Method: Least Squares Date:08/05/05me:13:17 Sample: 1 60 Included observations: 60 Weighting series: W1 Variable oefficient Std error t-Statisti 10.370512.62971639435870.0002 0.6309500.01853234.046670.0000 Weighted Statistics 0. 211441 Mean dependent var 106.210 Adjusted R-squared 0. 197845 S.D. dependent var 8.685376 S.E. of regression 7.778892 Akaike info criterion 6.973470 sum squared resid 3509.647 Schwarz criterion 7.043282 Log likelihood -207.2041 F-statistic 1159.176 Durbin-Watson stat 0.958467 Prob (F-statistic 0.000000 Unweighted Statistics 0.946335 Mean dependent var 119.666 Adjusted R-squared 0.945410 S.D. dependent var 38.68984 S.E. of regression 9.039689 Sum squared resid 4739. 526 Durbin-Watson stat 0.800564 其估计的书写形式为 F=103705+06310X (39436(34.0467) R2=0.2114sc=77789F=1159.18 练习题55参考解答 (1)建立样本回归模型 y=1929944+0.0319X (0.1948)(3.83) R2=0.4783.se=2759.15.F=146692 (2)利用 White检验判断模型是否存在异方差 te heterosked asticity Test F-statistic 3.057161 Probability 0.076976 Obs"R-squared 5.212471 Probabil 0.073812 Test Equation: Dependent Variable: RESID 2 Method: Least Squares Date:08/08/05Tme:15:389 Method: Least Squares Date: 08/05/05 Time: 13:17 Sample: 1 60 Included observations: 60 Weighting series: W1 Variable Coefficient Std. Error t-Statistic Prob. C 10.37051 2.629716 3.943587 0.0002 X 0.630950 0.018532 34.04667 0.0000 Weighted Statistics R-squared 0.211441 Mean dependent var 106.2101 Adjusted R-squared 0.197845 S.D. dependent var 8.685376 S.E. of regression 7.778892 Akaike info criterion 6.973470 Sum squared resid 3509.647 Schwarz criterion 7.043282 Log likelihood -207.2041 F-statistic 1159.176 Durbin-Watson stat 0.958467 Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.946335 Mean dependent var 119.6667 Adjusted R-squared 0.945410 S.D. dependent var 38.68984 S.E. of regression 9.039689 Sum squared resid 4739.526 Durbin-Watson stat 0.800564 其估计的书写形式为 2 ˆ 10.3705 0.6310 (3.9436)(34.0467) 0.2114, . . 7.7789, 1159.18 Y X R s e F = + = = = 练习题 5.5 参考解答 （1）建立样本回归模型。 2 ˆ 192.9944 0.0319 (0.1948) (3.83) 0.4783, . . 2759.15, 14.6692 Y X R s e F = + = = = （2）利用 White 检验判断模型是否存在异方差。 White Heteroskedasticity Test: F-statistic 3.057161 Probability 0.076976 Obs*R-squared 5.212471 Probability 0.073812 Test Equation: Dependent Variable: RESID^2 Method: Least Squares Date: 08/08/05 Time: 15:38