异方差实验报告

1、.附件二：实验报告格式（首页） 山东轻工业学院实验报告 成绩 课程名称 计量经济学 指导教师 苏卫东 实验日期 2013.5.18 院（系） 商学院会计系 专业班级 实验地点 实验楼二机房 学生姓名 学号 同组人 无 实验项目名称 异方差的检验 一、 实验目的和要求 3、掌握异方差性问题出现的来源、后果、检验及修正的原理，以及相关的Eviews操 作方法 4、练习检查和克服模型的异方差的操作方法。 6、用图示法、斯皮尔曼法、戈德菲尔德、white验证法，验证该模型是否存在异方差 二、 实验原理2、运用EVIEWS软件及普通最小二乘法进行模型估计3、检验模型的异方差性并对其进行调整三、 主要仪器

2、设备、试剂或材料Eviews软件、课本教材、电脑 四、 实验方法与步骤1、CREATE U 1 31 回车2、DATA Y X 回车 输入数据obsYX12648777210592103909954413110508512210979610711912740612747850313499943114269105881552211898167301295017663137791857514819196351512222116316170222880171578241271816542560419140026500201829267602122002830022201727430232105295

3、6024160028150252250321002624203250027257035250281720335002919003600030210036200312800382003、LS Y C X 回车用最小二乘法进行估计出现Dependent Variable: YMethod: Least SquaresDate: 05/18/13 Time: 11:46Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb. C-700.411116.6679-6.003460X0.08783

4、10.00482718.195750R-squared0.919464 Mean dependent var1266.452Adjusted R-squared0.916686 S.D. dependent var846.757S.E. of regression244.4088 Akaike info criterion13.8979Sum squared resid1732334 Schwarz criterion13.99042Log likelihood-213.418 F-statistic331.0852Durbin-Watson stat1.089829 Prob(F-stati

5、stic)0用普通最小二乘法进行估计，估计结果如下=700.41+0.087831Xi R2=0.92 =0.92 F=335.82 t=(-6.0) (18.2) 括号内为t统计量。(一).图示检验法分别绘制X、Y坐标系散点图，命令如下：Scat x yGenr e2=resid2Scat x e2出现可以看出，随着可支配收入x的增加，储蓄y的离散程度增加，表明随机误差项ui存在异方差性。（二）斯皮尔曼等级相关系数检验命令scat x e2sort x data x dd1（输入1-31）ls y c x 出现Dependent Variable: YMethod: Least Square

6、sDate: 05/18/13 Time: 11:34Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C-700.4110116.6679-6.0034580.0000X0.0878310.00482718.195750.0000R-squared0.919464Mean dependent var1266.452Adjusted R-squared0.916686S.D. dependent var846.7570S.E. of regression244.4088Akaike

7、 info criterion13.89790Sum squared resid1732334.Schwarz criterion13.99042Log likelihood-213.4175F-statistic331.0852Durbin-Watson stat1.943262Prob(F-statistic)0.000000sort x data x dd1ls y c x genr e1=abs(resid)sort e1 data e1 dd2genr r=1-6*sum(dd2-dd1)2)/(313-31)genr z=r*sqrt(30)出现3.326。R=0.607258 z

8、=3.326089 给定显著性水平=0.05，查正态分布表，得,因为Z=3.331.96，所以拒绝H0,接受H1,即等级相关系数是显著的，说明储蓄计量模型的随机误差项存在异方差性。(三)、Goldfeld-Quant检验命令sort x smpl 1 11 ls y c x Dependent Variable: YMethod: Least SquaresDate: 05/18/13 Time: 11:37Sample: 1 11Included observations: 11VariableCoefficientStd. Errort-StatisticProb.C-744.635119

9、5.4108-3.8106140.0041X0.0882580.0157055.6196190.0003R-squared0.778216Mean dependent var331.3636Adjusted R-squared0.753574S.D. dependent var260.8157S.E. of regression129.4724Akaike info criterion12.72778Sum squared resid150867.9Schwarz criterion12.80012Log likelihood-68.00278F-statistic31.58011Durbin

10、-Watson stat1.142088Prob(F-statistic)0.000326smpl 21 31 ls y c x Dependent Variable: YMethod: Least SquaresDate: 05/18/13 Time: 11:38Sample: 21 31Included observations: 11VariableCoefficientStd. Errort-StatisticProb.C666.3811911.25850.7312760.4832X0.0457790.0278981.6409710.1352R-squared0.230295Mean

11、dependent var2152.909Adjusted R-squared0.144772S.D. dependent var354.4462S.E. of regression327.7867Akaike info criterion14.58557Sum squared resid966997.0Schwarz criterion14.65791Log likelihood-78.22063F-statistic2.692786Durbin-Watson stat2.743586Prob(F-statistic)0.135222.记下第一个残差平方和：150867.9 记下第二个残差平

12、方和：966997.0。计算F=6.41，给定显著性水平=0.05，查F分布表V1=V2=11-2=9,F0.05(9,9)=3.18,因为F=6.413.18，所以接受备择假设，即储蓄计量模型的随机误差项存在异方差性。(四).White检验命令smpl 21 31 ls y c x smpl 1 31 ls y c x出现Dependent Variable: YMethod: Least SquaresDate: 05/18/13 Time: 11:41Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-S

13、tatisticProb.C-700.4110116.6679-6.0034580.0000X0.0878310.00482718.195750.0000R-squared0.919464Mean dependent var1266.452Adjusted R-squared0.916686S.D. dependent var846.7570S.E. of regression244.4088Akaike info criterion13.89790Sum squared resid1732334.Schwarz criterion13.99042Log likelihood-213.4175

14、F-statistic331.0852Durbin-Watson stat1.943262Prob(F-statistic)0.000000White Heteroskedasticity Test:F-statistic5.819690Probability0.007699Obs*R-squared9.102584Probability0.010554Test Equation:smpl 1 31 ls y c xDependent Variable: RESID2Method: Least SquaresDate: 05/18/13 Time: 11:44Sample: 1 31Inclu

15、ded observations: 31VariableCoefficientStd. Errort-StatisticProb.C19975.9882774.930.2413290.8111X-2.1986328.094419-0.2716230.7879X20.0001460.0001760.8300460.4135R-squared0.293632Mean dependent var55881.73Adjusted R-squared0.243177S.D. dependent var77875.67S.E. of regression67748.39Akaike info criter

16、ion25.17675Sum squared resid1.29E+11Schwarz criterion25.31553Log likelihood-387.2397F-statistic5.819690Durbin-Watson stat2.580140Prob(F-statistic)0.007699因为TR2=310.2936=9.1，所以结论是该回归模型中存在异方差.其中obs*R-squared等于9.102584表示的就是统计量TR2的值。(五)克服异方差命令smpl 1 31 ls y c x Dependent Variable: YMethod: Least Squares

17、Date: 05/18/13 Time: 11:51Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C-700.4110116.6679-6.0034580.0000X0.0878310.00482718.195750.0000R-squared0.919464Mean dependent var1266.452Adjusted R-squared0.916686S.D. dependent var846.7570S.E. of regression244.4088Akaike

18、info criterion13.89790Sum squared resid1732334.Schwarz criterion13.99042Log likelihood-213.4175F-statistic331.0852Durbin-Watson stat1.943262Prob(F-statistic)0.000000genr ww=1/abs(resid)ls (w=1/x) y c xDependent Variable: YMethod: Least SquaresDate: 05/18/13 Time: 12:01Sample: 1 31Included observations: 31VariableCoeffi