计量经济学模型
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通货膨胀影响因素计量分析
我国价格指数P，职工平均工资W（元），国内生产总值Y（亿元），全社会固定资产投资总值Y1(亿元)，当年全国总的失业率E2，通过对样本值的估算，考察其他因素对价格指数（即通货膨胀情况）的影响，1979年－2002年样本观测值如下：
P W Y Y1 E2
102 668 3624.1 745.9 0.0136564723985
106 762 4038.2 667.51 0.012633149197
102.4 772 4517.8 845.31 0.00996264009963
101.9 798 4860.3 1230.4 0.00829793755747
101.5 826 5301.8 1430.06 0.00580212816066
102.8 974 5957.4 1832.87 0.00487271075506
108.8 1148 7206.7 2543.2 0.00476931673052
106 1329 8989.1 3120.6 0.00512163892446
107.3 1459 10201.4 3791.7 0.00522050508858
118.5 1749 11954.5 4753.8 0.00541826835072
118 1935 14922.3 4410.4 0.00678550271959
103.1 2140 16917.8 4517 0.00878710408279
103.4 2340 18598.4 5594.5 0.00907839191418
106.4 2711 21662.5 8080.1 0.00943367973406
114.7 3371 26651.9 13072.3 0.00978241536729
124.1 4538 34560.5 17042.1 0.00998018639466
117.1 5500 46670 20019.3 0.0114733861012
108.3 6210 57494.9 22974 0.0116820755393
102.8 6470 66850.5 22913.5 0.0138418079096
99.2 7479 73142.7 24941.1 0.0201145837668
98.6 8346 76967.2 28406.2 0.0191919330686
100.4 9371 80579.4 29854.7 0.0257730565467
100.7 10870 88254 32917.7 0.0189031599312
99.2 12422 95727.9 37213.5 0.0214968152866
1、 建立模型：
2413210EYYWP
2、 先估计原模型，得到如下结果：
Dependent Variable: P
Method: Least Squares
Date: 06/23/04 Time: 20:31
Sample: 1979 2002
Included observations: 24
Variable Coefficient Std. Error t-Statistic Prob.
C 112.9413 2.521478 44.79170 0.0000
W -0.002580 0.002278 -1.132503 0.2715
Y -0.000883 0.000294 -3.003207 0.0073
Y1 0.003136 0.000768 4.081272 0.0006 E2 -512.3672 350.5272 -1.461705 0.1602
R-squared 0.614042 Mean dependent var 106.3833
Adjusted R-squared 0.532787 S.D. dependent var 7.060525
S.E. of regression 4.826077 Akaike info criterion 6.168997
Sum squared resid 442.5294
Schwarz criterion 6.414425
Log likelihood -69.02796 F-statistic 7.557031
Durbin-Watson stat 1.314405 Prob(F-statistic) 0.000807
3、 异方差的检验
通过WHITE检验来实现在原模型上的异方差的检验，结果如下：
White Heteroskedasticity Test:
F-statistic 0.269434 Probability 0.985907
Obs*R-squared 7.088114 Probability 0.931262
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 06/23/04
Time: 20:36
Sample: 1979 2002
Included observations: 24
Variable Coefficient Std. Error t-Statistic Prob.
C 28.94473 158.7409 0.182339 0.8594
W 0.238799 0.332782 0.717584 0.4912
W^2 4.28E-05 0.000203 0.210525 0.8379
W*Y 3.42E-07 1.72E-05 0.019912 0.9845
W*Y1 -1.64E-05 0.000102 -0.160437 0.8761
W*E2 -32.85953 30.76633 -1.068036 0.3133
Y 0.013687 0.039546 0.346117 0.7372
Y^2 3.80E-07 8.65E-07 0.439086 0.6710
Y*Y1 -2.24E-06 7.00E-06 -0.320569 0.7559
Y*E2 -1.063647 2.182985 -0.487244 0.6377
Y1 -0.096841
0.073574 -1.316230 0.2206
Y1^2 4.36E-06 1.09E-05 0.399162 0.6991
Y1*E2 11.11194 10.26995 1.081987 0.3074
E2 -20145.84 23709.81 -0.849684 0.4175
E2^2 1908982. 1875482. 1.017862 0.3353
R-squared 0.295338 Mean dependent var 18.43873
Adjusted R-squared
-0.800803 S.D. dependent var 35.37338
S.E. of regression 47.46895 Akaike info criterion 10.82720
Sum squared resid 20279.71 Schwarz criterion 11.56348
Log likelihood -114.9264 F-statistic 0.269434
Durbin-Watson stat 1.734882 Prob(F-statistic) 0.985907
由此可见，685.23)14(7.088114205.02nR，所以不存在异方差。 4、 自相关的检验
由上可知，DW＝1.314405，而当T=24,K=4时，dl＝10.1 du=1.78，所以DW检验不能确定自相关。故选用其他的检验方法——BG检验，结果如下
Dependent Variable: U
Method: Least Squares
Date: 06/23/04 Time: 21:09
Sample(adjusted): 1981 2002
Included observations: 22 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
U(-1) 0.497295 0.202575 2.454873 0.0268
U(-2) -0.321097 0.207111 -1.550361 0.1419
C -1.254104 2.574213 -0.487179 0.6332
W -0.004071 0.002261 -1.800307 0.0920
Y -0.000537 0.000304 -1.763203 0.0982
Y1 0.002449 0.000779 3.143750 0.0067
E2 430.5368 451.9385 0.952645 0.3559
R-squared 0.627584 Mean dependent var -0.180493
Adjusted R-squared 0.478618 S.D. dependent var 6.240318
S.E. of regression 4.505932 Akaike info criterion 6.102038
Sum squared resid 304.5514 Schwarz criterion 6.449188
Log likelihood -60.12242 F-statistic 4.212932
Durbin-Watson stat 1.818982 Prob(F-statistic)
0.011072
又因为841.3)1(806848.13205.02nR，认为u存在一阶自相关。下面我们采用DW统计量来求自相关系数，2/1^DW=1-1.3144/2=0.3428，然后用差分估计法，做如下变换，P1=P-0.3428*P(-1)
W1=W-0.3428*W(-1)
Y2=Y-0.3428*Y(-1)
Y3=Y1-0.3428*Y1(-1)
得到的估计结果如下，
Dependent Variable: P1
Method: Least Squares
Date: 06/28/04 Time: 17:15
Sample(adjusted): 1980 2002
Included observations: 23 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 73.43472 2.081378 35.28179
0.0000
W1 -0.002514 0.002768 -0.908036 0.3759
Y2 -0.000915 0.000340 -2.692451 0.0149
