1． OLS 检验
EViews 最小二乘法估计结果：
Dependent Variable: LNY Method: LeasБайду номын сангаас Squares Date: 12/01/11 Time: 11:09
Sample: 1980 2000 Included observations: 21 Coefficient C LNX R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 1.452109 0.870419 0.988300 0.987684 0.117889 0.264059 16.15139 1604.952 0.000000 Std. Error 0.190925 0.021727 t-Statistic 7.605641 40.06186 Prob. 0.0000 0.0000 9.031179 1.062296 -1.347752 -1.248273 -1.326162 0.451709
-0.027388 0.003293 1.034982 -0.521883 0.057467 0.582003 0.477503 0.083057 0.110376 25.31033 5.569435 0.005271
0.0006 0.0022
Time: 11:17
Sample: 1980 2000 Included observations: 21 Presample missing value lagged residuals set to zero. Coefficient C LNX RESID(-1) RESID(-2) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) -0.025902 0.003098 1.008103 -0.465000 0.580668 0.506668 0.080706 0.110728 25.27686 7.846883 0.001679 Std. Error 0.131079 0.014926 0.216751 0.217953 t-Statistic -0.197609 0.207594 4.650981 -2.133486 Prob. 0.8457 0.8380 0.0002 0.0478 1.09E-15 0.114904 -2.026367 -1.827411 -1.983189 1.516376
Breusch-Godfrey Serial Correlation LM Test: F-statistic Obs*R-squared Test Equation: Dependent Variable: RESID Method: Least Squares Date: 12/01/11 Time: 11:18 7.425914 12.22205 Prob. F(3,16) Prob. Chi-Square(3) 0.0025 0.0067
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
由于resid(-1)、resid（-2）分别为0.0002、0.0478.均小于显著性水平0.05，且其T统计量的 绝对值均大于1.729，所以此方程存在二阶序列相关。 接着进行三阶序列相关的检验：
Sample: 1980 2000 Included observations: 21 Presample missing value lagged residuals set to zero. Coefficient Std. Error t-Statistic Prob.
C LNX RESID(-1) RESID(-2) RESID(-3) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic)
F-statistic Obs*R-squared Test Equation: Dependent Variable: RESID Method: Least Squares Date: 12/01/11
11.77032 12.19402
Prob. F(2,17) Prob. Chi-Square(2)
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
3.做 LM 检验
Breusch-Godfrey Serial Correlation LM Test:
.3
.2
.1
R(-1)
.0 -.1 -.2 -.2 -.1 .0 R .1 .2 .3
根据 OLS 计算结果，看出残差 r 呈线性自回归，表明随机误差μ 存在自相关。且 由 DW 检验得： Durbin-Watson stat＝0.451709，给定显著性水平 a=0.05，查 D-W 表， n=21， k （解释变量个数） ＝1， 得下限临界值 dL=1.22， 上限临界值 dU=1.42， 因为 DW 统计量为 0.451709<dL=1.22。根据判定区域知，此时随机误差项存在一 阶自相关。
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
11
.3
10
.2
9
.1
.15 8 .10 7
.0
.05 .00
-.1
暨南大学本科实验报告专用纸
课程名称 计量经济学成绩评定 实验项目名称序列相关指导教师黄建军 实验项目编号 02010037905 实验项目类型 综合性 学生姓名 李碧妍学号 2009050226 学院经济学院系财税系专业财政学专业 实验时间 2011 年 12 月 1 日 上午实验地点 经济学院机房
为此，进行如下的校正：
Dependent Variable: LNY
Method: Least Squares Date: 12/13/11 Time: 19:51
Sample (adjusted): 1982 2000 Included observations: 19 after adjustments Convergence achieved after 7 iterations Variable C LNX AR(1) AR(2) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Inverted AR Roots Dependent Variable: R Method: Least Squares Date: 12/13/11 Time: 19:55 Coefficient 1.067728 0.911255 0.913717 -0.427302 0.996982 0.996379 0.060374 0.054675 28.62274 1651.791 0.000000 .46+.47i .46-.47i Std. Error 0.253666 0.027926 0.203740 0.180875 t-Statistic 4.209196 32.63122 4.484725 -2.362418 Prob. 0.0008 0.0000 0.0004 0.0321 9.180568 1.003240 -2.591867 -2.393038 -2.558217 1.983830
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
Sample (adjusted): 1982 2000 Included observations: 19 after adjustments Variable C LNY R(-1) R(-2) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Coefficient -0.285362 0.029973 0.894153 -0.381699 0.718521 0.662225 0.056613 0.048076 29.84463 12.76331 0.000209 Std. Error 0.131589 0.014182 0.201074 0.178163 t-Statistic -2.168586 2.113405 4.446888 -2.142411 Prob. 0.0466 0.0517 0.0005 0.0490 -0.021596 0.097410 -2.720487 -2.521658 -2.686837 1.989727
-.05
-.2 80 82 84 86 88 90 92 94 96 98 00
-.10 82 84 86 88 Residual 90 92 Actual 94 96 Fitted 98 00