计量经济学上机模型分析方法总结一、随机误差项的异方差问题的检验与修正
模型一：
Dependent Variable: LOG(Y)
Method: Least Squares
Date: 07/29/12 Time: 09:03
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 1.602528 0.860978 1.861288 0.0732
LOG(X1) 0.325416 0.103769 3.135955 0.0040
LOG(X2) 0.507078 0.048599 10.43385 0.0000
R-squared 0.796506 Mean dependent var 7.448704 Adjusted R-squared 0.781971 S.D. dependent var 0.364648 S.E. of regression 0.170267 Akaike info criterion -0.611128 Sum squared resid 0.811747 Schwarz criterion -0.472355 Log likelihood 12.47249 F-statistic 54.79806 Durbin-Watson stat 1.964720 Prob(F-statistic) 0.000000
（一）异方差的检验
1、GQ检验法
模型二：
Dependent Variable: LOG(Y)
Method: Least Squares
Date: 07/29/12 Time: 09:19
Sample: 1 12
Included observations: 12
Variable Coefficient Std. Error t-Statistic Prob.
C 3.744626 1.191113 3.143804 0.0119
LOG(X1) 0.344369 0.082999 4.149077 0.0025
LOG(X2) 0.168904 0.118844 1.421228 0.1890
R-squared 0.669065 Mean dependent var 7.239161 Adjusted R-squared 0.595524 S.D. dependent var 0.133581 S.E. of regression 0.084955 Akaike info criterion -1.881064 Sum squared resid 0.064957 Schwarz criterion -1.759837 Log likelihood 14.28638 F-statistic 9.097834 Durbin-Watson stat 1.810822 Prob(F-statistic) 0.006900
模型三：
Dependent Variable: LOG(Y)
Method: Least Squares
Date: 07/29/12 Time: 09:20
Sample: 20 31
Included observations: 12
Variable Coefficient Std. Error t-Statistic Prob.
C -0.353381 1.607461 -0.219838 0.8309
LOG(X1) 0.210898 0.158220 1.332942 0.2153
LOG(X2) 0.856522 0.108601 7.886856 0.0000
R-squared 0.878402 Mean dependent var 7.769851
Adjusted R-squared 0.851381 S.D. dependent var 0.390363
S.E. of regression 0.150490 Akaike info criterion -0.737527
Sum squared resid 0.203824 Schwarz criterion -0.616301
Log likelihood 7.425163 F-statistic 32.50732
Durbin-Watson stat 2.123203 Prob(F-statistic) 0.000076
进行模型二和模型三两次回归，目的仅是得到出去中间7个样本点以后前后各12个样本点的残差平方和RSS1和RSS2，然后用较大的RSS除以较小的RSS即可求出F统计量值进行显著性检验。
2、怀特检验法（White）
模型一的怀特残差检验结果：
White Heteroskedasticity Test:
F-statistic 4.920995 Probability 0.004339
Obs*R-squared 13.35705 Probability 0.009657
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 05/29/13 Time: 09:04
Sample: 1 31
Included observations: 31
Variable Coefficient Std. Error t-Statistic Prob.
C 3.982137 2.882851 1.381319 0.1789
LOG(X1) -0.579289 0.916069 -0.632364 0.5327
(LOG(X1))^2 0.041839 0.066866 0.625710 0.5370
