计量课后习题第六章.docx
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计量课后习题第六章
6.1
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
15:
54
Sample:
119
Includedobservations:
19
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
79.93004
12.39919
6.446390
0.0000
X
0.690488
0.012877
53.62068
0.0000
R-squared
0.994122
Meandependentvar
700.2747
AdjustedR-squared
0.993776
S.D.dependentvar
246.4491
S.E.ofregression
19.44245
Akaikeinfocriterion
8.872095
Sumsquaredresid
6426.149
Schwarzcriterion
8.971510
Loglikelihood
-82.28490
Hannan-Quinncriter.
8.888920
F-statistic
2875.178
Durbin-Watsonstat
0.574663
Prob（F-statistic）
0.000000
Y=0.690488x+79.93004
Dw=0.574663n=19dl=1.18du=1.401
模型存在自相关
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
16:
02
Sample（adjusted）:
219
Includedobservations:
18afteradjustments
Convergenceachievedafter5iterations
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
104.0449
23.87618
4.357687
0.0006
X
0.669262
0.020831
32.12757
0.0000
AR
（1）
0.630015
0.164218
3.836462
0.0016
R-squared
0.997097
Meandependentvar
719.1867
AdjustedR-squared
0.996710
S.D.dependentvar
238.9866
S.E.ofregression
13.70843
Akaikeinfocriterion
8.224910
Sumsquaredresid
2818.814
Schwarzcriterion
8.373306
Loglikelihood
-71.02419
Hannan-Quinncriter.
8.245372
F-statistic
2575.896
Durbin-Watsonstat
1.787878
Prob（F-statistic）
0.000000
InvertedARRoots
.63
DW=1.787878可以判断在5%显著水平下广义差分法后模型中已无自相关。
Y=104.0449+0.669262x,居民家庭收入每增加一元，平均说来人均实际消费支出将增加0.669262元。
6.2
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
17:
08
Sample:
19852011
Includedobservations:
27
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
-1666.930
555.8502
-2.998883
0.0061
X
0.265028
0.011721
22.61184
0.0000
R-squared
0.953384
Meandependentvar
8522.312
AdjustedR-squared
0.951519
S.D.dependentvar
7680.271
S.E.ofregression
1691.069
Akaikeinfocriterion
17.77530
Sumsquaredresid
71492818
Schwarzcriterion
17.87128
Loglikelihood
-237.9665
Hannan-Quinncriter.
17.80384
F-statistic
511.2954
Durbin-Watsonstat
0.601332
Prob（F-statistic）
0.000000
y=-1666.930+0.265028xn=27a=0.05dl=1.316du=1.469dw=0.601332
说明模型具有相关性。
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
17:
09
Sample（adjusted）:
19862011
Includedobservations:
26afteradjustments
Convergenceachievedafter6iterations
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
-1632.831
1445.298
-1.129754
0.2702
X
0.260932
0.024776
10.53183
0.0000
AR
（1）
0.701865
0.151780
4.624230
0.0001
R-squared
0.975284
Meandependentvar
8801.717
AdjustedR-squared
0.973135
S.D.dependentvar
7691.158
S.E.ofregression
1260.628
Akaikeinfocriterion
17.22477
Sumsquaredresid
36551200
Schwarzcriterion
17.36994
Loglikelihood
-220.9221
Hannan-Quinncriter.
17.26658
F-statistic
453.7857
Durbin-Watsonstat
1.654943
Prob（F-statistic）
0.000000
InvertedARRoots
.70
Y=-1632.831+0.260932xn=27a=0.05dl=1.316du=1.469dw=1.654943
可知在5%显著性水平下广义差分法模型中已无自相关。
6.3
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
20:
55
Sample:
19812006
Includedobservations:
26
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
-2123.864
324.8012
-6.538966
0.0000
X
0.784106
0.041276
18.99680
0.0000
R-squared
0.937643
Meandependentvar
3604.775
AdjustedR-squared
0.935044
S.D.dependentvar
2414.000
S.E.ofregression
615.2413
Akaikeinfocriterion
15.75571
Sumsquaredresid
9084525.
Schwarzcriterion
15.85249
Loglikelihood
-202.8242
Hannan-Quinncriter.
15.78358
F-statistic
360.8784
Durbin-Watsonstat
0.440822
Prob（F-statistic）
0.000000
Y=-2123.864+0.784106XN=26a=0.05dl=1.302du=1.461dw=0.440822
由此可知此模型存在自相关。
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
20:
56
Sample（adjusted）:
19822006
Includedobservations:
25afteradjustments
Convergenceachievedafter7iterations
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
-2914.286
1192.273
-2.444311
0.0230
X
0.865050
0.119983
7.209763
0.0000
AR
（1）
0.787017
0.132752
5.928459
0.0000
R-squared
0.975002
Meandependentvar
3717.661
AdjustedR-squared
0.972730
S.D.dependentvar
2392.713
S.E.ofregression
395.1262
Akaikeinfocriterion
14.90845
Sumsquaredresid
3434744.
Schwarzcriterion
15.05472
Loglikelihood
-183.3557
Hannan-Quinncriter.
14.94902
F-statistic
429.0384
Durbin-Watsonstat
0.912240
Prob（F-statistic）
0.000000
InvertedARRoots
.79
y=-2914.286+0.865050xN=26a=0.05dl=1.302du=1.461dw=0.912240
6.4
6.5
1.葡萄酒价格的对数对hrain的回归
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
21:
18
Sample:
128
Includedobservations:
28
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
607.7699
63.26986
9.605994
0.0000
X
7.667088
41.51142
0.184698
0.8549
R-squared
0.001310
Meandependentvar
597.1071
AdjustedR-squared
-0.037101
S.D.dependentvar
134.5212
S.E.ofregression
136.9939
Akaikeinfocriterion
12.74650
Sumsquaredresid
487950.5
Schwarzcriterion
12.84166
Loglikelihood
-176.4510
Hannan-Quinncriter.
12.77559
F-statistic
0.034113
Durbin-Watsonstat
1.302665
Prob（F-statistic）
0.854899
y=7.667088X+607.7699r^2=0.001310a=0.05dl=1.328du=1.476dw=1.302665
模型中存在自相关。
修正后：
DependentVariable:
Y
Method:
LeastSquares
Date:
06/09/15Time:
21:
40
Sample（adjusted）:
228
Includedobservations:
27afteradjustments
Convergenceachievedafter7iterations
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
538.7340
72.14390
7.467492
0.0000
X
-43.61104
38.94329
-1.119860
0.2739
AR
（1）
0.465607
0.190773
2.440633
0.0224
R-squared
0.166824
Meandependentvar
597.0000
AdjustedR-squared
0.097393
S.D.dependentvar
137.0825
S.E.ofregression
130.2361
Akaikeinfocriterion
12.68101
Sumsquaredresid
407074.8
Schwarzcriterion
12.82500
Loglikelihood
-168.1937
Hannan-Quinncriter.
12.72383
F-statistic
2.402718
Durbin-Watsonstat
1.783005
Prob（F-statistic）
0.111903
InvertedARRoots
.47
Y=-43.61104X+538.7340a=0.05DL=1.316DU=1.469DW=1.783005
此模型不具备自相关。
2.葡萄酒价格的对数对wrain的回归
DependentVariable:
Y1
Method:
LeastSquares
Date:
06/09/15Time:
21:
57
Sample:
128
Includedobservations:
28
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
156.1172
82.38902
1.894878
0.0693
X
-28.60091
54.05552
-0.529103
0.6012
R-squared
0.010653
Meandependentvar
195.8929
AdjustedR-squared
-0.027399
S.D.dependentvar
175.9965
S.E.ofregression
178.3913
Akaikeinfocriterion
13.27458
Sumsquaredresid
827409.7
Schwarzcriterion
13.36974
Loglikelihood
-183.8442
Hannan-Quinncriter.
13.30368
F-statistic
0.279950
Durbin-Watsonstat
1.154326
Prob（F-statistic）
0.601223
y=-28.60091x+156.1172a=0.05dl=1.328du=1.476dw=1.154326
模型存在自相关
修正后：
DependentVariable:
Y1
Method:
LeastSquares
Date:
06/09/15Time:
22:
01
Sample（adjusted）:
228
Includedobservations:
27afteradjustments
Convergenceachievedafter9iterations
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
78.62165
91.81988
0.856260
0.4003
X
-82.26617
46.91906
-1.753364
0.0923
AR
（1）
0.495758
0.178560
2.776420
0.0105
R-squared
0.222035
Meandependentvar
197.2222
AdjustedR-squared
0.157204
S.D.dependentvar
179.2058
S.E.ofregression
164.5179
Akaikeinfocriterion
13.14836
Sumsquaredresid
649587.5
Schwarzcriterion
13.29234
Loglikelihood
-174.5028
Hannan-Quinncriter.
13.19117
F-statistic
3.424853
Durbin-Watsonstat
1.730821
Prob（F-statistic）
0.049150
InvertedARRoots
.50
y=-82.26617x+78.62165a=0.05dl=1.316du=1.469dw=1.730821
此模型不存在自相关。
3.葡萄酒价格的对数对degrees的回归
DependentVariable:
Y2
Method:
LeastSquares
Date:
06/09/15Time:
22:
25
Sample:
128
Includedobservations:
28
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
17.17795
0.282212
60.86887
0.0000
X
0.540385
0.185160
2.918480
0.0072
R-squared
0.246759
Meandependentvar
16.42643
AdjustedR-squared
0.217789
S.D.dependentvar
0.690905
S.E.ofregression
0.611055
Akaikeinfocriterion
1.921490
S
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