1、1.根据搜集到的我国19832001年19年的民航客运量y、国内生产总值x1、实际利用外资额x2 、民航里程x3 、来华旅游入境人数x4数据资料进行分析，下面是其Eviews的案例分析结果： Dependent Variable: YMethod: Least SquaresDate: 09/22/08 Time: 21:11Sample: 1 19Included observations: 19Variable Coefficient Std. Error t-Statistic Prob. C -139.1572 232.6374 -0.598172 0.5593X1 0.036397
2、0.014217 （1） 0.0227X2 （2） 1.467469 1.097913 0.2908X3 7.505461 （3） 0.785504 0.4452X4 0.212216 0.142629 1.487891 0.1590R-squared 0.988977 Mean dependent var 3329.789Adjusted R-squared (4) S.D. dependent var 2370.662S.E. of regression 282.2216 Akaike info criterion 14.34420Sum squared resid 1115086. Sc
3、hwarz criterion 14.59273Log likelihood -131.2699 F-statistic 314.0201Durbin-Watson stat 1.890784 Prob(F-statistic) 0.000000White Heteroskedasticity Test:F-statistic 2.633628 Probability 0.076698Obs*R-squared 12.88458 Probability 0.115883Test Equation:Dependent Variable: RESID2Method: Least SquaresDa
4、te: 10/13/08 Time: 22:56Sample: 1 19Included observations: 19VariableCoefficient Std. Error t-Statistic Prob. C -80010.10 106191.3 -0.753452 0.4685X1 4.656329 14.88223 0.312878 0.7608X12 6.53E-05 0.000149 0.437255 0.6712X2 -117.8830 903.4451 -0.130482 0.8988X22 -0.622113 1.052638 -0.591004 0.5676X3
5、3006.499 6347.715 0.473635 0.6459X32 -16.63940 28.98757 -0.574018 0.5786X4 1.825724 65.47175 0.027886 0.9783X42 -0.009094 0.008874 -1.024848 0.3296R-squared 0.678136 Mean dependent var 58688.75Adjusted R-squared 0.420645 S.D. dependent var 70617.55S.E. of regression 53750.83 Akaike info criterion 24
6、.92762Sum squared resid 2.89E+10 Schwarz criterion 25.37499Log likelihood -227.8124 F-statistic 2.633628Durbin-Watson stat 2.990826 Prob(F-statistic) 0.076698（1）将上边表中的所缺数值（1）-（4）补齐；（2）检验各回归系数的统计显著性。（3）利用经典判断法你认为该模型中是否存在多重共线性的可能性。（4）检验模型是否存在自相关。 （ )85.1,6.0,5.uld(5) 检验模型是否存在异方差.2.为了考察我国农村家庭从事农业劳动的收入（
7、x1）和农业以外的其他收入(x2)变动对农村家庭人均消费(y)增长的影响，现对三个变量进行回归分析得到如下结果。根据输出结果完成下列要求：1）. 用标准记法写出样本回归方程，并解释各回归系数的经济含义；2）. 对模型进行异方差检验，说明模型是否存在异方差；3） 对模型进行自相关检验，说明模型是否存在序列自相关；4） 计算模型的方差扩大因子，说明模型是否存在多重共线性。（=0.05， =1.30， =1.57）lduDependent Variable: LOG(Y)Method: Least SquaresDate: 11/09/07 Time: 21:34Sample: 1 31Includ
8、ed observations: 31Variable CoefficientStd. Error t-Statistic Prob. C 1.602528 0.860978 1.861288 0.0732LOG(X1) 0.325416 0.103769 3.135955 0.0040LOG(X2) 0.507078 0.048599 10.43385 0.0000R-squared 0.796506 Mean dependent var 7.448704Adjusted R-squared0.781971 S.D. dependent var 0.364648S.E. of regress
9、ion0.170267 Akaike info criterion -0.611128Sum squared resid0.811747 Schwarz criterion -0.472355Log likelihood 12.47249 F-statistic 54.79806Durbin-Watson stat1.964720 Prob(F-statistic) 0.000000White Heteroskedasticity Test:F-statistic 4.920995 Probability 0.004339Obs*R-squared 13.35705 Probability 0
10、.009657Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 11/09/07 Time: 21:53Sample: 1 31Included observations: 31Variable Coefficient Std. Errort-StatisticProb. C 3.982137 2.882851 1.381319 0.1789LOG(X1) -0.579289 0.916069 -0.632364 0.5327(LOG(X1)2 0.041839 0.066866 0.625710 0.5370
11、LOG(X2) -0.563656 0.203228 -2.773514 0.0101(LOG(X2)2 0.040280 0.013879 2.902173 0.0075Dependent Variable: LOG(X1)Method: Least SquaresDate: 11/09/07 Time: 22:03Sample: 1 31Included observations: 31Variable Coefficient Std. Error t-Statistic Prob. C 7.630561 0.605020 12.61209 0.0000LOG(X2) -0.103332
12、0.084825 -1.218173 0.2330R-squared 0.048680 Mean dependent var 6.896563Adjusted R-squared0.015875 S.D. dependent var 0.307141S.E. of regression0.304694 Akaike info criterion0.523321Sum squared resid2.692309 Schwarz criterion 0.615837Log likelihood -6.111482 F-statistic 1.483946Durbin-Watson stat1.26
13、9696 Prob(F-statistic) 0.2329773. Eviews 分析结果(局部） 。Dependent Variable: YMethod: Least SquaresDate: 10/28/07 Time: 11:07Sample(adjusted): 120Included observations: 20 after adjusting endpointsVariable Coefficient Std. Error t-Statistic Prob. C 4.826789 9.217366 0.523663 0.6193X1 0.178381 0.308178 （1）
14、 0.5838X2 0.688030 （2） 3.277910 0.0169X3 （3） 0.156400 -1.423556 0.2044R-squared 0.852805 Mean dependent var 41.90000Adjusted R-squared（4） S.D. dependent var 34.28783S.E. of regression16.11137 Akaike info criterion8.686101Sum squared resid1557.457 Schwarz criterion 8.807135Log likelihood -39.43051 F-
15、statistic 11.58741Durbin-Watson stat3.579994 Prob(F-statistic) 0.0065791）.填上（1） 、 （2） 、 （3） 、 （4）位置所缺数据；2.)以标准记法写出回归方程；3)检验各个偏回归系数的统计显著性；4） 检验回归模型线性关系的显著性；5). 检验模型是否存在自相关（=0.05， =1.00， =1.68）ldu4.下面是某案例的 Eviews 局部分析结果,根据输出结果完成下列要求（写出判断或检验的依据）:1说明模型是否存在多重共线性。2. 对模型进行异方差检验，说明模型是否存在异方差；3对模型进行自相关检验，说明模型
16、是否存在序列自相关；（=0.05， =0.71， =2.06）lduDependent Variable: YMethod: Least SquaresDate: 10/03/08 Time: 22:13Sample: 1983 2000Included observations: 18VariableCoefficientStd. Error t-Statistic Prob. C -12815.96 14076.42 -0.910456 0.3805X1 6.212140 0.740809 8.385619 0.0000X2 0.421373 0.126897 3.320580 0.006
17、1X3 -0.166253 0.059222 -2.807271 0.0158X4 -0.097726 0.067638 -1.444840 0.1741X5 -0.028403 0.202333 -0.140379 0.8907R-squared 0.982801 Mean dependent var 44127.11Adjusted R-squared 0.975635 S.D. dependent var 4409.100S.E. of regression 688.2328 Akaike info criterion 16.16733Sum squared resid 5683973.
18、 Schwarz criterion 16.46412Log likelihood -139.5060 F-statistic 137.1430Durbin-Watson stat 3.405930 Prob(F-statistic) 0.000000White Heteroskedasticity Test:F-statistic 1.109456 Probability 0.459143Obs*R-squared 11.03658 Probability 0.354675Test Equation:Dependent Variable: RESID2Method: Least Square
19、sDate: 10/03/08 Time: 22:50Sample: 1983 2000Included observations: 18VariableCoefficientStd. Error t-Statistic Prob. C 3.49E+08 9.56E+08 0.365207 0.7257X1 8408.804 9356.773 0.898686 0.3987X12 -1.145278 1.445158 -0.792493 0.4541X2 -10576.50 16836.58 -0.628186 0.5498X22 0.047685 0.075673 0.630138 0.54
20、86X3 474.4214 369.7506 1.283085 0.2403X32 -0.009578 0.007231 -1.324559 0.2269X4 -926.4577 599.5460 -1.545265 0.1662X42 0.010993 0.007680 1.431525 0.1954X5 14742.43 9595.393 1.536407 0.1683X52 -0.230682 0.147639 -1.562468 0.1622R-squared 0.613143 Mean dependent var 315844.5Adjusted R-squared 0.060491
21、 S.D. dependent var 533410.1S.E. of regression 517025.2 Akaike info criterion 29.42733Sum squared resid 1.87E+12 Schwarz criterion 29.97145Log likelihood -253.8460 F-statistic 1.109456Durbin-Watson stat 2.375909 Prob(F-statistic) 0.4591435.某个案例的 Eviews 分析结果(局部）如下，根据输出结果完成下列要求（写出判断或检验的依据）：1说明模型是否存在多重
22、共线性。2. 对模型进行异方差检验，说明模型是否存在异方差；3对模型进行自相关检验，说明模型是否存在序列自相关；（=0.05， =0.93， =1.69）lduDependent Variable: YMethod: Least SquaresDate: 10/03/08 Time: 22:52Sample: 1983 2000Included observations: 18Variable Coefficient Std. Error t-Statistic Prob. C 30538.02 12311.20 2.480507 0.0264X1 6.893705 1.533406 4.49
23、5682 0.0005X4 -0.219380 0.130389 -1.682500 0.1146X5 0.020514 0.401029 0.051153 0.9599R-squared 0.911936 Mean dependent var 44127.61Adjusted R-squared 0.893065 S.D. dependent var 4409.147S.E. of regression 1441.833 Akaike info criterion 17.57835Sum squared resid 29104338 Schwarz criterion 17.77621Log
24、 likelihood -154.2051 F-statistic 48.32494Durbin-Watson stat 1.989729 Prob(F-statistic) 0.000000White Heteroskedasticity Test:F-statistic 1.384302 Probability 0.302559Obs*R-squared 7.744020 Probability 0.257463Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 10/03/08 Time: 22:54Sam
25、ple: 1983 2000Included observations: 18Variable Coefficient Std. Error t-Statistic Prob. C -4.12E+08 3.42E+08 -1.206744 0.2528X1 15344.77 15601.55 0.983541 0.3465X12 -2.387109 2.365151 -1.009284 0.3345X4 -1131.057 1040.149 -1.087398 0.3001X42 0.015954 0.012836 1.242953 0.2397X5 25804.91 21138.42 1.2
26、20759 0.2477X52 -0.405732 0.327950 -1.237176 0.2418R-squared 0.430223 Mean dependent var 1616908.Adjusted R-squared 0.119436 S.D. dependent var 1663301.S.E. of 1560814. Akaike info criterion 31.64461regressionSum squared resid 2.68E+13 Schwarz criterion 31.99087Log likelihood -277.8015 F-statistic 1.384302Durbin-Watson stat 2.582895 Prob(F-statistic) 0.302559
