EVIEWS在计量经济学教学过程中的演示示例.doc

EVIEWS在计量经济学教学过程中的演示示例陈冬冬（川农经管）EVIEWS在计量经济学教学过程中的演示示例目的：1、正确使用EVIEWS 2、会使用OLS和WLS，Goldfeld-Quandt检验 3、能根据计算结果进行相关分析和计算实例：某市人均储蓄与人均收入的关系分析（异方差检验及补救）根据某市19781998年人均储蓄与人均收入的数据资料（见下表），其中X为人均收入（元），Y为人均储蓄（元），经分析人均储蓄受人均收入的线性影响，可建立一元线性回归模型进行分析。obsXY1978590.2000107.00001979664.9400123.00001980809.5000159.00001981875.5400189.00001982991.2500233.000019831109.950312.000019841357.870401.000019851682.800522.000019861890.580664.000019872098.250871.000019882499.5801033.00019892827.7301589.00019903084.1702209.00019913462.7102878.00019923932.5203722.00019935150.7905350.00019947153.3508080.00019959076.85011758.00199610448.2115839.00199711575.4818196.00199812500.8420954.001、用OLS估计法估计参数设模型为：运行EVIEWS软件，并输入数据，得计算结果如下：Dependent Variable: YMethod: Least SquaresDate: 10/11/05 Time: 23:10Sample: 1978 1998Included observations: 21VariableCoefficientStd. Errort-StatisticProb. C-2185.998339.9020-6.4312620.0000X1.6841580.06216627.091500.0000R-squared0.974766 Mean dependent var4533.238Adjusted R-squared0.973438 S.D. dependent var6535.103S.E. of regression1065.086 Akaike info criterion16.86989Sum squared resid21553736 Schwarz criterion16.96937Log likelihood-175.1338 F-statistic733.9495Durbin-Watson stat0.293421 Prob(F-statistic)0.0000002、异方差检验 （1）Goldfeld-Quandt检验在workfile窗口Procs菜单项选Sort series项，出现排序对话框，输入X，OK。在Sample菜单里，将时间定义为19781985，用OLS方法计算得如下结果：Y = -145.441495 + 0.3971185479*X（-8.730234） （25.42693）R-squared0.990805 Sum squared resid115.12284Dependent Variable: YMethod: Least SquaresDate: 10/11/05 Time: 23:25Sample: 1978 1985Included observations: 8VariableCoefficientStd. Errort-StatisticProb. C-145.441516.65952-8.7302340.0001X0.3971190.01561825.426930.0000R-squared0.990805 Mean dependent var255.7500Adjusted R-squared0.989273 S.D. dependent var146.0105S.E. of regression15.12284 Akaike info criterion8.482607Sum squared resid1372.202 Schwarz criterion8.502468Log likelihood-31.93043 F-statistic646.5287Durbin-Watson stat1.335534 Prob(F-statistic)0.000000在Sample菜单里，将时间定义为19911998，用OLS方法计算得如下结果：Y = -4602.367144 + 1.952519317*X（-5.065962） （18.40942）R-squared0.982604 Sum squared resid25811189.Dependent Variable: YMethod: Least SquaresDate: 10/11/05 Time: 23:29Sample: 1991 1998Included observations: 8VariableCoefficientStd. Errort-StatisticProb. C-4602.367908.4882-5.0659620.0023X1.9525190.10606118.409420.0000R-squared0.982604 Mean dependent var10847.12Adjusted R-squared0.979705 S.D. dependent var6908.102S.E. of regression984.1400 Akaike info criterion16.83373Sum squared resid5811189. Schwarz criterion16.85359Log likelihood-65.33492 F-statistic338.9068Durbin-Watson stat0.837367 Prob(F-statistic)0.000002求F统计量：，查F分布表，给定显著性水平，得临界值，比较，拒绝原假设，表明随机误差项显著的存在异方差。3、异方差的修正（1）WLS估计法。首先生成权函数,然后用OLS估计参数，Y = -2262.639946 + 1.566910934*XDependent Variable: YMethod: Least SquaresDate: 10/12/05 Time: 08:07Sample: 1978 1998Included observations: 21Weighting series: WVariableCoefficientStd. Errort-StatisticProb. C-2262.640131.2507-17.239070.0000X1.5669110.05763727.185900.0000Weighted StatisticsR-squared0.961501 Mean dependent var2183.201Adjusted R-squared0.959475 S.D. dependent var2104.209S.E. of regression423.5951 Akaike info criterion15.02583Sum squared resid3409224. Schwarz criterion15.12530Log likelihood-155.7712 F-statistic474.5211Durbin-Watson stat0.354490 Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.962755 Mean dependent var4533.238Adjusted R-squared0.960794 S.D. dependent var6535.103S.E. of regression1293.978 Sum squared resid31813191Durbin-Watson stat0.224165（2）对数变换法。用GENR生成LY和LX序列，用OLS方法求LY 对LX的回归，结果如下：LY = -6.839135503 + 1.787148637*LXDependent Variable: LYMethod: Least SquaresDate: 10/12/05 Time: 00:05Sample: 1978 1998Included observations: 21VariableCoefficientStd. Errort-StatisticProb. C-6.8391360.237565-28.788450.0000LX1.7871490.03003359.506800.0000R-squared0.994663 Mean dependent var7.195082Adjusted R-squared0.994382 S.D. dependent var1.746173S.E. of regression0.130880 Akaike info criterion