计量经济学作业

3.2

⑴用Eviews分析如下

DependentVariable:Y

Method:LeastSquares

Date:12/01/14Time:20:25

Sample:19942011

Includedobservations:18

VariableCoefficientStd.Errort-StatisticProb.

X20.1354740.01279910,584540.0000

X318.853489.7761811.9285120.0729

C-18231.588638.216-2.1105730.0520

R-squared0.985838Meandependentvar6619.191

AdjustedR-squared0.983950S.D.dependentvar5767.152

S.E.ofregression730.6306Akaikeinfocriterion16.17670

Sumsquaredresid8007316.Schwarzcriterion16.32510

Loglikelihood-142.5903Hannan-Quinncriter.16.19717

F-statistic522.0976Durbin-Watsonstat1.173432

Prob(F-statistic)0.000000

由表可知模型为:Y=0.135474X2+18.85348X3-18231.58

检验：可决系数是0.985838,修正的可决系数为0.983950,说明模型

对样本拟合较好。

F检验，F=522,0976>F(2,15)=4.77,回归方程显著。

t检验，t统计量分别为X2的系数对应t值为10.58454,大于t(15)

=2.131,系数是显著的，X3的系数对应t值为L928512,小于t(15)

=2.131,说明此系数是不显著的。

(2)(2)表内数据In后重新输入数据:

DependentVariable:LNY

Method:LeastSquares

Date:10/25/15Time:22:18

Sample:19942011

Includedobservations:18

Coefficien

VariabletStd.Errort-StatisticProb.

C-10.810901.698653-6.3643970.0000

LNX21.5737840.09154717.191060.0000

X30.0024380.0009362.6053210.0199

Meandependent

R-squared0.986373var8.400112

S.D.dependent

AdjustedR-squared0.984556var0.941530

Akaikeinfo

S.E.ofregression0.117006criterion-1.302176

Schwarz

Sumsquaredresid0.205355criterion-1.153780

Hannan-Quinn

Loglikelihood14.71958criter.-1.281714

Durbin-Watson

F-statistic542.8930stat0.684080

Prob(P-statiStic)0.000000

模型为lny=-10.81090+1.5737841nx2+0.002438x3

检验：经济意义为其他条件不变的情况下，工业增加值每增加一个单

位百分比出口货物总和增加1.57单位百分比，汇率每增加一单位百

分比，出口总额增加0.0024个单位百分比。

拟合优度检验，R八2=0.986373修正可决系数为0.984556,拟合很好。

F检验对于HO:X2=X3=O,给定显著性水平a=0.05F(2,15)=4.77

F=542.8930>F(2,15)显著

t检验对于H0:Xj=0(j=2,3),给定显著性水平a=0.05t(15)=2.131

当j=2时显著，当j=3时显著。

(3)两个模型表现出的汇率对Y的印象存在巨大差异

3.3

⑴用Eviews分析如下

DependentVariable:Y

Method:LeastSquares

Date:12/01/14Time:20:30

Sample:118

Includedobservations:18

VariableCoefficientStd.Errort-StatisticProb.

X0.0864500.0293632.9441860.0101

T52.370315.20xx6710.067020.0000

C-50.0163849.46026-1.0112440.3279

R-squared0.951235Meandependentvar755.1222

AdjustedR-squared0.944732S.D.dependentvar258.7206

S.E.ofregression60.82273Akaikeinfocriterion11.20482

Sumsquaredresid55491.07Schwarzcriterion11.35321

Loglikelihood-97.84334Hannan-Quinncriter.11.22528

F-statistic146.2974Durbin-Watsonstat2.605783

Prob(F-statistic)0.000000

由表可知模型为：Y=0.086450X+52.3703IT-50.01638

检验：可决系数是0.951235,修正的可决系数为0.944732,说明模型

对样本拟合较好。

F检验，F=539.7364>F[2,15)=4.77,回归方程显著。

t检验，t统计量分别为2.944186,10.06702,均大于t(15)=2.131,

所以这些系数都是显著的。

经济意义：家庭月平均收入增加1元，家庭书刊年消费支出增加

0.086450元，户主受教育年数增加1年，家庭书刊年消费支出增加

52.37031元。

R-squared0.483182Meandependentvar1942.933

AdjustedR-squared0.450881S.D.dependentvar698.8325

S.E.ofregression517.8529Akaikeinfocriterion15.44170

Sumsquaredresid4290746.Schwarzcriterion15.54063

Loglikelihood-136.9753Hannan-Quinncriter.15.45534

F-statistic14.95867Durbin-Watsonstat1.052251

Prob(F-statistic)0.001364

模型：x=123.1516T+444.5888

(3)对残差模型进展分析，用Eviews分析如下

DependentVariable:El

Method:LeastSquares

Date:12/03/14Time:20:39

Sample:118

Includedobservations:18

VariableCoefficientStd.Errort-StatisticProb.

E20.0864500.0284313.0407420.0078

C3.96E-1413.880832.85E-151.0000

R-squared0.366239Meandependentvar2.30E-14

AdjustedR-squared0.326629S.D.dependentvar71.76693

S.E.ofregression58.89136Akaikeinfocriterion11.09370

Sumsquaredresid55491.07Schwarzcriterion11.19264

Loglikelihood-97.84334Hannan-Quinncriter.11.10735

F-statistic9.246111Durbin-Watsonstat2.605783

Prob(F-statistic)0.007788

模型：E]=0.086450E2+3.96e-14

参数：斜率系数a为0.086450,截距为3.96e-14

(4)由上可知，02与a2的系数是一样的。回归系数与被解释变量

的残差系数是一样的，它们的变化规律是一致的。

3.4

为了分析中国税收收入（Y）与国内生产总值（X2）、财政支出（X3）、

商品零售价格指数（X4）的关系，利用1978〜2007年的数据，用EViews

作回归，局部结果如下：

表3回归结果

DependentVariable:LNY

Method:LeastSquares

Date:06/30/13Time:19:39

Sample:19782007

Includedobservations:30

VariableCoefficientStd.Errort-StatisticProb.

C-2.7553670.640080(1)0.0002

LNX20.451234(2)3.1748310.0038

LNX30.6271330.161566(3)0.0006

X4(4)0.0056451.7955670.0842

R-squared0.987591Meandependentvar8.341376

AdjustedR-squared(5)S.D.dependentvar1.357225

S.E.ofregression(6)Akaikeinfocriterion-0.707778

Sumsquaredresid0.662904Schwarzcriterion-0.520952

Loglikelihood14.61668F-statistic(7)

Durbin-Watsonstat0.616136Prob(F-statistic)().000000

填补表中空缺数据:

-2.755367

⑴tc=0.640080=4.304723

0.451234

⑵=3.174831=0.130789

0.627133

(3)=0.161566=3.881590

(4)=0005645x1.795567=().()10136

1-(1-0.987591)—

⑸I二26=0.986159

6)S.Eofregression回归标准差

sumsquaredresid/0.622904

=vn-kJ26=0.154783

R2n-k0.98759126

⑺=\-R2>7^7=1-0.987591*30=689.751148

②分析回归结果：

根据图中数据，模型估计的结果与为：

InY=-