实验三 SPSS 多元时间序列分析方法

实验三多元时间序列分析方法

1.实验目的

了解协整理论及协整检验方法；掌握协整的两种检验方法：E-G两步法与Johansen方法；熟悉向量自回归模型VAR的应用；掌握误差修正模型ECM的含义及检验方法；掌握Granger因果关系检验方法。

2.实验仪器

装有EViews7.0软件的微机一台。

3.实验内容

【例6-2】

时间与M2之间的关系首先用单位根检验是否为平稳序列。原假设为H0：非平稳序列H1：平稳序列。用Eviews软件解决该问题，得到如下结果：Null Hypothesis: M2 has a unit root

Exogenous: None

Lag Length: 3 (Automatic - based on SIC, maxlag=13)

t-Statistic Prob.* Augmented Dickey-Fuller test statistic 5.681169 1.0000

Test critical

values: 1% level -2.579052

5% level -1.942768

10% level -1.615423

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test Equation Dependent Variable: D(M2)

Method: Least Squares

Date: 04/16/13 Time: 10:36

Sample (adjusted): 1991M05 2005M01 Included observations: 165 after adjustments

Variable Coefficien

t Std. Error t-Statistic Prob.

M2(-1) 0.013514 0.002379 5.681169 0.0000 D(M2(-1)) -0.490280 0.074458 -6.584611 0.0000 D(M2(-2)) 0.070618 0.083790 0.842797 0.4006 D(M2(-3)) 0.387086 0.073788 5.245935 0.0000

R-squared 0.480147 Mean dependent

var 1440.03

7

Adjusted

R-squared 0.470461 S.D. dependent var 1509.48

9

S.E. of regression 1098.447 Akaike info criterion 16.8651

3

Sum squared resid 1.94E+08 Schwarz criterion 16.9404

2

Log likelihood -1387.373 Hannan-Quinn

criter. 16.8956

9

Durbin-Watson

stat 1.965242

从上图我们可以看出t-statistic的值是5.681169，大于临界值，p>a，故不能拒绝被检验的指数序列是非平稳的原假设。因此一阶差分序列进行ADF检验，结果如下图显示。

Null Hypothesis: D(M2) has a unit root

Exogenous: None

Lag Length: 8 (Automatic - based on SIC, maxlag=13)

t-Statistic Prob.* Augmented Dickey-Fuller test statistic 0.988183 0.9143

Test critical

values: 1% level -2.579587

5% level -1.942843

10% level -1.615376

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test Equation Dependent Variable: D(M2,2)

Method: Least Squares

Date: 04/16/13 Time: 10:37

Sample (adjusted): 1991M11 2005M01 Included observations: 159 after adjustments

Variable Coefficien

t Std. Error t-Statistic Prob.

D(M2(-1)) 0.053616 0.054257 0.988183 0.3247 D(M2(-1),2) -1.526069 0.096352 -15.83852 0.0000 D(M2(-2),2) -1.519649 0.149134 -10.18981 0.0000 D(M2(-3),2) -1.225623 0.184003 -6.660869 0.0000 D(M2(-4),2) -1.237445 0.196285 -6.304319 0.0000 D(M2(-5),2) -0.972024 0.197161 -4.930093 0.0000 D(M2(-6),2) -0.810098 0.185290 -4.372060 0.0000 D(M2(-7),2) -0.605069 0.144997 -4.172983 0.0001 D(M2(-8),2) -0.333781 0.080550 -4.143781 0.0001

R-squared 0.801713 Mean dependent

var 16.0700

1

Adjusted 0.791137 S.D. dependent var 2352.91