第三章案例
- 格式:doc
- 大小:66.50 KB
- 文档页数:3
实例:某市人均储蓄与人均收入的关系分析(异方差性检验及补救)
根据某市1978-1998年人均储蓄与人均收入的数据资料(见下表),其中X 为人均收入(元),Y为人均储蓄(元),经分析人均储蓄受人均收入的线性影响,可建立一元线性回归模型进行分析。
obs X Y
1978590.2000107.0000
1979664.9400123.0000
1980809.5000159.0000
1981875.5400189.0000
1982991.2500233.0000
19831109.950312.0000
19841357.870401.0000
19851682.800522.0000
19861890.580664.0000
19872098.250871.0000
19882499.5801033.000
19892827.7301589.000
19903084.1702209.000
19913462.7102878.000
19923932.5203722.000
19935150.7905350.000
19947153.3508080.000
19959076.85011758.00
199610448.2115839.00
199711575.4818196.00
199812500.8420954.00
1、用OLS估计法估计参数
设模型为:
运行EVIEWS软件,并输入数据,得计算结果如下:
Dependent Variable: Y
Method: Least Squares
Date: 10/11/05 Time: 23:10
Sample: 1978 1998
Included observations: 21
Std. Error t-Statistic Prob.
Variable Coefficien
t
C-2185.998339.9020-6.4312620.0000
X 1.6841580.06216627.091500.0000 R-squared0.974766 Mean dependent var4533.238
Adjusted R-squared0.973438 S.D. dependent var6535.103
16.86989
S.E. of regression1065.086 Akaike info
criterion
Sum squared resid21553736 Schwarz criterion16.96937
Log likelihood-175.1338 F-statistic733.9495
Durbin-Watson stat0.293421 Prob(F-statistic)0.000000
2、异方差检验
(1)Goldfeld-Quandt检验
在Procs菜单项选Sort series项,出现排序对话框,输入X,OK。
在Sample菜单里,将时间定义为1978-1985,用OLS方法计算得如下结果:Y = -145.441495 + 0.3971185479*X
(-8.730234)(25.42693)
R-squared=0.990805 Sum squared resid1=15.12284
Dependent Variable: Y
Method: Least Squares
Date: 10/11/05 Time: 23:25
Sample: 1978 1985
Included observations: 8
Std. Error t-Statistic Prob.
Variable Coefficien
t
C-145.441516.65952-8.7302340.0001
X0.3971190.01561825.426930.0000 R-squared0.990805 Mean dependent var255.7500
Adjusted R-squared0.989273 S.D. dependent var146.0105
8.482607
S.E. of regression15.12284 Akaike info
criterion
Sum squared resid1372.202 Schwarz criterion8.502468
Log likelihood-31.93043 F-statistic646.5287
Durbin-Watson stat 1.335534 Prob(F-statistic)0.000000
在Sample菜单里,将时间定义为1991-1998,用OLS方法计算得如下结果:Y = -4602.367144 + 1.952519317*X
(-5.065962)(18.40942)
R-squared=0.982604 Sum squared resid2=5811189.
Dependent Variable: Y
Method: Least Squares
Date: 10/11/05 Time: 23:29
Sample: 1991 1998
Included observations: 8
Std. Error Variable Coefficien
t。