C X1 X2 RESID(-1)
R-squared
Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic
Prob(F-statistic)
R-squared
Adjusted R-squared S.E. of regression
Durbin-Watson stat
Coefficient Std. Error t-Statistic
-766.3965 937.0314 -0.817898 0.020990 0.027070 0.775390 -0.001273 0.001716 -0.742002 -0.007092 0.007881 -0.899910
Weighted Statistics 0.029121 Mean dependent var -0.078755 S.D. dependent var 4.273921 Akaike info criterion 493.1929 Schwarz criterion -86.87425 Hannan-Quinn criter. 0.269946 Durbin-Watson stat 0.846488 Unweighted Statistics -0.014569 Mean dependent var -0.127299 S.D. dependent var 42689.59 Sum squared resid
1.69E-08
Prob. 0.4206 0.4448 0.4645 0.3761
-0.564513 4.074747 5.862855 6.047885 5.923170 1.683210
-4021.722 40207.07 4.92E+10
2从上表可以看出，nR2=0.902738，由LM检验可知，在α=0.05下，查?分
2?2统计量与临界值，因为布表，得临界值χ0 (5)=11.0705,比较计算的.052nR2=0.902738<χ0.05 (5)=11.0705,所以接受原假设，表明模型不存在自相关。
七、模型检验
（一）经济意义检验
模型估计结果表明，在假定其他变量不变的情况下，当旅游景区固定资产每增长1元时，旅游收入增加0.788277元；在假定其他变量不变的情况下，当景区从业人员每增加1人时，旅游收入增加0.235806万元。这与理论分析判断相一致。
（二）统计检验
1.拟合优度：由表中数据可得：R2=0.999848，修正的可决系数为
R2=0.999837，这说明模型对样本的拟合很好。
?2.F检验：针对H0：β1=β2=0，给定显著性水平α=0.05，在F分布表中查出自由度为k=2和n-k-1=28的临界值Fα( 2，28)=3.34。由表中得到F=92014.78，由于F=92014.78> Fα( 2，28)=3.34，应拒绝原假设，说明回归方程显著，即“旅游景区固定资产”、“旅游从业人员”等变量联合起来确实对“旅游景区营业收入”有显著影响。 3．t检验：分别对H0：βj=0(j=1,2),给定显著性水平α=0.05，查t分布表得自由度为n-k-1=28临界值tα/2(n-k-1)=2.048。由表中数据可得，?1、?2对应的t统计量分别为57.57099、243.6786，其绝对值均大于tα/2(n-k-1)=2.048，这说明应该分别拒绝H0：βj =0(j=1,2),也就是说，当在其他解释变量不变的情况下，解释变量“旅游景区固定资产”（X1） 、“旅游从业人数”（X2）分别对被解释变量“旅游景区营业收入”(Y)影响显著。 八、附录
以下是多重共线性参数估计
备表1 对X1回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:14 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C -15595.61 18604.86 -0.838255 X1 1.978224 0.229091 8.635111
R-squared 0.719983 Mean dependent var Adjusted R-squared 0.710327 S.D. dependent var S.E. of regression 60671.69 Akaike info criterion Sum squared resid 1.07E+11 Schwarz criterion Log likelihood -384.3636 Hannan-Quinn criter. F-statistic 74.56515 Durbin-Watson stat Prob(F-statistic) 0.000000
^^Prob. 0.4087 0.0000 114619.2 112728.1 24.92668 25.01920 24.95684 2.090544
备表2 对X2回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C 15958.73 11364.71 1.404236 X2 0.315120 0.025260 12.47495
R-squared 0.842924 Mean dependent var Adjusted R-squared 0.837508 S.D. dependent var S.E. of regression 45441.05 Akaike info criterion Sum squared resid 5.99E+10 Schwarz criterion Log likelihood -375.4027 Hannan-Quinn criter. F-statistic 155.6243 Durbin-Watson stat Prob(F-statistic) 0.000000
备表3 对X3回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C 53599.95 15413.41 3.477488 X3 0.316946 0.045785 6.922479 R-squared 0.622988 Mean dependent var Adjusted R-squared 0.609988 S.D. dependent var S.E. of regression 70399.77 Akaike info criterion Sum squared resid 1.44E+11 Schwarz criterion Log likelihood -388.9737 Hannan-Quinn criter. F-statistic 47.92072 Durbin-Watson stat Prob(F-statistic) 0.000000
Prob. 0.1709 0.0000 114619.2 112728.1 24.34856 24.44108 24.37872 1.665119
Prob. 0.0016 0.0000 114619.2 112728.1 25.22411 25.31662 25.25427 1.724195
备表4 对X4回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C -143904.9 66622.99 -2.159989 X4 12.54525 3.131970 4.005547
R-squared 0.356191 Mean dependent var Adjusted R-squared 0.333991 S.D. dependent var S.E. of regression 91996.75 Akaike info criterion Sum squared resid 2.45E+11 Schwarz criterion Log likelihood -397.2681 Hannan-Quinn criter. F-statistic 16.04440 Durbin-Watson stat Prob(F-statistic) 0.000394
备表5 对X2、X1回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C -4316.824 12795.42 -0.337373 X2 0.230304 0.039088 5.891959 X1 0.711446 0.265507 2.679575
R-squared 0.874983 Mean dependent var Adjusted R-squared 0.866053 S.D. dependent var S.E. of regression 41257.10 Akaike info criterion Sum squared resid 4.77E+10 Schwarz criterion Log likelihood -371.8644 Hannan-Quinn criter. F-statistic 97.98460 Durbin-Watson stat Prob(F-statistic) 0.000000
Prob. 0.0392 0.0004 114619.2 112728.1 25.75923 25.85175 25.78939 1.829839
Prob. 0.7384 0.0000 0.0122 114619.2 112728.1 24.18480 24.32357 24.23004 1.893654
备表6 对X2、X3回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C 16874.53 10798.59 1.562660 X2 0.258113 0.036788 7.016265 X3 0.087950 0.043040 2.043471
R-squared 0.863310 Mean dependent var Adjusted R-squared 0.853546 S.D. dependent var S.E. of regression 43140.27 Akaike info criterion Sum squared resid 5.21E+10 Schwarz criterion Log likelihood -373.2480 Hannan-Quinn criter. F-statistic 88.42123 Durbin-Watson stat Prob(F-statistic) 0.000000
备表7 对X2、X4回归分析 Dependent Variable: Y Method: Least Squares Date: 11/14/13 Time: 21:15 Sample: 1 31 Included observations: 31
Coefficient Std. Error t-Statistic C 10868.79 37371.23 0.290833 X2 0.312045 0.033484 9.319239 X4 0.293708 2.050660 0.143226
R-squared 0.843039 Mean dependent var Adjusted R-squared 0.831828 S.D. dependent var S.E. of regression 46228.45 Akaike info criterion Sum squared resid 5.98E+10 Schwarz criterion Log likelihood -375.3913 Hannan-Quinn criter. F-statistic 75.19429 Durbin-Watson stat Prob(F-statistic) 0.000000
Prob. 0.1294 0.0000 0.0505 114619.2 112728.1 24.27407 24.41284 24.31930 1.600090
Prob. 0.7733 0.0000 0.8871 114619.2 112728.1 24.41234 24.55112 24.45758 1.642818