实验三 SPSS 多元时间序列分析方法

1、实验三多元时间序列分析方法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。实验仪器装有EViews7.0软件的微机一台。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Eview s软件解决该问题，得到如下结果：Null Hypothesis: M2 has a unit rootExogenous: NoneLag Length: 3 (Automatic - b

2、ased on SIC, maxlag=13)t-Statistic Prob.*Augmented Dickey-Fuller test statistic 5.681169 1.0000Test criticalvalues:1% level-2.5790525% level-1.94276810% level-1.615423*MacKinnon (1996) one-sided p-values.Augmented Dickey-Fuller Test EquationDependent Variable: D(M2)Method: Least SquaresDate: 04/16/1

3、3 Time: 10:36Sample (adjusted): 1991M05 2005M01Included observations: 165 after adjustmentsCoefficienVariabletStd. Error t-StatisticProb.M2(-1)0.0135140.002379 5.6811690.0000D(M2(-1)-0.4902800.074458 -6.5846110.0000D(M2(-2)0.0706180.083790 0.8427970.4006D(M2(-3)0.3870860.073788 5.2459350.0000Mean de

4、pendent 1440.03R-squared0.480147var7Adjusted1509.48R-squared0.470461 S.D. dependent var916.8651S.E. of regression 1098.447 Akaike info criterionSum squared resid 1.94E+08 Schwarz criterion2Hannan-Quinn16.8956Log likelihood -1387.373criter.9Durbin-Watsonstat1.965242从上图我们可以看出t-statistic的值是5.681169，大于临

5、界值，pa，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 rootExogenous: NoneLag Length: 8 (Automatic - based on SIC, maxlag=13)t-Statistic Prob.MacKinnon (1996) one-sided p-values.Augmented Dickey-Fuller test statistic 0.988183 0.9143Test criticalvalues:1% level-2.5795

6、875% level-1.94284310% level-1.615376Augmented Dickey-Fuller Test EquationDependent Variable: D(M2,2)Method: Least SquaresDate: 04/16/13Time: 10:37Sample (adjusted): 1991M11 2005M01Included observations: 159 after adjustmentsCoefficienVariablet Std. Error t-Statistic Prob.D(M2(-1)0.053616 0.054257 0

7、.988183 0.3247D(M2(-1),2)-1.526069 0.096352 -15.83852 0.0000D(M2(-2),2)-1.519649 0.149134 -10.18981 0.0000D(M2(-3),2)-1.225623 0.184003 -6.660869 0.0000D(M2(-4),2)-1.237445 0.196285 -6.304319 0.0000D(M2(-5),2)-0.972024 0.197161 -4.930093 0.0000D(M2(-6),2)-0.810098 0.185290 -4.372060 0.0000D(M2(-7),2

8、)-0.605069 0.144997 -4.172983 0.0001D(M2(-8),2)-0.333781 0.080550 -4.143781 0.0001Mean dependent 16.0700R-squared0.801713var1Adjusted0.791137 S.D. dependent var 2352.91R-squared16.8535S.E. of regression 1075.320 Akaike info criterion 617.0272Sum squared resid 1.73E+08 Schwarz criterion7Hannan-Quinn1

9、6.9241Log likelihood -1330.858criter.0Durbin-Watsonstat1.970407从上图我们可以看出t-statistic的值是0.988183，大于临界值，pa，故不能 拒绝被检验的指数序列是非平稳的原假设。因此二阶差分序列进行ADF检验，结 果如下图显示Null Hypothesis: D(M2,2) has a unit rootExogenous: NoneLag Length: 7 (Automatic - based on SIC, maxlag=13)t-Statistic Prob.*Augmented Dickey-Fuller t

10、est statistic -9.223132 0.0000Test criticalvalues:1% level-2.5795875% level-1.94284310% level-1.615376*MacKinnon (1996) one-sided p-values.Augmented Dickey-Fuller Test EquationDependent Variable: D(M2,3)Method: Least SquaresDate: 04/16/13 Time: 10:38Sample (adjusted): 1991M11 2005M01Included observa

11、tions: 159 after adjustmentsCoefficienVariabletStd. Errort-StatisticProb.D(M2(-1),2)-8.9007550.965047-9.2231320.0000D(M2(-1),3)6.4311290.9246726.9550380.0000D(M2(-2),3)4.9702860.8335415.9628610.0000D(M2(-3),3)3.8024320.7007735.4260550.0000D(M2(-4),3)2.6170580.5445964.8055010.0000D(M2(-5),3)1.6882010

12、.3805594.4361090.0000D(M2(-6),3)0.9109680.2149904.2372570.0000D(M2(-7),3)0.3259340.0801514.0664870.0001R-squared0.941321 Mean dependent 0.11205varAdjusted4339.32 TOC o 1-5 h z R-squared0.938601S.D. dependent var416.8474S.E. of regression1075.236Akaike info criterion717.0018Sum squared resid1.75E+08S

13、chwarz criterion8Hannan-Quinn 16.9101Log likelihood -1331.374criter.8Durbin-Watsonstat1.963915从上图我们可以看出t-statistic的值是-9.223132，小于临界值，pa，故拒 绝被检验的指数序列是平稳的原假设。Date: 04/16/13 Time: 10:09 Sample: 1991 M01 2005M01 Included observations: 167AutocorrelationPartiaKCorrelationAC PAC Q-Stat Prob111.11 -0.701 -

14、0.701 33:437 0.0002 0.141 -0.688 06.814 0.000113 0.277 -0.143 100.04 0.0001114 -0.453 -0.95 135.53 0.00011匚15 0 371 -0.224 159.50 0.0005：1匚16 -0.135 -0.156 162.69 0.000IE1ir11 -0.005 -0.095 163.97 0.0001IZZ1S 0.143 -0.304 167.59 0.000111pi9 -0.010 0.052 167.61 0.00012111110 -0.14 0.029 171.24 0.0001

15、C111 0.143 -0.U1 174.96 0.000111112： -0.011 -0.015 174.98 0.000a ,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(X) has a unit rootExogenous: NoneLag Length: 0 (Automatic - based on SIC, maxlag=20)t-Statistic Prob.*Augmented Dickey-Fuller test statistic -29.94678 0.0000Test criti

16、calvalues:1% level-2.5675785% level-1.94118110% level-1.616459*MacKinnon (1996) one-sided p-values.Augmented Dickey-Fuller Test EquationDependent Variable: D(X,2)Method: Least SquaresDate: 04/16/13 Time: 10:54Sample (adjusted): 1/06/2003 9/14/2006Included observations: 885 after adjustmentsCoefficie

17、nVariablet Std. Error t-Statistic Prob.-1.007165 0.033632 -29.94678 0.0000Mean dependent -1.13E-0 TOC o 1-5 h z R-squared0.503597var5Adjusted0.06330R-squared0.503597 S.D. dependent var2-3.38104S.E. of regression 0.044600 Akaike info criterion 1-3.37563Sum squared resid 1.758410 Schwarz criterion3Han

18、nan-Quinn-3.37897Log likelihood1497.111criter.4Durbin-Watsonstat1.999816从上图我们可以看出t-statistic的值是-29.94678，远小于临界值，pa，故拒绝被检验的指数序列是平稳的原假设。Date: 04/16/13 Time: 10:57Sample: 1/02/2003 9/1 4/2006Included observations: 386AutocorrelationPartial CorrelationAGPACQ-StatProb11111-0.007-0.0070.04730.827111120.01

19、?0.0130.19390.90SII1i13-0.025-0.0250.75010.861111140.0030.002.0.75600.94411115-0.009-0.0090.33720.97511116-0.013-0.0140.98890.93611117-0.020-0.0201:35190.9S7II1II1.0-0.029-0.0292.08460.97311)90.0470.0474.10110.S05111II100.0240.0254.63260.91411110.0970.09513.1430.2341II1II120.0300.03313.9510.04111113

20、0.0150.01314.1450.3641II1II140.0340.03815.1630.-367(1(115-0.063-0.06210.7190；227111116-0.020-0.01819.0690.265II11117-0.027-0.01919.7450.20711100.0660.067216510.167II1i119-0.035-0.02924.7800.1631)1)洒0.0550.04627.522.0.1211II1II210.0340.03323.6030.1.2411II122-0.018-0.03528.9040.1431110.0660.055318450.

21、0S4111124-0.015-0.01533.0520.1031111250.0090.00633.1340.123(1II12&-0.052：-0.03435.6440.09SII1II127-0.030-0.03136.4760.1051(128-0.066-0.05740.490O.OSO1If.11.淬0.0340.02441.5700.0611111300.0100.00841.6800.0761II11制0.0250.01542.2510.0061II11320.0260.00942.8860.0951II1II330.0260.03343.5000.1041111340.0190.00043.8500.120II11135-0.025-0.02144g0.1321110.0490.05546.6760.110Dependent Variable: XMethod