自相关的检验与修正.doc

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 实验日期 2013-5-25 院（系） 商学院 专业班级 实验地点 二机房 学生姓名 学号 同组人 无 实验项目名称 自相关的检验与修正 一、 实验目的和要求 掌握Eviews软件的操作和自相关的检验与修正二、 实验原理 Eviews软件的操作和自相关的检验与修正，图表法，DW检验，运用迭代法三、 主要仪器设备、试剂或材料 Eviews软件，计算机四、 实验方法与步骤 （1）准备工作：建立工作文件，并输入数据： CREATE EX-6-1 A 1978 2000; TATA CINSUM INCOME PRICE; (2)相关图分析： GENR Y=CONSUM/PRICE; GENR X=INCOME/PRICE; SCAT X Y; LS Y C X; (3)自相关检验 1）图示法 LINR RESID; SCAT RESID(-1) RESID; 2)观察结果窗口，由DW统计量，查表，与DL,DU比较得出结论； 3）LM检验 在方程窗口中点击Viewresidual test series correlation LM test; (4)自相关的修正 GENR GDY=Y-0.7*Y(-1); GENR GDX=X-0.7*X(-1); LS GDY C GDX; (5)再次检验自相关是否存在，用1),2),3）之一检验； 五、 实验数据记录、处理及结果分析 （1）建立工作组，输入数据如下： 1978344.88388.3211979385.2425.41.011980474.72526.921.0621981485.88539.521.0751982496.56576.721.0811983520.84604.311.0861984599.64728.171.0161985770.64875.521.251986949.081069.611.33619871071.041187.491.42619881278.871329.71.66719891291.091477.771.91219901440.471638.921.9719911585.711844.982172238.382.41819932322.192769.262.84419943301.373982.133.52619954064.14929.534.06619964679.615967.714.43219975204.296608.564.56919985471.017110.544.54619995851.537649.834.49620006121.078140.554.478（2）相关图分析 Scat x y,得到关于X和Y的散点图如下： 从上图可知，X和Y存在线性关系。再者，Eviews 估计结果如下图： Dependent Variable: YMethod: Least SquaresDate: 05/25/13 Time: 10:47Sample: 1978 2000Included observations: 23VariableCoefficientStd. Errort-StatisticProb.C112.608116.974476.6339660.0000X0.7108740.01679042.339840.0000R-squared0.988421Mean dependent var771.4916Adjusted R-squared0.987870S.D. dependent var295.2138S.E. of regression32.51395Akaike info criterion9.884157Sum squared resid22200.30Schwarz criterion9.982896Log likelihood-111.6678F-statistic1792.662Durbin-Watson stat0.582546Prob(F-statistic)0.000000得到估计的回归方程： (6.5) (42.1) R2 =0.9883 s.e=32.8 DW=0.60 T=23 回归方程拟合得效果比较好，但是DW值比较低。（3）自相关检验1）图示法： 由scat resid(-1) resid 得到下图：由上图可知，方程存在序列相关性。2）已知DW=0.60，若给定a=0.05,查表得DW临界值 dL=1.26，dU=1.44 。因为DW=0.061.26，认为误差项存在严重自相关。3）LM检验 Breusch-Godfrey Serial Correlation LM Test:F-statistic7.584071Probability0.003791Obs*R-squared10.21031Probability0.006065Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 05/25/13 Time: 10:54Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.C3.90350913.386240.2916060.7737X-0.0056610.013323-0.4249120.6757RESID(-1)0.5966480.2317782.5742270.0186RESID(-2)0.1405640.2365540.5942150.5594R-squared0.443926Mean dependent var-2.32E-14Adjusted R-squared0.356125S.D. dependent var31.76641S.E. of regression25.48994Akaike info criterion9.471215Sum squared resid12345.00Schwarz criterion9.668693Log likelihood-104.9190F-statistic5.056047Durbin-Watson stat1.765655Prob(F-statistic)0.009645 LMBG自相关检验辅助回归方程式估计结果是： 3.9） 0.2 -0.4 R2 =0.43 DW=2.00 LM= =230.43=9.89因为 ，LM=9.893.84，所以LM检验结果也说明误差项存在一阶正相关。（4）自相关的修正 Dependent Variable: GDYMethod: Least SquaresDate: 05/25/13 Time: 11:00Sample (adjusted): 1979 2000Included observations: 22 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.C46.5422111.876453.9188640.0009GDX0.6746730.03282720.552380.0000R-squared0.954792Mean dependent var269.7844Adjusted R-squared0.952532S.D. dependent var103.3914S.E. of regression22.52611Akaike info criterion9.153735Sum squared resid10148.51Schwarz criterion9.252921Log likelihood-98.69108F-statistic422.4005Durbin-Watson stat2.310424Prob(F-statistic)0.000000 令GDY=Y-0.70*Y(-1) GDX=X-0.70X(-1) 以GDY、GDX、（1979-2000）为样本再次回归，得 GDY=45.2489+0.6782GDX (3.7) (20.0) R2 =0.95 s.e=23.2 DW=2.31, T=22(19792000) 回归方程拟合优度依然较好，且DW=2.13.查表得，。因为 DW=2,132.57，依据判断规则，误差项已经消除自相关。（5）再次检验自相关是否存在 Breusch-Godfrey Serial Correlation LM Test:F-statistic0.660806Probability0.528521Obs*R-squared1.504816Probability0.471230Test Equation:Dependent Variable: RESIDMethod: Least SquaresDate: 05/25/13 Time: 11:02Presample missing value lagged residuals set to zero.VariableCoefficientStd. Errort-StatisticProb.C0.07870712.089110.0065110.9949GDX-0.0002740.033404-0.0081990.9935RESID(-1)-0.1361810.232983-0.5845130.5661RESID(-2)0.2047850.2330330.8787800.3911R-squared0.068401Mean dependent var3.42E-14Adjusted R-squared-0.086866S.D. dependent var21.98323S.E. of regression22.91814Akaike info criterion9.264701Sum squared resid9454.345Schwarz criterion9.463072Log likelihood-97.91171F-statistic0.440537Durbin-Watson s