中级计量经济学第四章知识题以及解答思路EViews.docx
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中级计量经济学第四章知识题以及解答思路EViews.docx
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中级计量经济学第四章知识题以及解答思路EViews
第4章
习题一
表1给出了1965~1970年美国制造业利润和销售额的季度数据。
假定利润不仅与销售额有关,而且和季度因素有关。
要求对下列二种情况分别估计利润模型:
(1)如果认为季度影响使利润平均值发生变异,应如何引入虚拟变量?
(2)如果认为季度影响使利润对销售额的变化率发生变异,如何引入虚拟变量?
表1
利润(Y)
销售额(X)
利润(Y)
销售额(X)
1965-I
10503
114862
1968-I
12539
148826
II
12092
123968
II
14849
158913
III
10834
121454
III
13203
155727
IV
12201
131917
IV
14947
168409
1966-I
12245
129911
1969-I
14151
162781
II
14001
140976
II
15949
176057
III
12213
137828
III
14024
172419
IV
12820
145645
IV
14315
183327
1967-I
11349
136989
1970-I
12381
170415
II
12615
145126
II
13991
181313
III
11014
141536
III
12174
176712
IV
12730
151776
IV
10985
180370
Quarterly65-70
Quick-EquationEstimation
Ycx@seas
(1)@seas
(2)@seas(3)
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
18:
38
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6868.015
1892.766
3.628559
0.0018
X
0.038265
0.011483
3.332252
0.0035
@SEAS
(1)
-182.1690
654.3568
-0.278394
0.7837
@SEAS
(2)
1140.294
630.6806
1.808038
0.0865
@SEAS(3)
-400.3371
636.1128
-0.629349
0.5366
R-squared
0.525596
Meandependentvar
12838.54
AdjustedR-squared
0.425721
S.D.dependentvar
1433.284
S.E.ofregression
1086.160
Akaikeinfocriterion
17.00174
Sumsquaredresid
22415107
Schwarzcriterion
17.24716
Loglikelihood
-199.0208
F-statistic
5.262563
Durbin-Watsonstat
0.388380
Prob(F-statistic)
0.005024
T和P在5%情况下都不通过,第二季度相对还好一点
假设第二季度显著,结果的经济含义是什么?
Ycx@seas
(2)@seas(3)@seas(4)
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
18:
47
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6685.846
1711.618
3.906155
0.0009
X
0.038265
0.011483
3.332252
0.0035
@SEAS
(2)
1322.463
638.4258
2.071444
0.0522
@SEAS(3)
-218.1681
632.1991
-0.345094
0.7338
@SEAS(4)
182.1690
654.3568
0.278394
0.7837
R-squared
0.525596
Meandependentvar
12838.54
AdjustedR-squared
0.425721
S.D.dependentvar
1433.284
S.E.ofregression
1086.160
Akaikeinfocriterion
17.00174
Sumsquaredresid
22415107
Schwarzcriterion
17.24716
Loglikelihood
-199.0208
F-statistic
5.262563
Durbin-Watsonstat
0.388380
Prob(F-statistic)
0.005024
第二季度依旧显著影响
四种都试一下(去掉一个季节),选一个最显著的
124
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
18:
51
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6467.678
1789.178
3.614888
0.0018
X
0.038265
0.011483
3.332252
0.0035
@SEAS
(1)
218.1681
632.1991
0.345094
0.7338
@SEAS
(2)
1540.632
628.3419
2.451900
0.0241
@SEAS(4)
400.3371
636.1128
0.629349
0.5366
R-squared
0.525596
Meandependentvar
12838.54
AdjustedR-squared
0.425721
S.D.dependentvar
1433.284
S.E.ofregression
1086.160
Akaikeinfocriterion
17.00174
Sumsquaredresid
22415107
Schwarzcriterion
17.24716
Loglikelihood
-199.0208
F-statistic
5.262563
Durbin-Watsonstat
0.388380
Prob(F-statistic)
0.005024
134
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
18:
52
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
8008.309
1827.543
4.382009
0.0003
X
0.038265
0.011483
3.332252
0.0035
@SEAS
(1)
-1322.463
638.4258
-2.071444
0.0522
@SEAS(3)
-1540.632
628.3419
-2.451900
0.0241
@SEAS(4)
-1140.294
630.6806
-1.808038
0.0865
R-squared
0.525596
Meandependentvar
12838.54
AdjustedR-squared
0.425721
S.D.dependentvar
1433.284
S.E.ofregression
1086.160
Akaikeinfocriterion
17.00174
Sumsquaredresid
22415107
Schwarzcriterion
17.24716
Loglikelihood
-199.0208
F-statistic
5.262563
Durbin-Watsonstat
0.388380
Prob(F-statistic)
0.005024
(2)
Y=c+βx+α1D1X+α2D2X+α3D3X
D1=1(第一季度)0(其他)
Ycx@seas
(1)*x@seas
(2)*x@seas(3)*x
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
00
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6965.852
1753.642
3.972220
0.0008
X
0.037363
0.011139
3.354215
0.0033
@SEAS
(1)*X
-0.000893
0.004259
-0.209588
0.8362
@SEAS
(2)*X
0.007712
0.003962
1.946502
0.0665
@SEAS(3)*X
-0.002291
0.004041
-0.566985
0.5774
R-squared
0.528942
Meandependentvar
12838.54
AdjustedR-squared
0.429771
S.D.dependentvar
1433.284
S.E.ofregression
1082.323
Akaikeinfocriterion
16.99466
Sumsquaredresid
22257030
Schwarzcriterion
17.24009
Loglikelihood
-198.9359
F-statistic
5.333675
Durbin-Watsonstat
0.418713
Prob(F-statistic)
0.004722
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
10
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
8008.309
1827.543
4.382009
0.0003
X
0.038265
0.011483
3.332252
0.0035
@SEAS
(1)
-1322.463
638.4258
-2.071444
0.0522
@SEAS(3)
-1540.632
628.3419
-2.451900
0.0241
@SEAS(4)
-1140.294
630.6806
-1.808038
0.0865
R-squared
0.525596
Meandependentvar
12838.54
AdjustedR-squared
0.425721
S.D.dependentvar
1433.284
S.E.ofregression
1086.160
Akaikeinfocriterion
17.00174
Sumsquaredresid
22415107
Schwarzcriterion
17.24716
Loglikelihood
-199.0208
F-statistic
5.262563
Durbin-Watsonstat
0.388380
Prob(F-statistic)
0.005024
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
11
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6965.852
1753.642
3.972220
0.0008
X
0.035072
0.011790
2.974675
0.0078
@SEAS
(1)*X
0.001398
0.004241
0.329736
0.7452
@SEAS
(2)*X
0.010003
0.004068
2.458823
0.0237
@SEAS(4)*X
0.002291
0.004041
0.566985
0.5774
R-squared
0.528942
Meandependentvar
12838.54
AdjustedR-squared
0.429771
S.D.dependentvar
1433.284
S.E.ofregression
1082.323
Akaikeinfocriterion
16.99466
Sumsquaredresid
22257030
Schwarzcriterion
17.24009
Loglikelihood
-198.9359
F-statistic
5.333675
Durbin-Watsonstat
0.418713
Prob(F-statistic)
0.004722
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
11
Sample:
1965Q11970Q4
Includedobservations:
24
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
6965.852
1753.642
3.972220
0.0008
X
0.036471
0.012353
2.952415
0.0082
@SEAS
(2)*X
0.008604
0.004237
2.030539
0.0565
@SEAS(3)*X
-0.001398
0.004241
-0.329736
0.7452
@SEAS(4)*X
0.000893
0.004259
0.209588
0.8362
R-squared
0.528942
Meandependentvar
12838.54
AdjustedR-squared
0.429771
S.D.dependentvar
1433.284
S.E.ofregression
1082.323
Akaikeinfocriterion
16.99466
Sumsquaredresid
22257030
Schwarzcriterion
17.24009
Loglikelihood
-198.9359
F-statistic
5.333675
Durbin-Watsonstat
0.418713
Prob(F-statistic)
0.004722
习题二
表2给出了某地区某行业的库存
和销售
的统计资料。
假设库存额依赖于本年销售额与前三年的销售额,试用Almon变换估计以下有限分布滞后模型:
表2
库存Y
(万元)
销售额X
(万元)
库存Y
(万元)
销售额X
(万元)
1980
11267
8827
1990
17053
13668
1981
12661
9247
1991
19491
14956
1982
12968
9579
1992
21164
15483
1983
12518
9093
1993
22719
16761
1984
13177
10073
1994
24269
17852
1985
13454
10265
1995
25411
17620
1986
13735
10299
1996
25611
18639
1987
14553
11038
1997
26930
20672
1988
15011
11677
1998
30218
23799
1989
15846
12445
1999
36784
27359
Y=α+α0ΣXt-i+α1ΣXt-i+α2ΣXt-i+μt
↑3,i=0笔记11,26)
在最上面输入
genrz0=x+x(-1)+x(-1)+x(-3)
genrz1=x(-1)+2*x(-2)+3*x(-3)
genrz2=x(-1)+4*x(-2)+9*x(-3)
ycz0z1z2
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
38
Sample(adjusted):
19831999
Includedobservations:
17afteradjustments
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
-1928.495
503.5272
-3.829972
0.0021
Z0
0.344027
0.091848
3.745615
0.0024
Z1
0.815758
0.351519
2.320667
0.0372
Z2
-0.339041
0.128632
-2.635739
0.0206
R-squared
0.996564
Meandependentvar
20467.29
AdjustedR-squared
0.995771
S.D.dependentvar
6997.995
S.E.ofregression
455.0907
Akaikeinfocriterion
15.28119
Sumsquaredresid
2692398.
Schwarzcriterion
15.47724
Loglikelihood
-125.8902
F-statistic
1256.768
Durbin-Watsonstat
1.985515
Prob(F-statistic)
0.000000
YcPDL(x,3,2)
重新回归
DependentVariable:
Y
Method:
LeastSquares
Date:
11/26/14Time:
19:
46
Sample(adjusted):
19831999
Includedobservations:
17after
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