1、Prob.0.0128 0.0000 119.6667 38.68984 7.272246 7.342058 1024.564 0.0000000.946423 Mean dependent var 0.945500 S.D. dependent var 9.032255 Akaike info criterion 4731.735 Schwarz criterion -216.1674 F-statistic 1.790431 Prob（F-statistic）（2）White检验结果：White Heteroskedasticity Test: F-statistic Obs*R-squa
2、redTest Equation: RESID_ Method:45 Sample:Variable C X X_Adjusted R-squared S.E. of regressionCoefficient -10.03614 0.165977 0.001800Std. Error 131.1424 1.619856 0.004587t-Statistic -0.076529 0.102464 0.392469Prob.0.9393 0.9187 0.6962 78.86225 111.1375 12.142856.301373 Probability 10.86401 Probabili
3、ty0.003370 0.0043740.181067 Mean dependent var 0.152332 S.D. dependent var 102.3231 Akaike info criterionSum squared resid Log likelihood Durbin-Watson stat596790.5 Schwarz criterion -361.2856 F-statistic 1.442328 Prob（F-statistic）12.24757 6.301373 0.003370nR2=10.86401, 查表得?20.05（2）=5.99147，nR2 5.99
4、147,所以拒绝原假设，表明模型中随机误差项存在异方差。 Goldfeld-Quandt检验： 16:16 Sample: 1 22 22Coefficient 12.53695 0.605911Std. Error 7.069578 0.063910t-Statistic 1.773365 9.480730Prob.0.0914 0.0000 78.63636 12.56050 6.330594 6.429780 89.88424 0.0000000.817990 Mean dependent var 0.808890 S.D. dependent var 5.490969 Akaike i
5、nfo criterion 603.0148 Schwarz criterion -67.63654 F-statistic 1.136382 Prob（F-statistic）17 Sample: 39 60Adjusted R-squared S.E. of regression Sum squared residCoefficient -39.54393 0.841215Std. Error 27.08272 0.113266t-Statistic -1.460116 7.426927Prob.0.1598 0.0000 160.8182 21.13367 7.751033 7.8502
6、190.733898 Mean dependent var 0.720593 S.D. dependent var 11.17103 Akaike info criterion 2495.840 Schwarz criterionLog likelihood Durbin-Watson stat-83.26137 F-statistic 0.610587 Prob（F-statistic）55.15924 0.000000eF=?e2221=2495.840/603.0148=4.139, 查得F0.05（20，20）=2.12，4.139 2.12，则拒绝原假设，表明模型中随机误差项存在异方
7、差。（3） 加权最小二乘法修正异方差 W1=1/X53 Sample: 60 Weighting series: W1Weighted Statistics R-squaredAdjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat Unweighted Statistics R-squaredAdjusted R-squared S.E. of regression Durbin-Watson statCoefficient 10.37051 0.630950Std. E
8、rror 2.629716 0.018532t-Statistic 3.943587 34.04667Prob.0.0002 0.0000 106.2101 8.685376 6.973470 7.043281 15.55188 0.000219119.6667 38.68984 4739.5260.211441 Mean dependent var 0.197845 S.D. dependent var 7.778892 Akaike info criterion 3509.647 Schwarz criterion -207.2041 F-statistic 1.969805 Prob（F
9、-statistic）0.946335 Mean dependent var 0.945410 S.D. dependent var 9.039689 Sum squared resid 1.796748 STD_RESID_ Method:54 Sample:Coefficient 238.8363 -2.139584 0.005690Std. Error 73.63191 0.909493 0.002575t-Statistic 3.243652 -2.352502 2.209642Prob.0.0020 0.0221 0.0312 58.49412 59.49678 10.98844 1
10、1.09316 3.138491 0.0509253.138491 Probability 5.951910 Probability0.050925 0.0509990.099198 Mean dependent var 0.067591 S.D. dependent var 57.45087 Akaike info criterion 188134.3 Schwarz criterion -326.6533 F-statistic 1.606243 Prob（F-statistic）虽然White检验结果nR2=5.95191 ?20.05（2）=5.99147，显示已消除异方差，但R2=0
11、.2114,拟合优度太低，不是理想的结果。 W2=1/X255 Sample: W2Coefficient 10.12327 0.633029Std. Error 2.755775 0.024590t-Statistic 3.673475 25.74374Prob.0.0005 0.0000Unweighted Statistics R-squared94.01206 41.02965 7.057130 7.126941 1451.660 0.0000000.961581 Mean dependent var 0.960918 S.D. dependent var 8.111184 Akaik
12、e info criterion 3815.896 Schwarz criterion -209.7139 F-statistic 2.091305 Prob（F-statistic）119.6667 38.68984 4735.4440.946381 Mean dependent var 0.945457 S.D. dependent var 9.035795 Sum squared resid 1.79504356 Sample:Coefficient 735.7452 -7.380790 0.018132Std. Error 89.80882 1.109309 0.003141t-Sta
13、tistic 8.192349 -6.653505 5.772821Prob.0.0000 0.0000 0.0000 63.59827 106.2429 11.38565 11.49037 39.31455 0.00000039.31455 Probability 34.78417 Probability0.000000 0.0000000.579736 Mean dependent var 0.564990 S.D. dependent var 70.07281 Akaike info criterion 279881.3 Schwarz criterion -338.5696 F-sta
14、tistic 1.520939 Prob（F-statistic）虽然R2=0.9616,拟合优度很高，但Whit e检验结果nR2=34.78417 ?20.05（2）=5.99147，显示异方差仍存在，不是理想的结篇二：计量经济学第三版庞皓课后习题答案（1）对百户拥有家用汽车量建立计量经济模型，用Eviews分析如下：? YMethod: Least SquaresDate: 05/24/15Time: 22:28Sample: 1 31 31 C 246.8540 51.97500 4.749476 0.0001X2 5.996865 1.406058 4.265020 0.0002X3
15、 -0.524027 0.179280 -2.922950 0.0069X4 -2.265680 0.518837 -4.366842 0.0002R-squared 0.666062 Mean dependent var 16.77355Adjusted R-squared 0.628957 S.D. dependent var 8.252535S.E. of regression 5.026889 Akaike info criterion 6.187394Sum squared resid 682.2795 Schwarz criterion 6.372424Log likelihood
16、 -91.90460 Hannan-Quinn criter. 6.247709F-statistic 17.95108 Durbin-Watson stat 1.147253Prob（F-statistic） 0.000001得到模型为Y=246.8540+5.996865X20.524027X32.265680X4对模型进行检验1）可决系数是0.666062，修正的可决系数为0.628957，说明模型对样本拟合较好2）F检验，F=17.95108 F（3.27）=3.65,回归方程显著。3）t检验，t统计量分别为4.749476,4.265050，-2.922950，-4.366843，均
17、大于t（27）=2,0518，所以这些系数都是显著的。依据1）可决系数越大，说明拟合程度越好2）F的值与临界值比较，若大于临界值，则否定原假设，回归方程是显著的；若小于临界值，则接受原假设，回归方程不显著。3）t的值与临界值比较，若大于临界值，则否定原假设，系数都是显著的；若小于临界值，则接受原假设，系数不显著。（2）经济意义：人均GDP增加一万元，百户拥有家用汽车增加5.996865辆，城镇人口比重增加一个百分点，百户拥有家用汽车减少0.524047辆，交通工具消费价格指数每上升1，百户拥有家用汽车减少2.265680辆。（3）模型改进:收集其他年份的截面数据进行分析3.3（1）用Eview
18、s分析得 05/26/15Time: 13:13 1 18 18Variable Coefficient Std. Error t-Statistic Prob. C -50.48685 49.44365 -1.021099 0.3234X 0.086214 0.029198 2.952725 0.0099T 52.43607 5.176603 10.12943 0.0000R-squared 0.951338 Mean dependent var 755.1222Adjusted R-squared 0.944850 S.D. dependent var 258.7206S.E. of re
19、gression 60.75813 Akaike info criterion 11.20269Sum squared resid 55373.25 Schwarz criterion 11.35109Log likelihood -97.82422 Hannan-Quinn criter. 11.22315F-statistic 146.6246 Durbin-Watson stat 2.606756Prob（F-statistic） 0.000000模型为：Y=-50.48685+0.086214X+52.43607T对模型进行检验：1）可决系数是0.951338，修正的可决系数为0.94
20、4850，说明模型对样本拟合很好。2）F检验，F=146.6246 F（2,15）=4.77，回归方程显著。3）t检验，t统计量分别为2.952725，10.12943，均大于t（15）=2.131，所以这些系数都是显著的。经济意义检验：模型估计结果说明，在假定其他变量不变的情况下，家庭月平均收入每增长1元，平均说来家庭书刊年消费支出会增长0.086214元;户主受教育年数每增长1年，平均说来家庭书刊年消费支出增加52.43607元。（2）用Eviews分析： 05/28/15 Time:30 18 Variable Coefficient Std. Error t-Statistic Pro
21、b. T 63.01676 4.548581 13.85416 0.0000C -11.58171 58.02290 -0.199606 0.8443R-squared 0.923054 Mean dependent varAdjusted R-squared 0.918245 S.D. dependent varS.E. of regression 73.97565 Akaike info criterionSum squared resid 87558.36 Schwarz criterionLog likelihood -101.9481 Hannan-Quinn criter.F-st
22、atistic 191.9377 Durbin-Watson stat X 05/28/15Time:34 18Variable Coefficient Std. Error t-StatisticT 123.1516 31.84150 3.867644C 444.5888 406.1786 1.094565R-squared 0.483182 Mean dependent varAdjusted R-squared 0.450881 S.D. dependent varS.E. of regression 517.8529 Akaike info criterionSum squared r
23、esid 4290746. Schwarz criterionLog likelihood -136.9753 Hannan-Quinn criter.F-statistic 14.95867 Durbin-Watson statProb（F-statistic） 0.001364以上分别是Y与T，X与T的一元回归模型分别是：Y = 63.01676T - 11.58171X = 123.1516T + 444.5888（3）用Eviews分析结果如下： E1 05/29/15Time: 20:39E2 0.086450 0.028431 3.040742C 3.96E-14 13.88083
24、 2.85E-15R-squared 0.366239 Mean dependent varAdjusted R-squared 0.326629 S.D. dependent var 755.1222 258.7206 11.54979 11.64872 11.56343 2.134043 Prob. 0.0014 0.2899 1942.933 698.8325 15.44170 15.54063 15.45534 1.052251Prob. 0.0078 1.0000 2.30E-14 71.76693S.E. of regression 58.89136 Akaike info criterion 11.09370Sum squared resid 55491.07 Schwarz criterion 11.19264Log likelihood -97.84334 Hannan-Quinn criter. 11.10735F-statistic 9.246111 Durbin-Watson stat
