Method: Least Squares Date: 05/27/15 Time: 22:40 Sample: 1994 2011 Included observations: 18
Variable Coefficient Std. Error t-Statistic Prob. X2 0.001382 0.001102 1.254330 0.2336 X3 0.001942 0.003960 0.490501 0.6326 X4 -3.579090 3.559949 -1.005377 0.3346 X5 0.004791 0.005034 0.951671 0.3600 X6 0.045542 0.095552 0.476621 0.6422 C -13.77732 15.73366 -0.875659 0.3984 R-squared 0.994869 Mean dependent var 12.76667
Adjusted R-squared 0.992731 S.D. dependent var 9.746631 S.E. of regression 0.830963 Akaike info criterion 2.728738 Sum squared resid 8.285993 Schwarz criterion 3.025529 Log likelihood -18.55865 Hannan-Quinn criter. 2.769662 F-statistic 465.3617 Durbin-Watson stat 1.553294 Prob(F-statistic) 0.000000
①与预期不相符。
②评价:
可决系数为0.994869,可以认为拟合程度很好。 F检验,F=465.3617>F(5.12)=3,89,回归方程显著 T检验,X2,X3,X4,X5,X6 ,系数对应的t值分别为:1.254330,0.490501,-1.005377,0.951671,0.476621,均小于t(12)=2.179,所以所得系数都是不显著的。 (3)由Eviews分析得
????Dependent Variable: Y Method: Least Squares Date: 05/27/15 Time: 22:42 Sample: 1994 2011 Included observations: 18
Variable Coefficient Std. Error t-Statistic Prob. X5 0.001032 2.20E-05 46.79946 0.0000 X6 -0.054965 0.031184 -1.762581 0.0983 C 4.205481 3.335602 1.260786 0.2266 R-squared 0.993601 Mean dependent var 12.76667
Adjusted R-squared 0.992748 S.D. dependent var 9.746631 S.E. of regression 0.830018 Akaike info criterion 2.616274 Sum squared resid 10.33396 Schwarz criterion 2.764669 Log likelihood -20.54646 Hannan-Quinn criter. 2.636736
F-statistic 1164.567 Durbin-Watson stat 1.341880 Prob(F-statistic) 0.000000
①得到模型的方程为:
Y=0.001032 X5-0.054965 X6+4.205481 ②评价:
1) 可决系数为0.993601,拟合程度很好。
2) F检验,F=1164.567>F(5.12)=3,89,回归方程显著
3) T检验,X5 系数对应的t值为46.79946,大于t(12)=2.179,所以系数是显著的,
即人均GDP对年底存款余额有显著影响。 X6 系数对应的t值为-1.762581,小于t(12)=2.179,所以系数是不显著的,即居民消费价格指数对年底存款余额影响不显著。
4.3
(1)根据Eviews分析得到数据如下: Dependent Variable: LNY Method: Least Squares Date: 12/05/14 Time: 11:39 Sample: 1985 2011
Included observations: 27 Variable Coefficient Std. Error t-Statistic Prob. LNGDP 1.338533 0.088610 15.10582 0.0000
LNCPI -0.421791 0.233295 -1.807975 0.0832
C -3.111486 0.463010 -6.720126 0.0000 R-squared 0.988051 Mean dependent var 9.484710 Adjusted R-squared 0.987055 S.D. dependent var 1.425517 S.E. of regression 0.162189 Akaike info criterion -0.695670 Sum squared resid 0.631326 Schwarz criterion -0.551689 Log likelihood 12.39155 Hannan-Quinn criter. -0.652857 F-statistic 992.2582 Durbin-Watson stat 0.522613 Prob(F-statistic) 0.000000 得到的模型方程为: LNY=1.338533 LNGDPt-0.421791 LNCPIt-3.111486 (2)
① 该模型的可决系数为0.988051,可决系数很高,F检验值为992.2582,
明显显著。但当α=0.05时,t(24)=2.064,LNCPI的系数不显著,可能存在多重共线性。
②得到相关系数矩阵如下:
LNGDP, LNCPI之间的相关系数很高,证实确实存在多重共线性。 (3)由Eviews得: a)
Dependent Variable: LNY Method: Least Squares Date: 12/03/14 Time: 14:41 Sample: 1985 2011
Included observations: 27
Variable Coefficient Std. Error t-Statistic Prob. LNGDP 1.185739 0.027822 42.61933 0.0000
C -3.750670 0.312255 -12.01156 0.0000 R-squared 0.986423 Mean dependent var 9.484710 Adjusted R-squared 0.985880 S.D. dependent var 1.425517 S.E. of regression 0.169389 Akaike info criterion -0.642056 Sum squared resid 0.717312 Schwarz criterion -0.546068 Log likelihood 10.66776 Hannan-Quinn criter. -0.613514 F-statistic 1816.407 Durbin-Watson stat 0.471111 Prob(F-statistic) 0.000000 b)
Dependent Variable: LNY Method: Least Squares Date: 12/03/14 Time: 14:41 Sample: 1985 2011 Included observations: 27 Variable Coefficient Std. Error t-Statistic Prob. LNCPI 2.939295 0.222756 13.19511 0.0000
C -6.854535 1.242243 -5.517871 0.0000 R-squared 0.874442 Mean dependent var 9.484710 Adjusted R-squared 0.869419 S.D. dependent var 1.425517 S.E. of regression 0.515124 Akaike info criterion 1.582368 Sum squared resid 6.633810 Schwarz criterion 1.678356 Log likelihood -19.36196 Hannan-Quinn criter. 1.610910 F-statistic 174.1108 Durbin-Watson stat 0.137042 Prob(F-statistic) 0.000000 c)
Dependent Variable: LNGDP Method: Least Squares Date: 12/05/14 Time: 11:11 Sample: 1985 2011 Included observations: 27 Variable Coefficient Std. Error t-Statistic Prob. LNCPI 2.511022 0.158302 15.86227 0.0000
C -2.796381 0.882798 -3.167634 0.0040 R-squared 0.909621 Mean dependent var 11.16214 Adjusted R-squared 0.906005 S.D. dependent var 1.194029 S.E. of regression 0.366072 Akaike info criterion 0.899213 Sum squared resid 3.350216 Schwarz criterion 0.995201 Log likelihood -10.13938 Hannan-Quinn criter. 0.927755 F-statistic 251.6117 Durbin-Watson stat 0.099623
Prob(F-statistic) 0.000000 ①得到的回归方程分别为 1)LNY=1.185739 LNGDPt-3.750670 2)LNY=2.939295 LNCPIt-6.854535 3)LNGDPt=2.511022 LNCPIt-2.796381 ②对多重共线性的认识:
单方程拟合效果都很好,回归系数显著,判定系数较高,GDP和CPI对进口的显著的单一影响,在这两个变量同时引入模型时影响方向发生了改变,这只有通过相关系数的分析才能发现。
(4)建议:如果仅仅是作预测,可以不在意这种多重共线性,但如果是进行结构分析,还是应该引起注意的。 4.4
(1)按照设计的理论模型,由Eviews分析得:
Dependent Variable: CZSR Method: Least Squares Date: 12/03/14 Time: 11:40 Sample: 1985 2011 Included observations: 27
Variable Coefficient Std. Error t-Statistic CZZC 0.090114 0.044367 2.031129 GDP -0.025334 0.005069 -4.998036 SSZE 1.176894 0.062162 18.93271 C -221.8540 130.6532 -1.698038 R-squared 0.999857 Mean dependent var
Adjusted R-squared 0.999838 S.D. dependent var S.E. of regression 353.0540 Akaike info criterion Sum squared resid 2866884. Schwarz criterion Log likelihood -194.5455 Hannan-Quinn criter. F-statistic 53493.93 Durbin-Watson stat Prob(F-statistic) 0.000000
Prob. 0.0540 0.0000 0.0000 0.1030 22572.56 27739.49 14.70707 14.89905 14.76416 1.458128
从回归结果可见,可决系数为0.999857,校正的可决系数为0.999838,模型拟合的很好。F的统计量为53493.93,说明在α=0.05,水平下,回归方程回归方程整体上是显著的。但是t检验结果表明,国内生产总值对财政收入的影响显著,但回归系数的符号为负,与实际不符合。由此可得知,该方程可能存在多重共线性。
(2)得到相关系数矩阵如下:
由上表可知,CZZC与
GDP,CZZC与SSZE,GDP与SSZE之间的相关系数都非常高,说明确实存在多重共线性。方差扩大因子均大于10,存在严重多重共线性。并且通过以上分析,两两被解释变量之间相关性都很高。
(4)解决方式:分别作出财政收入与财政支出、国内生产总值、税收总额之间的一元回归。 。
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