发布时间 : 星期二 文章异方差练习题参考解答更新完毕开始阅读426896d3842458fb770bf78a6529647d26283408
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（2）用White检验判断是否存在异方差。
White Heteroskedasticity Test: F-statistic Obs*R-squared
Test Equation:
Dependent Variable: RESID^2 Method: Least Squares Date: 08/08/05 Time: 17:04 Sample: 1978 2000 Included observations: 23
Variable C X X^2 R-squared
Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat
Coefficient -2319.690 10.85979 -0.002560 Std. Error 2268.373 6.644388 0.003247 t-Statistic -1.022623 1.634430 -0.788315 Prob. 0.3187 0.1178 0.4398 5013.402 19.42572 19.57383 9.509463 0.001252
9.509463 Probability 11.21085 Probability
0.001252 0.003678
0.487428 Mean dependent var 3337.769 0.436171 S.D. dependent var 3764.490 Akaike info criterion 2.83E+08 Schwarz criterion -220.3958 F-statistic 1.552514 Prob(F-statistic)
由上表可知，nR?11.2109，给定??0.05，在自由度为2下，查卡方分布表，得临界值
2为??5.9915，显然，nR?11.2109>??5.9915，则拒绝原假设，说明模型存在异
222方差。
进一步，用ARCH检验判断模型是否存在异方差。经试算选滞后阶数为1，则ARCH检验结果见下表
ARCH Test:
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F-statistic Obs*R-squared
Test Equation:
9.394796 Probability 7.031364 Probability
0.006109 0.008009
Dependent Variable: RESID^2 Method: Least Squares Date: 08/08/05 Time: 17:11 Sample(adjusted): 1979 2000
Included observations: 22 after adjusting endpoints Variable C RESID^2(-1) R-squared
Adjusted R-squared S.E. of regression Sum squared resid Log likelihood Durbin-Watson stat
Coefficient 1676.876 0.588797 Std. Error 1086.874 0.192098 t-Statistic 1.542843 3.065093 Prob. 0.1385 0.0061 0.319607 Mean dependent var 3457.332 0.285588 S.D. dependent var 4308.730 Akaike info criterion 3.71E+08 Schwarz criterion -214.2730 F-statistic 1.874793 Prob(F-statistic)
5097.707 19.66118 19.76037 9.394796 0.006109
由上表可知，(n?p)R?7.0314，在??0.05和自由度为1下，查卡方分布表，得临界值为?0.05(1)?3.8415，显然，(n?p)R?7.0314>?0.05(1)?3.8415，则说明模型中随机误差项存在异方差。
（3）修正异方差。取权数为W?1/X，得如下估计结果
22222??8.3065?0.8558XY
(1.8563)(34.1172)R2?0.9941,s.e.?13.4795,F?1163.99
经检验异方差的表现有明显的降低。
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