计量经济学课程实验报告.docx
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计量经济学课程实验报告.docx
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计量经济学课程实验报告
计量经济学课程实验报告
实验序号
2
实验名称
Eviews的异方差检验与校正
实验组别
12
模拟角色
实验地点
2教602
指导老师
刘冬萍
实验日期
11月29日
实验时间
16:
05——17:
45
一、实验目的及要求
学会使用计量学分析^p软件Eviews的异方差检验与校正功能。
二、实验环境
2教602,经管学院电脑实验室
三、实验内容与步骤?
DATAY_
SORT_
1.生成相关图
SCAT_Y
根据相关图随着_的增大Y的取值范围不断增大,所以方程存在异方差.
2.方程的异方差检验
(1)WHITE检验
建立回归模型LSYC_
DependentVariable:
Y
Method:
LeastSquares
Date:
11/22/12Time:
17:
06
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
0.859469
0.709057
1.212130
0.2411
_
0.036340
0.009633
3.772393
0.0014
R-squared
0.441531
Meandependentvar
3.100000
AdjustedR-squared
0.410504
S.D.
dependentvar
2.255986
S.E.
ofregression
1.732115
Akaikeinfocriterion
4.031203
Sumsquaredresid
54.09
Schwarzcriterion
4.130776
Loglikelihood
-38.31203
F-statistic
14.23095
Durbin-Watsonstat
2.111232
Prob(F-statistic)
0.001395
进行WHITE检验
WhiteHeteroskedasticityTest:
F-statistic
6.172459
Probability
0.009656
Obs_R-squared
8.413667
Probability
0.014893
TestEquation:
DependentVariable:
RESID^2
Method:
LeastSquares
Date:
11/22/12Time:
17:
07
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
-0.840162
3.268547
-0.257045
0.8002
_
0.034691
0.096616
0.359062
0.7240
_^2
0.000259
0.000550
0.470375
0.6441
R-squared
0.420683
Meandependentvar
2.70020__
AdjustedR-squared
0.352528
S.D.
dependentvar
5.061699
S.E.
ofregression
4.072927
Akaikeinfocriterion
5.784082
Sumsquaredresid
282.0085
Schwarzcriterion
5.933442
Loglikelihood
-54.84082
F-statistic
6.172459
Durbin-Watsonstat
2.196613
Prob(F-statistic)
0.009656
Nr^2=8.413677因为检验的P=0.014893小于0.05,所以存在异方差.
(2)PARK检验
LSYC_
DependentVariable:
Y
Method:
LeastSquares
Date:
11/22/12Time:
17:
13
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
0.859469
0.709057
1.212130
0.2411
_
0.036340
0.009633
3.772393
0.0014
R-squared
0.441531
Meandependentvar
3.100000
AdjustedR-squared
0.410504
S.D.
dependentvar
2.255986
S.E.
ofregression
1.732115
Akaikeinfocriterion
4.031203
Sumsquaredresid
54.09
Schwarzcriterion
4.130776
Loglikelihood
-38.31203
F-statistic
14.23095
Durbin-Watsonstat
2.111232
Prob(F-statistic)
0.001395
GENRE2=LOG(RESID2)
GENRLN_=LOG(_)
LSLNE2CLN_
DependentVariable:
LNE2
Method:
LeastSquares
Date:
11/22/12Time:
17:
16
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
-7.692798
2.272023
-3.385881
0.0033
LN_
1.839358
0.571316
3.219514
0.0048
R-squared
0.365421
Meandependentvar
-0.465580
AdjustedR-squared
0.330167
S.D.
dependentvar
1.915506
S.E.
ofregression
1.567714
Akaikeinfocriterion
3.831754
Sumsquaredresid
44.23911
Schwarzcriterion
3.931327
Loglikelihood
-36.31754
F-statistic
10.36527
Durbin-Watsonstat
1.937606
Prob(F-statistic)
0.004754
由上图可看出P分别为0.0033,0.0048,0.004754都是小概率事件,所以方程是显著的,表明随机误差项的方差随着解释变量的取值不同而不断变化,即存在异方差性.
(3)GLEISER检验
LSYC_
GENRE=ABS(RESID)
eq\o\ac(○,1)GENR_1=_^0.5
LSEC_1
DependentVariable:
E1
Method:
LeastSquares
Date:
11/28/12Time:
13:
14
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
-1.250444
0.637839
-1.960437
0.0656
_1
0.326534
0.081232
4.019775
0.0008
R-squared
0.473046
Meandependentvar
1.192860
AdjustedR-squared
0.443771
S.D.
dependentvar
1.159531
S.E.
ofregression
0.864787
Akaikeinfocriterion
2.641972
Sumsquaredresid
13.46141
Schwarzcriterion
2.741545
Loglikelihood
-24.41972
F-statistic
16.15859
Durbin-Watsonstat
2.047999
Prob(F-statistic)
0.000804
|e1|=-1.250444+0.326534_1^0.5
R^2=0.473046F=16.15859P=
eq\o\ac(○,2)GENR_2=_^-2
LSEC_2
DependentVariable:
E
Method:
LeastSquares
Date:
11/28/12Time:
13:
27
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
1.665123
0.342774
4.857786
0.0001
_2
-657.9505
338.0359
-1.946392
0.0674
R-squared
0.173874
Meandependentvar
1.192860
AdjustedR-squared
0.127978
S.D.
dependentvar
1.159531
S.E.
ofregression
1.082794
Akaikeinfocriterion
3.091607
Sumsquaredresid
21.18
Schwarzcriterion
3.191180
Loglikelihood
-28.91607
F-statistic
3.788442
Durbin-Watsonstat
1.454864
Prob(F-statistic)
0.067388
|e2|=1.665123-657.9505_^-2
R^2=0.173874F=3.788442P=
eq\o\ac(○,3)GENR_3=_^2
LSEC_3
DependentVariable:
E
Method:
LeastSquares
Date:
11/28/12Time:
13:
32
Sle:
120
Includedobservations:
20
Variable
Coefficient
Std.
Error
t-Statistic
Prob.
C
0.580535
0.237632
2.443001
0.0251
_3
0.000113
2.67E-05
4.233931
0.0005
R-squared
0.498972
Meandependentvar
1.192860
AdjustedR-squared
0.471138
S.D.
dependentvar
1.159531
S.E.
ofregression
0.843245
Akaikeinfocriterion
2.59
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