计量经济学实验报告-多重共线性检验

计量经济学上机实验报告多重共线性检验实验背景近年来，中国旅游业一直保持高速发展，旅游业作为国民经济新的增长点，在整个社会经济发展中的作用日益显现。中国的旅游业分为国内旅游和入境旅游两大市场，入境旅游外汇收入年均增长22.6%，与此同时国内旅游也迅速增长。改革开放20多年来，特别是进入90年代后，中国的国内旅游收入年均增长14.4%，远高于同期GDP 9.76%的增长率。 为了规划中国未来旅游产业的发展，需要定量地分析影响中国旅游市场发展的主要因素。 模型 其中， Yt第t年全国旅游收入 X2国内旅游人数（万人） X3城镇居民人均旅游支出 （元） X4农村居民人均旅游支出 （元） X5公路里程（万公里） X6铁路里程（万公里）Y = 0.*X2 + 0.*X3 + 5.*X4 - 3.*X5 - 53.*X6 - 2220.数据来源中国统计局网站样本区间 19942009实验过程及结果（一）实证结果Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 15:49Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.X.0000X.8768X.0204X5-3.2.-1.0.1886X6-53.38584434.6829-0.0.9047C-2220.1512210.044-1.0.3388R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression252.1678Akaike info criterion14.17806Sum squared resid.0Schwarz criterion14.46778Log likelihood-107.4245F-statistic347.2644Durbin-Watson stat1.Prob(F-statistic)0.R2很高，F显著，但x3、x5、x6不显著，X5、X6的符号甚至是负的。可能存在多重共线性（二）检查各解释变量之间的相关性X2X3X4X5X6X.0.X.0.X.0.X.0.X.1.各解释变量相互之间的相关系数较高，证实确实存在严重多重共线性。（三）进一步检验和消除多重共线性，采用逐步回归法分别作Y对X2、X3、X4、X5、X6的一元回归，结果如下：变量x2x3x4x5x6参数估计值0.17.7860328.7987124.211453751.241t统计量27.9224558812.83403R-squared0.9823.按R-squared大小排序为：X2、X6、X5、X3、X4以X2为基础，分别加入X3、X4、X5、X6加入X3，不显著，排除。Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:11Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-3012.810549.3740-5.0.0001X59910.0000X.0555R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression335.2951Akaike info criterion14.63526Sum squared resid.Schwarz criterion14.78012Log likelihood-114.0821F-statistic487.3775Durbin-Watson stat0.Prob(F-statistic)0.加入X4，显著，保留Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:12Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2360.596180.9037-13.048910.0000X98450.0000X.0006R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression242.2577Akaike info criterion13.98524Sum squared resid.5Schwarz criterion14.13010Log likelihood-108.8819F-statistic939.5591Durbin-Watson stat0.Prob(F-statistic)0.加入X5，不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:12Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2052.457252.8897-8.0.0000X.0000X5-4.3.-1.0.2549R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression368.5792Akaike info criterion14.82455Sum squared resid.Schwarz criterion14.96941Log likelihood-115.5964F-statistic402.2068Durbin-Watson stat0.Prob(F-statistic)0.加入X6，显著，保留Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:12Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-6813.6822061.836-3.0.0057X.0000X6867.2159365.80032.0.0339R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression324.3425Akaike info criterion14.56884Sum squared resid.Schwarz criterion14.71370Log likelihood-113.5507F-statistic521.2956Durbin-Watson stat0.Prob(F-statistic)0.保留了X4和X6分别以X2和X4为基础，加入其他变量加入X3不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:35Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2323.426462.3572-5.0.0003X13290.0000X.0061X3-0.1.-0.0.9313R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression252.0685Akaike info criterion14.10960Sum squared resid.3Schwarz criterion14.30274Log likelihood-108.8768F-statistic578.5661Durbin-Watson stat0.Prob(F-statistic)0.加入X5不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:37Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2432.172178.3609-13.636240.0000X58080.0000X.0006X5-3.2.-1.0.1508R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression230.5411Akaike info criterion13.93105Sum squared resid.2Schwarz criterion14.12420Log likelihood-107.4484F-statistic692.4432Durbin-Watson stat1.Prob(F-statistic)0.加入X6不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:25Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2291.5332172.352-1.0.3123X99930.0000X.0095X6-12.85589402.8593-0.0.9751R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression252.1391Akaike info criterion14.11016Sum squared resid.7Schwarz criterion14.30330Log likelihood-108.8813F-statistic578.2396Durbin-Watson stat0.Prob(F-statistic)0.以X2、X6为基础，加入其他变量加入X3 ，不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:38Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-5877.5502399.623-2.0.0306X.0000X6606.4675495.01671.0.2440X.4416R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression329.0154Akaike info criterion14.64240Sum squared resid.Schwarz criterion14.83555Log likelihood-113.1392F-statistic337.9400Durbin-Watson stat0.Prob(F-statistic)0.加入X4不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:38Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2291.5332172.352-1.0.3123X99930.0000X6-12.85589402.8593-0.0.9751X.0095R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression252.1391Akaike info criterion14.11016Sum squared resid.7Schwarz criterion14.30330Log likelihood-108.8813F-statistic578.2396Durbin-Watson stat0.Prob(F-statistic)0.加入X5不显著，排除Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:39Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-6722.3952029.031-3.0.0062X.0000X6835.0915360.72052.0.0391X5-3.2.-1.0.2529R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression318.9580Akaike info criterion14.58031Sum squared resid.Schwarz criterion14.77346Log likelihood-112.6425F-statistic359.8440Durbin-Watson stat0.Prob(F-statistic)0.最后证实结果X2和X4Dependent Variable: YMethod: Least SquaresDate: 04/06/11 Time: 16:12Sample: 1994 2009Included observations: 16VariableCoefficientStd. Errort-StatisticProb.C-2360.596180.9037-13.048910.0000X98450.0000X.0006R-squared0.Mean dependent var4270.119Adjusted R-squared0.S.D. dependent var2720.860S.E. of regression242.2577Akaike info criterion1