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2.80%
24.10%
8.461
-0.223
1.82
1995
59810.5
2.90%
17.10%
-0.1429
1.91
1996
70142.5
3%
8.30%
8.314
0.6514
1.77
1997
78060.8
3.10%
8.28
0.3022
1.79
1998
83024.3
-0.80%
8.26
-0.0397
1.28
1999
88479.2
-1.40%
0.1918
1.39
2000
98000.5
0.40%
0.5173
1.26
2001
108068.2
3.60%
0.70%
-0.2062
0.98
2002
119095.7
4%
8.277
-0.1752
0.9
2003
135174.0
4.30%
1.20%
0.1027
0.82
2004
159586.7
4.20%
3.90%
-0.154
0.41
2005
185808.6
1.80%
8.1917
-0.083
0.39
2006
217522.7
4.10%
1.50%
7.8087
1.304
0.33
2007
267763.7
4.80%
7.7035
0.9666
0.26
2008
316228.8
5.90%
6.8505
-1.286
0.24
2009
343464.7
-0.70%
6.8189
0.7998
0.29
2010
400041.2
6.6227
-0.1431
0.3
二参数估计
模型为
X5=外债担保率
DependentVariable:
LOG（Y）
Method:
LeastSquares
Date:
06/14/11Time:
19:
18
Sample（adjusted）:
19912007
Includedobservations:
9afteradjustments
Variable
Coefficient
Std.Error
t-Statistic
Prob.
C
3.300339
2.799141
1.179054
0.3234
LOG（X1）
-0.847528
0.624481
-1.357172
0.2678
LOG（X2）
0.005220
0.031940
0.163432
0.8806
LOG（X3）
2.560787
0.346992
7.379966
0.0051
LOG（X4）
-0.123677
0.047515
-2.602903
0.0802
LOG（X5）
-0.944396
0.138662
-6.810795
0.0065
R-squared
0.996845
Meandependentvar
11.24235
AdjustedR-squared
0.991586
S.D.dependentvar
0.888625
S.E.ofregression
0.081511
Akaikeinfocriterion
-1.941445
Sumsquaredresid
0.019932
Schwarzcriterion
-1.809962
Loglikelihood
14.73650
F-statistic
189.5641
Durbin-Watsonstat
4.045962
Prob（F-statistic）
0.000600
LOG（Y）=3.300339-0.847528LOG（X1）+0.005220LOG（X2）+2.560787LOG（X3）-0.123677LOG（X4）-0.944396LOG（X5）
R2接近于1；
F检验通过；
但X1、X2、X4的参数未通过t检验，故解释变量间可能存在多重共线性。
1.000000
-0.449477
0.785400
-0.173970
-0.814595
-0.510952
-0.079836
0.301552
-0.175767
-0.432978
-0.264473
LOG（X1）LOG（X5）
30
Sample:
19912010
20
23.92099
1.122626
21.30807
0.0000
3.650893
0.331194
11.02343
0.870982
11.56900
0.863815
0.832606
0.307259
0.572388
1.699346
0.671961
-3.723880
121.5159
0.441441
0.000000
LOG（Y）=23.92099+3.650893LOG（X1）
R^2=0.870982
31
16
10.58560
0.673101
15.72661
-0.280130
0.192666
-1.453968
0.1680
0.131191
11.51426
0.069134
0.880592
0.849607
2.628383
10.10565
2.724957
-19.02707
2.114022
0.160927
0.168005
LOG（Y）=10.58560-0.280130LOG（X2）
R^2=
7.963480
2.330952
3.416407
0.0031
1.789969
1.153763
1.551418
0.1382
0.117945
0.068942
0.803393
2.494694
11.61792
2.594267
-22.94694
2.406898
0.061851
0.138206
32
19912009
11afteradjustments
11.43309
0.356896
32.03479
0.054845
0.281895
0.194557
0.8501
0.004188
11.39259
-0.106458
0.914023
0.961446
2.922208
8.319398
2.994553
-14.07214
0.037852
0.068566
0.850061
33
11.41318
0.076964
148.2917
-0.952219
0.096173
-9.901057
0.844869
0.836251
0.336922
0.756710
2.043298
0.856283
-5.567098
98.03094
0.388073
可见，第1个式子的拟合优度最高，可确定为初始回归模型
55
24.32676
1.501484
16.20181
3.744196
0.403281
9.284329
0.028152
0.079633
0.353530
0.7294
0.886143
0.868626
0.319175
0.721207
1.324346
0.866067
-2.769657
50.58897
0.500512
0.000001
20:
04
25.48138
1.920268
13.26970
3.817632
0.370658
10.29960
-0.494597
0.493838
-1.001536
0.3306
0.878171
0.863838
0.307233
0.615059
1.604663
0.764419
-3.150588
61.26987
0.514257
05
24.41519
1.211071
20.16000
3.760349
0.349684
10.75356
0.123257
0.076321
1.614987
0.1450
0.935567
0.919458
0.259399
0.366101
0.538302
0.474618
0.986442
58.07952
0.659393
0.000017
06
18.75787
1.823338
10.28765
2.147088
0.532763
4.030099
0.0009
-0.460338
0.141085
-3.262831
0.0046
0.920665
0.911332
0.247927
0.186118
1.044954
0.335478
1.138820
98.64071
0.395572
LOG
（1）LOG（5）的拟合优度最高，可确定为初始回归模型
08
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