多重共线性案例分析.ppt

1、第十二讲,多重共线性案例分析,多重共线性的侦查与处理,研究美国每人的子鸡消费量 令：,获取数据,196027.80000 397.5000 42.20000 50.70000 78.30000 65.80000 196129.90000 413.3000 38.10000 52.00000 79.2000066.90000 196229.80000 439.2000 40.30000 54.00000 79.2000067.80000 196330.80000 459.7000 39.50000 55.30000 79.2000069.60000 196431.20000 492.9000 3

2、7.30000 54.70000 77.4000068.70000 196533.30000 528.6000 38.10000 63.70000 80.2000073.60000 196635.60000 560.3000 39.30000 69.80000 80.4000076.30000 196736.40000 624.6000 37.80000 65.90000 83.9000077.20000 196836.70000 666.4000 38.40000 64.50000 85.5000078.10000 196938.40000 717.8000 40.10000 70.0000

3、0 93.7000084.70000 197040.40000 768.2000 38.60000 73.20000 106.100093.30000 197140.30000 843.3000 39.80000 67.80000 104.800089.70000 197241.80000 911.6000 39.70000 79.10000 114.0000100.7000 197340.40000 931.1000 52.10000 95.40000 124.1000113.5000 197440.70000 1021.500 48.90000 94.20000 127.6000115.3

4、000 197540.10000 1165.900 58.30000 123.5000 142.9000136.7000 197642.70000 1349.600 57.90000 129.9000 143.6000139.2000 197744.10000 1449.400 56.50000 117.6000 139.2000132.0000 197846.70000 1575.500 63.70000 130.9000 165.5000132.1000 197950.60000 1759.100 61.60000 129.8000 203.3000154.4000 198050.1000

5、0 1994.200 58.90000 128.0000 219.6000174.9000 198151.70000 2258.100 66.40000 141.0000 221.6000180.8000 198252.90000 2478.700 70.40000 168.2000 232.6000189.4000,估计方程及报告结果,Dependent Variable: LOG(Y) Method: Least Squares Date: 10/11/10 Time: 21:40 Sample: 1960 1982 Included observations: 23 VariableCo

6、efficient Std. Error t-Statistic Prob. C 2.189792 0.15571514.062830.0000 LOG(X1)0.342555 0.0832664.1139700.0007 LOG(X2)-0.504592 0.110894-4.5502120.0002 LOG(X3)0.148545 0.0996731.4903340.1535 LOG(X4)0.091105 0.1007160.9045680.3776 R-squared0.982313Mean dependent var3.663887 Adjusted R-squared 0.9783

7、83S.D. dependent var0.187659 S.E. of regression0.027591Akaike info criterion-4.152987 Sum squared resid0.013703Schwarz criterion-3.906140 Log likelihood52.75935Hannan-Quinn criter.-4.090906 F-statistic249.9282Durbin-Watson stat1.826069 Prob(F-statistic)0.000000,通过总体显著性检验 检验： 、 通过显著性检验； 、 未 通过显著性检验 很

8、大,多重共线性的侦查,（1） 值高且不显著的 值四个中占了两个，有理由怀疑该模型中存在着较为严重的多重共线性。,回归元的两两相关系数,（2）考察回归元之间的相关系数,回归元之间的相关系数均大于0.8，表明多重共线性是严重的,（3）辅助回归,应用克莱因法则： 辅助模型的 大于回归方程的 多重共线性问题比较严重,多重共线性的处理,（1）不做处理。 作为分析者，如果你主要关注的因素 是可支配收入与子鸡价格对子鸡消费量 的影响的话，两个统计量都通过了显著 性的 检验，对多重共线性可以不做处理。,（2）剔除不重要的变量 前两个变量是我们主要关心的因素，都通过了 显著性检验；后两个变量未通过显著性检验，由

9、相 关系数大小选择剔掉 ，然后再重新估计模型,Dependent Variable: LOG(Y) Method: Least Squares Date: 10/11/10 Time: 21:51 Sample: 1960 1982 Included observations: 23 VariableCoefficientStd. Errort-StatisticProb. C2.1254980.13788215.415330.0000 LOG(X1)0.4059240.0447919.0625350.0000 LOG(X2)-0.4388250.083332-5.2659560.0000 L

10、OG(X3)0.1066560.0878381.2142280.2395 R-squared 0.981509 Mean dependent var3.663887 Adjusted R-squared 0.978590S.D. dependent var0.187659 S.E. of regression0.027459Akaike info criterion-4.195488 Sum squared resid0.014326Schwarz criterion-3.998011 Log likelihood52.24812Hannan-Quinn criter.-4.145823 F-

11、statistic 336.1808 Durbin-Watson stat1.778678 Prob(F-statistic)0.000000,多重共线性的再检验： （1）回归元的相关系数,回归元之间的相关系数均大于0.8，表明多重共线性是严重的,（2）辅助回归,应用克莱因法则： 没有辅助模型的 大于回归方程的 多重共线性问题不是很严重,多重共线性的处理： （1）依据克莱因法则，则不必对其进行调整 （2）选择相关系数判定，则剔除 ，再做回归，得到下面的结果,Dependent Variable: LOG(Y) Method: Least Squares Date: 10/22/10 Time:

12、 09:28 Sample: 1960 1982 Included observations: 23 VariableCoefficientStd. Errort-StatisticProb. C2.0328200.11618317.496730.0000 LOG(X1)0.4515280.02469518.284350.0000 LOG(X2)-0.3722120.063466-5.8647400.0000 R-squared 0.980074Mean dependent var 3.663887 Adjusted R-squared0.978082S.D. dependent var 0.

13、187659 S.E. of regression0.027783Akaike info criterion -4.207711 Sum squared resid0.015437Schwarz criterion -4.059603 Log likelihood51.38868Hannan-Quinn criter. -4.170462 F-statistic 491.8681Durbin-Watson stat 1.875601 Prob(F-statistic)0.000000,多重共线性再检验,回归元之间的相关系数均大于0.8，表明多重共线性是严重的,多重共线性的处理 剔除 ，再回归获

14、得新模型,Dependent Variable: LOG(Y) Method: Least Squares Date: 10/22/10 Time: 09:31 Sample: 1960 1982 Included observations: 23 VariableCoefficientStd. Errort-StatisticProb. C1.4922110.11381913.110340.0000 LOG(X1)0.3201430.01672319.144350.0000 R-squared 0.945807Mean dependent var 3.663887 Adjusted R-squared0.943227S.D. dependent var 0.187659 S.E. of regression0.044714Akaike info