所有变量保持相同的滞后长度。再次发现了收入与货币的因果关系。对 Oritani (1979) 使用的较短样本期检验了因果关系。在那里，钱是非固定的，但收入是固定的。 Granger 检验是对 VAR 的修改，其中包括平稳变量和非平稳变量。格兰杰检验得出的是收入与货币的因果关系，而不是货币与收入的因果关系。下面是对 Sims (1972) 使用的过滤器的评论。