《计量经济学》李子奈第三版课后习题Eviews实验报告30页精选文档.docx

1、计量经济学李子奈第三版课后习题Eviews实验报告30页精选文档计量经济学实验报告实验一：EViews5.0软件安装及基本操作1.Eviews5.0的安装过程男人看完这些文章还没过隐吗？请速度看下面的男人推荐精彩文章 注：下载原文后点及连接进入，不下载无法观看少妇*女主播*玩车震，一晚17次*姿势诱人，原来是因为。（点此进入 男人必看）卖爆了，堪称装逼国产iPhone6顶极高配神机万众期待，顶级配置卖爆了！（苹果） 一夜七次郎从此不再是神话！娱乐圈只用不说的秘密.男人的加油站 | 一战到底，性福不停歇！用玛卡，还需要什么甜言蜜语！【警惕】千万别让你的情敌先吃了“玛卡”！否则宝马车都留不住她！那

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3、文件”和“eviews5.exe文件”到安装目录下；双击“Eviews5.reg”进行注册，安装完毕。2.基本操作（数据来源于李子奈版课后习题P61.12）运行Eviews,依次单击filenewwork fileunstructedobservation 31。命令栏中输入“data y gdp”，打开“y gdp”表，接下来将数据输入其中。做出“y gdp”的散点图，依次单击quickgraphscattergdp y。结果如下：开始进行LS回归：命令栏中输入“ls y c gdp”回车，即得到回归结果如下：Dependent Variable: YMethod: Least Square

4、sDate: 12/11/11 Time: 09:38Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C-10.3934186.05105-0.1207820.9047GDP0.0710320.0074069.5912490.0000R-squared0.760315Mean dependent var621.0548Adjusted R-squared0.752050S.D. dependent var619.5803S.E. of regression308.5175Akai

5、ke info criterion14.36377Sum squared resid2760308.Schwarz criterion14.45629Log likelihood-220.6385F-statistic91.99205Durbin-Watson stat1.570581Prob(F-statistic)0.000000回归方程为：Y = -10.39340931 + 0.07103165248*GDP对回归方程做检验：斜率项t值9.59大于t在5%显著水平下的检验值2.045，拒绝零假设；截距项t值0.121小于2.045，接受零假设。可决系数0.76，拟合较好，方程F检验值9

6、1.99通过F检验。下面进行预测：拓展工作空间：打开work file窗口，单击 ProcStructure，将End date的数据3132；确定预测值的起止日期：打开work file窗口，点击QuickSample,填入“1 32”。打开GDP数据表，在GDP的最下方填，按回车键。在出现的Equation界面，点击Forecast出现相应界面如下：双击YF，得到y32=593.3756，预测完毕。实验二：回归模型的建立与检验（数据来源于李子奈版课后习题P105.11）运行Eviews,依次单击filenewwork fileunstructedobservation 10。命令栏中输入“

7、data y x1 x2”，打开“y x1 x2”表，接下来将数据输入其中。开始进行LS回归：命令栏中输入“ls y c x1 x2”回车，即得到回归结果：Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 10:17Sample: 1 10Included observations: 10VariableCoefficientStd. Errort-StatisticProb.C626.509340.1301015.611950.0000X1-9.7905703.197843-3.0616170.0183X20.028

8、6180.0058384.9020300.0017R-squared0.902218Mean dependent var670.3300Adjusted R-squared0.874281S.D. dependent var49.04504S.E. of regression17.38985Akaike info criterion8.792975Sum squared resid2116.847Schwarz criterion8.883751Log likelihood-40.96488F-statistic32.29408Durbin-Watson stat1.650804Prob(F-

9、statistic)0.000292估计方程：依次单击viewrepresentations，得到回归方程为: Y = 626.5092847 - 9.790570097*X1 + 0.02861815879*X2，参数估计完毕。直接查看结果计算得到随机干扰项的方差值为2116.847/（10-2-1）=309.55，可决系数为0.902，修正后的可决系数为0.874。F=32.2945%显著水平下的F值4.74，即方程通过F检验；两个参数的t检验值均通过了5%显著水平下的t检验值2.365。下面进行预测：拓展工作空间：打开work file窗口，单击 ProcStructure，将End d

10、ate的数据1011；确定预测值的起止日期：打开work file窗口，点击QuickSample,填入“1 11”。在x1的最下方填入35，在x2的最下方填入20000，按回车键。在出现的Equation界面，点击Forecast出现相应界面如下：双击YF,得到y11=856.2025，预测完毕。实验三：异方差、自相关、多重共线性的检验1.异方差检验（数据来源于李子奈版课后习题P154.8）运行Eviews,依次单击filenewwork fileunstructedobservation 20。命令栏中输入“data y x”，打开“y x”表，接下来将数据输入其中。开始进行LS回归，命令

11、栏中输入“ls y c x”回车，即得到回归结果如下：Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 10:38Sample: 1 20Included observations: 20VariableCoefficientStd. Errort-StatisticProb.C272.3635159.67731.7057130.1053X0.7551250.02331632.386900.0000R-squared0.983129Mean dependent var5199.515Adjusted R-squared

12、0.982192S.D. dependent var1625.275S.E. of regression216.8900Akaike info criterion13.69130Sum squared resid846743.0Schwarz criterion13.79087Log likelihood-134.9130F-statistic1048.912Durbin-Watson stat2.087986Prob(F-statistic)0.000000回归方程为：Y = 272.3635389 + 0.7551249391*X开始检验异方差图示法：在工作文件窗口按Genr,在主窗口键入

13、命令e2=resid2，依次单击QuickGraphScatter可得散点图：显然，散点不在一条水平直线上，即说明存在异方差性。White检验法:依次单击ViewResidual TestsWhite Heteroskedasticity因为本题为一元函数，故无交叉乘积项，选no cross terms。经估计出现white检验结果，如下图：White Heteroskedasticity Test:F-statistic14.63595Probability0.000201Obs*R-squared12.65213Probability0.001789Test Equation:Depend

14、ent Variable: RESID2Method: Least SquaresDate: 12/11/11 Time: 11:16Sample: 1 20Included observations: 20VariableCoefficientStd. Errort-StatisticProb.C-180998.9103318.2-1.7518580.0978X49.4284628.939291.7080060.1058X2-0.0021150.001847-1.1447420.2682R-squared0.632606Mean dependent var42337.15Adjusted R

15、-squared0.589384S.D. dependent var45279.67S.E. of regression29014.92Akaike info criterion23.52649Sum squared resid1.43E+10Schwarz criterion23.67585Log likelihood-232.2649F-statistic14.63595Durbin-Watson stat2.081758Prob(F-statistic)0.000201所以拒绝原假设，表明模型存在异方差。 Goldfeld-Quanadt检验法：在命令栏中直接输入：sort x，得到按照

16、升序排列的x。开始取样本，依次单击quicksample，填入“1 8”，回归模型ls y c x；得到如下结果：Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 11:26Sample: 1 8Included observations: 8VariableCoefficientStd. Errort-StatisticProb.C1277.1611540.6040.8290000.4388X0.5541260.3114321.7792870.1255R-squared0.345397Mean dependent v

17、ar4016.814Adjusted R-squared0.236296S.D. dependent var166.1712S.E. of regression145.2172Akaike info criterion13.00666Sum squared resid126528.3Schwarz criterion13.02652Log likelihood-50.02663F-statistic3.165861Durbin-Watson stat3.004532Prob(F-statistic)0.125501继续取样本，依次单击quicksample，填入“13 20”，回归模型ls y

18、 c x；得到如下结果：Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 11:28Sample: 13 20Included observations: 8VariableCoefficientStd. Errort-StatisticProb.C212.2118530.88920.3997290.7032X0.7618930.06034812.625050.0000R-squared0.963723Mean dependent var6760.477Adjusted R-squared0.957676S.D. de

19、pendent var1556.814S.E. of regression320.2790Akaike info criterion14.58858Sum squared resid615472.0Schwarz criterion14.60844Log likelihood-56.35432F-statistic159.3919Durbin-Watson stat1.722960Prob(F-statistic)0.000015计算F统计量：F=RSS2/RSS1=615472.0/126528.3=4.864；F=4.864 F0.05（6,6）=4.28，拒绝原假设，表明模型确实存在异方

20、差性。异方差的修正：在对原模型进行OLS后，单击QuickGenerate Series,在弹出的对话框内输w1=1/e,w2=1/e2。再选择QuickEstimate Equation,在弹出的对话框中选择Options按钮，在出现的画面中，选中Weight Ls/TLS复选框，在 Weight内分别输入“w1”，“w2”，分别得下图：Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 11:33Sample: 1 20Included observations: 20Weighting series: W1Vari

21、ableCoefficientStd. Errort-StatisticProb.C415.6603116.97913.5532880.0023X0.7290260.02242932.503490.0000Weighted StatisticsR-squared0.999895Mean dependent var4471.606Adjusted R-squared0.999889S.D. dependent var7313.160S.E. of regression77.04831Akaike info criterion11.62138Sum squared resid106856.0Sch

22、warz criterion11.72096Log likelihood-114.2138F-statistic1056.477Durbin-Watson stat2.367808Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.981664Mean dependent var5199.515Adjusted R-squared0.980645S.D. dependent var1625.275S.E. of regression226.1101Sum squared resid920263.9Durbin-Watson stat

23、1.886959Dependent Variable: YMethod: Least SquaresDate: 12/11/11 Time: 11:34Sample: 1 20Included observations: 20Weighting series: W2VariableCoefficientStd. Errort-StatisticProb.C117.0597134.71860.8689200.3963X0.7869760.02605830.200730.0000Weighted StatisticsR-squared0.999999Mean dependent var4207.5

24、16Adjusted R-squared0.999999S.D. dependent var15774.21S.E. of regression15.35992Akaike info criterion8.396039Sum squared resid4246.688Schwarz criterion8.495613Log likelihood-81.96039F-statistic912.0839Durbin-Watson stat2.113659Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.980281Mean depen

25、dent var5199.515Adjusted R-squared0.979185S.D. dependent var1625.275S.E. of regression234.4844Sum squared resid989692.9Durbin-Watson stat1.836717经估计发现用w2=1/e2作为合适的权。再检验：单击QuickGenerate Series，分别输入x1=x*w2,y1=y*w2,按住ctrl,依次点击x1,y1，右键选择Open as group，依次单击QuickGraph可得下图：由该图可知，加权后X和Y的散点图在同一直线上，所以是同方差性。2.自相关检验（数据来源于李子奈版课后习题P155.9）运行Eviews,依次单击filenewwork fileAnnualstrat1980 end2007。命令栏中输入“data y x”，打开