計(jì)量經(jīng)濟(jì)學(xué)第三版龐浩版課后答案

第二章

2.2

(1)

①對于浙江省預(yù)算收入與全省生產(chǎn)總值的模型，用Eviews分析結(jié)果如下:

DependentVariable:Y

Method:LeastSquares

Date:12/03/14Time:17:00

Sample(adjusted):133

Includedobservations:33afteradjustments

Coefficie

VariablentStd.Errort-StatisticProb.??

X0.1761240.00407243.256390.0000

-154.306

C339.08196-3.9482740.0004

????Mean902.514

R-squared0.983702dependentvar8

Adjusted????S.D.dependent1351.00

R-squared0.983177var9

S.E.of????Akaikeinfo13.2288

regression175.2325criterion0

Sumsquared????Schwarz13.3194

resid951899.7criterion9

-216.275????Hannan-Quinn13.2593

LoglikelihoodIcriter.1

????Durbin-Watson0.10002

F-statistic1871.115stat1

Prob(F-statistic)0.000000

②由上可知，模型的參數(shù)：斜率系數(shù)0.176124,截距為一154.3063

③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)?zāi)Ｐ偷娘@著性：

1）可決系數(shù)為0.983702,說明所建模型整體上對樣本數(shù)據(jù)擬合較好。

2）對于回歸系數(shù)的t檢驗(yàn)：t（82）=43.25639>to.o25（31）=2.O395,對斜率系數(shù)的顯

著性檢驗(yàn)表明，全省生產(chǎn)總值對財(cái)政預(yù)算總收入有顯著影響。

④用規(guī)范形式寫出檢驗(yàn)結(jié)果如下：

Y=0.176124X—154.3063

(0.004072)(39.08196)

t=(43.25639)(-3.948274)

R2=0.983702F=1871.115n=33

⑤經(jīng)濟(jì)意義是：全省生產(chǎn)總值每增加1億元，財(cái)政預(yù)算總收入增加0.176124億元。

(2)當(dāng)x=32000時(shí),

①進(jìn)行點(diǎn)預(yù)測，由上可知丫=0.176124X—154.3063,代入可得:

Y=Y=0.176124*32000—154.3063=5481.6617

②進(jìn)行區(qū)間預(yù)測：

先由Eviews分析:

XY

?Mean76000.4417902.5148

?Median72689.2807209.3900

?Maximum727722.3174895.410

?Minimum7123.7200725.87000

?Std.Dev.77608.02171351.009

?Skewness71.43251971.663108

?Kurtosis74.01051574.590432

?Jarque-Ber

a712.69068718.69063

?Probability70.00175570.000087

?Sum7198014.5?29782.99

?SumSq.

Dev.71.85E+09758407195

?Observatio

ns?33?33

由上表可知,

(X—X)2=6\(n—1)=?7608.0212x(33—1)=1852223.473

(X—X)2=(32000—?6000.441)2=675977068.2

當(dāng)Xf=32000時(shí)，將相關(guān)數(shù)據(jù)代入計(jì)算得到：

即Yf的置信區(qū)間為(5481.6617—64.9649,5481.6617+64.9649)

⑶對于浙江省預(yù)算收入對數(shù)與全省生產(chǎn)總值對數(shù)的模型，由Eviews分析結(jié)果如下:

DependentVariable:LNY

Method:LeastSquares

Date:12/03/14Time:18:00

Sample(adjusted):133

Includedobservations:33afteradjustments

Coefficie

VariablentStd.Errort-StatisticProb.??

LNX0.9802750.03429628.582680.0000

-1.91828

C90.268213-7.1521210.0000

????Mean5.57312

R-squared0.963442dependentvar0

Adjusted????S.D.dependent1.68418

R-squared0.962263var9

S.E.of????Akaikeinfo0.66202

regression0.327172criterion8

Sumsquared????Schwarz0.75272

resid3.318281criterion6

-8.92346????Hannan-Quinn0.69254

Loglikelihood8criter.5

????Durbin-Watson0.09620

F-statistic816.9699stat8

Prob(F-statistic)0.000000

①模型方程為：lnY=0.980275lnX-1.918289

②由上可知，模型的參數(shù)：斜率系數(shù)為0.980275,截距為1918289

③關(guān)于浙江省財(cái)政預(yù)算收入與全省生產(chǎn)總值的模型，檢驗(yàn)其顯著性：

1）可決系數(shù)為0.963442,說明所建模型整體上對樣本數(shù)據(jù)擬合較好。

2）對于回歸系數(shù)的t檢驗(yàn)：t（3）=28.58268>to.o25（31）=2.0395,對斜率系數(shù)的顯

著性檢驗(yàn)表明，全省生產(chǎn)總值對財(cái)政預(yù)算總收入有顯著影響。

④經(jīng)濟(jì)意義：全省生產(chǎn)總值每增長1%,財(cái)政預(yù)算總收入增長0.980275%

2.4

(1)對建筑面積與建造單位成本模型，用Eviews分析結(jié)果如下:

DependentVariable:Y

Method:LeastSquares

Date:12/01/14Time:12:40

Sample:112

Includedobservations:12

Coefficie

VariablentStd.Errort-StatisticProb.??

-64.1840

X04.809828-13.344340.0000

C1845.47519.2644695.796880.0000

????Mean1619.33

R-squared0.946829dependentvar3

Adjusted????S.D.dependent131.225

R-squared0.941512var2

S.E.of????Akaikeinfo9.90379

regression31.73600criterion2

Sumsquared????Schwarz9.98461

resid10071.74criterion0

-57.4227????Hannan-Quinn9.87387

Loglikelihood5criter.1

????Durbin-Watson1.17240

F-statistic178.0715stat7

Prob(F-statistic)0.000000

由上可得：建筑面積與建造成本的回歸方程為:

Y=1845.475-64.18400X

(2)經(jīng)濟(jì)意義：建筑面積每增加1萬平方米，建筑單位成本每平方米減少64.18400

7Co

(3)

①首先進(jìn)行點(diǎn)預(yù)測，由Y=1845.475—64.18400X得，當(dāng)x=4.5,y=1556.647

②再進(jìn)行區(qū)間估計(jì):

用Eviews分析:

YX

?Mean71619.333?3.523333

?Median71630.00073.715000

?Maximum71860.00076.230000

?Minimum71419.00070.600000

?Std.Dev.7131.225271.989419

?Skewness70.003403-0.060130

?Kurtosis72.34651171.664917

?Jarque-Ber

a70.21354770.898454

?Probability70.89872970.638121

?Sum719432.00742.28000

?SumSq.

Dev.7189420.7743.53567

?Observatio

ns?12?12

由上表可知,

222

Ex'E(X—X)=6x(n—1)=?1.989419x(12—1)=43.5357

(X—X)2=(4.5—?3.523333)2=0.95387843

當(dāng)Xf=4.5時(shí)，將相關(guān)數(shù)據(jù)代入計(jì)算得到：

1556.647—2.228x31.73600xV1/12+43.5357/0.95387843W

Yf^1556.647+2.228x31.73600xV1/12+43.5357/0.95387843

即Yf的置信區(qū)間為(1556.647—478.1231,1556.647+478.1231)

第三章

3.2

1)對出口貨物總額計(jì)量經(jīng)濟(jì)模型，用Eviews分析結(jié)果如下：：

DependentVariable:Y

Method:LeastSquares

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

Sample:19942011

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

X20.1354740.01279910.584540.0000

X318.853489.7761811.9285120.0729

-18231.5

C88638.216-2.1105730.0520

????Mean6619.19

R-squared0.985838dependentvar1

Adjusted????S.D.dependent5767.15

R-squared0.983950var2

S.E.of????Akaikeinfo16.1767

regression730.6306criterion0

Sumsquared????Schwarz16.3251

resid8007316.criterion0

-142.590????Hannan-Quinn16.1971

Loglikelihood3criter.7

????Durbin-Watson1.17343

F-statistic522.0976stat2

Prob(F-statistic)0.000000

①由上可知，模型為：

Y=0.135474X2+18.85348X3-18231.58

②對模型進(jìn)行檢驗(yàn)：

1)可決系數(shù)是0.985838,修正的可決系數(shù)為0.983950,說明模型對樣本擬合較好

2)F檢驗(yàn),F=522.0976>F(2,15)=4.77,回歸方程顯著

3)t檢驗(yàn)，t統(tǒng)計(jì)量分別為X2的系數(shù)對應(yīng)t值為10.58454,大于t(15)=2.131,

系數(shù)是顯著的，X3的系數(shù)對應(yīng)t值為1.928512,小于t(15)=2.131,說明此系數(shù)

是不顯著的。

(2)對于對數(shù)模型，用Eviews分析結(jié)果如下：

DependentVariable:LNY

Method:LeastSquares

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

Sample:19942011

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

LNX21.5642210.08898817.577890.0000

LNX31.7606950.6821152.5812290.0209

-20.5204

C85.432487-3.7773630.0018

????Mean8.40011

R-squared0.986295dependentvar2

Adjusted????S.D.dependent0.94153

R-squared0.984467var0

S.E.of????Akaikeinfo-1.2964

regression0.117343criterion24

Sumsquared????Schwarz-1.1480

resid0.206540criterion29

????Hannan-Quinn-1.2759

Loglikelihood14.66782criter.62

????Durbin-Watson0.68665

F-statistic539.7364stat6

Prob(F-statistic)0.000000

①由上可知，模型為：

LNY=-20.52048+1.564221LNX2+1.760695LNX3

②對模型進(jìn)行檢驗(yàn)：

1)可決系數(shù)是0.986295,修正的可決系數(shù)為0.984467,說明模型對樣本擬合較好。

2)F檢驗(yàn),F=539.7364>F(2,15)=4.77,回歸方程顯著。

3)t檢驗(yàn),t統(tǒng)計(jì)量分別為-3.777363,17.57789,2.581229,均大于t(15)=2.131,

所以這些系數(shù)都是顯著的。

(3)

①(1)式中的經(jīng)濟(jì)意義：工業(yè)增加1億元，出口貨物總額增加0.135474億元，人

民幣匯率增加1,出口貨物總額增加18.85348億元。

②（2）式中的經(jīng)濟(jì)意義：工業(yè)增加額每增力口1%,出口貨物總額增加1.564221%,人

民幣匯率每增加1%,出口貨物總額增加1.760695%

3.3

（1）對家庭書刊消費(fèi)對家庭月平均收入和戶主受教育年數(shù)計(jì)量模型，由Eviews分析

結(jié)果如下：

DependentVariable:Y

Method:LeastSquares

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

Sample:118

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

X0.0864500.0293632.9441860.0101

T52.370315.20216710.067020.0000

-50.0163

C849.46026-1.0112440.3279

????Mean755.122

R-squared0.951235dependentvar2

Adjusted????S.D.dependent258.720

R-squared0.944732var6

S.E.of????Akaikeinfo11.2048

regression60.82273criterion2

Sumsquared????Schwarz11.3532

resid55491.07criterion1

-97.8433????Hannan-Quinn11.2252

Loglikelihood4criter.8

????Durbin-Watson2.60578

F-statistic146.2974stat3

Prob(F-statistic)0.000000

①模型為：Y=0.086450X+52.37031T-50.01638

②對模型進(jìn)行檢驗(yàn):

1）可決系數(shù)是0.951235,修正的可決系數(shù)為0.944732,說明模型對樣本擬合較好。

2)F檢驗(yàn),F=539.7364>F(2,15)=4.77,回歸方程顯著。

3)t檢驗(yàn)，t統(tǒng)計(jì)量分別為2.944186,10.06702,均大于t(15)=2.131,所以這

些系數(shù)都是顯著的。

③經(jīng)濟(jì)意義：家庭月平均收入增加1元，家庭書刊年消費(fèi)支出增加0.086450元，戶

主受教育年數(shù)增加1年，家庭書刊年消費(fèi)支出增加52.37031元。

(2)用Eviews分析：

①

DependentVariable:Y

Method:LeastSquares

Date:12/01/14Time:22:30

Sample:118

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

T63.016764.54858113.854160.0000

-11.5817

C158.02290-0.1996060.8443

????Mean755.122

R-squared0.923054dependentvar2

Adjusted????S.D.dependent258.720

R-squared0.918245var6

S.E.of????Akaikeinfo11.5497

regression73.97565criterion9

Sumsquared????Schwarz11.6487

resid87558.36criterion2

-101.948????Hannan-Quinn11.5634

Loglikelihood1criter.3

????Durbin-Watson2.13404

F-statistic191.9377stat3

Prob(F-statistic)0.000000

②

DependentVariable:X

Method:LeastSquares

Date:12/01/14Time:22:34

Sample:118

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

T123.151631.841503.8676440.0014

C444.5888406.17861.0945650.2899

????Mean1942.93

R-squared0.483182dependentvar3

Adjusted????S.D.dependent698.832

R-squared0.450881var5

S.E.of????Akaikeinfo15.4417

regression517.8529criterion0

Sumsquared????Schwarz15.5406

resid4290746.criterion3

-136.975????Hannan-Quinn15.4553

Loglikelihood3criter.4

????Durbin-Watson1.05225

F-statistic14.95867stat1

Prob(F-statistic)0.001364

以上分別是y與T,X與T的一元回歸

模型分別是：

Y=63.01676T-11.58171

X=123,1516T+444.5888

(3)對殘差進(jìn)行模型分析，用Eviews分析結(jié)果如下：

DependentVariable:E1

Method:LeastSquares

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

Sample:118

Includedobservations:18

Coefficie

VariablentStd.Errort-StatisticProb.??

E20.0864500.0284313.0407420.0078

C3.96E-1413.880832.85E-151.0000

????Mean2.30E-1

R-squared0.366239dependentvar4

Adjusted????S.D.dependent71.7669

R-squared0.326629var3

S.E.of????Akaikeinfo11.0937

regression58.89136criterion0

Sumsquared????Schwarz11.1926

resid55491.07criterion4

-97.8433????Hannan-Quinn11.1073

Loglikelihood4criter.5

????Durbin-Watson2.60578

F-statistic9.246111stat3

Prob(F-statistic)0.007788

模型為：

Ei=0.086450E2+3.96e-14

參數(shù)：斜率系數(shù)a為0.086450,截距為3.96e-14

(3)由上可知，B2與a2的系數(shù)是一樣的。回歸系數(shù)與被解釋變量的殘差系數(shù)是一

樣的，它們的變化規(guī)律是一致的。

第五章

5.3

(1)由Eviews軟件分析得：

DependentVariable:Y

Method:LeastSquares

Date:12/10/14Time:16:00

Sample:131

Includedobservations:31

Coefficie

VariablentStd.Errort-StatisticProb.??

X1.2442810.07903215.744110.0000

C242.4488291.19400.8326020.4119

????Mean4443.52

R-squared0.895260dependentvar6

Adjusted????S.D.dependent1972.07

R-squared0.891649var2

S.E.of????Akaikeinfo15.8515

regression649.1426criterion2

Sumsquared1222019????Schwarz15.9440

resid6criterion4

-243.698????Hannan-Quinn15.8816

Loglikelihood6criter.8

????Durbin-Watson1.07858

F-statistic247.8769stat1

Prob(F-statistic)0.000000

由上表可知，2007年我國農(nóng)村居民家庭人均消費(fèi)支出（x）對人均純收入（y）的模

型為：

Y=1.244281X+242.4488

（2）

①由圖形法檢驗(yàn)

由上圖可知，模型可能存在異方差。

②Goldfeld-Quanadt檢驗(yàn)

1）定義區(qū)間為1-12時(shí)，由軟件分析得:

DependentVariable:Y1

Method:LeastSquares

Date:12/10/14Time:11:34

Sample:112

Includedobservations:12

Coefficie

VariablentStd.Errort-StatisticProb.??

X11.4852960.5003862.9682970.0141

-550.549

C21220.063-0.4512470.6614

????Mean3052.95

R-squared0.468390dependentvar0

Adjusted????S.D.dependent550.514

R-squared0.415229var8

S.E.of????Akaikeinfo15.0740

regression420.9803criterion6

Sumsquared????Schwarz15.1548

resid1772245.criterion8

-88.4443????Hannan-Quinn15.0441

Loglikelihood7criter.4

????Durbin-Watson2.35416

F-statistic8.810789stat7

Prob(F-statistic)0.014087

得￡eii2=1772245.

2)定義區(qū)間為20-31時(shí)，由軟件分析得:

DependentVariable:Y1

Method:LeastSquares

Date:12/10/14Time:16:36

Sample:2031

Includedobservations:12

Coefficie

VariablentStd.Errort-StatisticProb.??

X11.0869400.1488637.3016230.0000

C1173.307733.25201.6001410.1407

????Mean6188.32

R-squared0.842056dependentvar9

Adjusted????S.D.dependent2133.69

R-squared0.826262var2

S.E.of????Akaikeinfo16.5699

regression889.3633criterion0

Sumsquared????Schwarz16.6507

resid7909670.criterion2

-97.4194????Hannan-Quinn16.5399

LoglikelihoodOcriter.8

????Durbin-Watson2.33976

F-statistic53.31370stat7

Prob(F-statistic)0.000026

得Ee2i2=7909670.

3)根據(jù)Goldfeld-Quanadt檢驗(yàn),F統(tǒng)計(jì)量為:

F=￡e#/￡eii2=7909670./1772245=4.4631

在a=0.05水平下，分子分母的自由度均為10,查分布表得臨界值Fo.o5(10,10)=2.98,

因?yàn)镕=4.4631>F0,05(10,10)=2.98,所以拒絕原假設(shè)，此檢驗(yàn)表明模型存在異方

差。

(3)

1)采用WLS法估計(jì)過程中，

①用權(quán)數(shù)w1=1/X,建立回歸得：

DependentVariable:Y

Method:LeastSquares

Date:12/09/14Time:11:13

Sample:131

Includedobservations:31

Weightingseries:W1

Coefficie

VariablentStd.Errort-StatisticProb.??

X1.4258590.11910411.971570.0000

-334.813

C1344.3523-0.9722980.3389

WeightedStatistics

????Mean3946.08

R-squared0.831707dependentvar2

Adjusted????S.D.dependent536.190

R-squared0.825904var7

S.E.of????Akaikeinfo15.4710

regression536.6796criterion2

Sumsquared????Schwarz15.5635

resid8352726.criterion4

-237.800????Hannan-Quinn15.5011

Loglikelihood8criter.8

????Durbin-Watson1.36908

F-statistic143.3184stat1

Prob(F-statistic)0.000000

Unweighted

Statistics

????Mean4443.52

R-squared0.875855dependentvar6

Adjusted????S.D.dependent1972.07

R-squared0.871574var2

S.E.of????Sumsquared144842

regression706.7236resid89

Durbin-Watson

stat1.532908

對此模型進(jìn)行White檢驗(yàn)得:

HeteroskedasticityTest:White

F-statistic0.299395????Prob.F(2,28)0.7436

????Prob.

Obs*R-squared0.649065Chi-Square(2)0.7229

Scaledexplained????Prob.

SS1.798067Chi-Square(2)0.4070

TestEquation:

DependentVariable:WGT_RESIDA2

Method:LeastSquares

Date:12/10/14Time:21:13

Sample:131

Includedobservations:31

Collineartestregressorsdroppedfromspecification

Coefficie

VariablentStd.Errort-StatisticProb.??

C61927.891045682.0.0592220.9532

-593927.

WGTA291173622.-0.5060640.6168

X*WGTA2282.4407747.97800.3776060.7086

R-squared0.020938????Mean269442.

dependentvar8

Adjusted-0.04899????S.D.dependent689166.

R-squared5var5

S.E.of????Akaikeinfo29.8639

regression705847.6criterion5

Sumsquared1.40E+1????Schwarz30.0027

resid3criterion3

-459.891????Hannan-Quinn29.9091

Loglikelihood3criter.9

????Durbin-Watson1.92233

F-statistic0.299395stat6

Prob(F-statistic)0.743610

從上可知，nR2=0.649065,比較計(jì)算的/統(tǒng)計(jì)量的臨界值,因?yàn)閚R2=0.649065<Z2

0.05(2)=5.9915,所以接受原假設(shè)，該模型消除了異方差

估計(jì)結(jié)果為：

Y=1.425859X-334.8131

t=(11.97157)(-0.972298)

R2=0.875855F=143.3184DW=1.369081

②用權(quán)數(shù)W2=1/x2,用回歸分析得：

DependentVariable:Y

Method:LeastSquares

Date:12/09/14Time:21:08

Sample:131

Includedobservations:31

Weightingseries:W2

Coefficie

VariablentStd.Errort-StatisticProb.??

X1.5570400.14539210.709220.0000

-693.194

C6376.4760-1.8412720.0758

WeightedStatistics

????Mean3635.02

R-squared0.798173dependentvar8

Adjusted????S.D.dependent1029.83

R-squared0.791214var0

S.E.of????Akaikeinfo15.1922

regression466.8513criterion4

Sumsquared????Schwarz15.2847

resid6320554.criterion5

-233.479????Hannan-Quinn15.2224

Loglikelihood7criter.0

????Durbin-Watson1.56297

F-statistic114.6875stat5

Prob(F-statistic)0.000000

Unweighted

Statistics

????Mean4443.52

R-squared0.834850dependentvar6

Adjusted????S.D.dependent1972.07

R-squared0.829156var2

S.E.of????Sumsquared192683

regression815.1229resid34

Durbin-Watson

stat1.678365

對此模型進(jìn)行White檢驗(yàn)得:

HeteroskedasticityTest:White

F-statistic0.299790????Prob.F(3,27)0.8252

????Prob.

Obs*R-squared0.999322Chi-Square(3)0.8014

Scaledexplained????Prob.

SS1.789507Chi-Square(3)0.6172

TestEquation:

DependentVariable:WGT_RESIDA2

Method:LeastSquares

Date:12/10/14Time:21:29

Sample:131

Includedobservations:31

Coefficie

VariablentStd.Errort-StatisticProb.??

-111661.

C8549855.7-0.2030750.8406

WGTA2426220.22240181.0.1902620.8505

XA2*WGTA20.1948880.5163950.3774020.7088

-583.215

X*WGTA212082.820-0.2800120.7816

????Mean203888.

R-squared0.032236dependentvar8

Adjusted-0.07529????S.D.dependent419282.

R-squared3var0

S.E.of????Akaikeinfo28.9229

regression434780.1criterion8

Sumsquared5.10E+1????Schwarz29.1080

resid2criterion1

-444.306????Hannan-Quinn28.9833

Loglikelihood2criter.0

????Durbin-Watson1.83585

F-statistic0.299790stat4

Prob(F-statistic)0.825233

從上可知，nR2=0.999322,比較計(jì)算的/統(tǒng)計(jì)量的臨界值,因?yàn)閚R2=0.999322<Z2

0.05(2)=5.9915,所以接受原假設(shè)，該模型消除了異方差

估計(jì)結(jié)果為：

Y=1.557040X-693.1946

t=(10.70922)(-1.841272)

R2=0.798173F=114.6875DW=1.562975

③用權(quán)數(shù)w3=1/sqr(x)，用回歸分析得：

DependentVariable:Y

Method:LeastSquares

Date:12/09/14Time:21:35

Sample:131

Includedobservations:31

Weightingseries:W3

Coefficie

VariablentStd.Errort-StatisticProb.??

X1.3301300.09834513.525070.0000

-47.4024

C2313.1154-0.1513900.8807

WeightedStatistics

????Mean4164.11

R-squared0.863161dependentvar8

Adjusted????S.D.dependent991.207

R-squared0.858442var9

S.E.of????Akaikeinfo15.6501

regression586.9555criterion2

Sumsquared????Schwarz15.7426

resid9990985.criterion3

-240.576????Hannan-Quinn15.6802

Loglikelihood8criter.7

????Durbin-Watson1.23766

F-statistic182.9276stat4

Prob(F-statistic)0.000000

Unweighted

Statistics

????Mean4443.52

R-squared0.890999dependentvar6

Adjusted????S.D.dependent1972.07

R-squared0.887240var2

S.E.of????Sumsquared127174

regression662.2171resid12

Durbin-Watson

stat1.314859

對此模型進(jìn)行White檢驗(yàn)得:

HeteroskedasticityTest:White

F-statistic0.423886????Prob.F(2,28)0.6586

????Prob.

Obs*R-squared0.911022Chi-Square(2)0.6341

Scaledexplained????Prob.

SS2.768332Chi-Square(2)0.2505

TestEquation:

DependentVariable:WGT_RESIDA2

Method:LeastSquares

Date:12/09/14Time:20:36

Sample:131

Includedobservations:31

Collineartestregressorsdroppedfromspecification

Coefficie

VariablentStd.Errort-StatisticProb.??

C1212308.2141958.0.5659810.5759

-715673.

WGTA201301839.-0.5497400.5869

-0.01519

XA2*WGTA240.082276-0.1846770.8548

????Mean322289.

R-squared0.029388dependentvar8

Adjusted-0.03994????S.D.dependent863356.

R-squared2var7

S.E.of????Akaikeinfo30.3059

regression880429.8criterion7

Sumsquared2.17E+1????Schwarz30.4447

resid3criterion5

-466.742????Hannan-Quinn30.3512

Loglikelihood6criter.1

????Durbin-Watson1.88742

F-statistic0.423886stat6

Prob(F-statistic)0.658628

從上可知，nR2=0.911022,比較計(jì)算的/統(tǒng)計(jì)量的臨界值，因?yàn)閚R2=0.911022</

0.05(2)=5.9915,所以接受原假設(shè)，該模型消除了異方差。

估計(jì)結(jié)果為：

Y=1.330130X-47.40242

t=(13.52507)(-0.151390)

R2=0.863161F=182.9276DW=1.237664

經(jīng)過檢驗(yàn)發(fā)現(xiàn)，用權(quán)數(shù)wl的效果最好，所以綜上可知，即修改后的結(jié)果為：

Y=1.425859X-334.8131

t=(11.97157)(-0.972298)

R2=0.875855F=143.3184DW=1.369081

第六章

6.1

⑴建立居民收入-消費(fèi)模型，用Eviews分析結(jié)果如下:

DependentVariable:Y

Method:LeastSquares

Date:12/20/14Time:14:22

Sample:119

Includedobservations:19

Coefficie

VariablentStd.Errort-StatisticProb.??

X0.6904880.01287753.620680.0000

C79.9300412.399196.4463900.0000

????Mean700.274

R-squared0.994122dependentvar7

Adjusted????S.D.dependent246.449

R-squared0.993776var1

S.E.of????Akaikeinfo8.87209

regression19.44245criterion5

Sumsquared????Schwarz8.97151

resid6426.149criterion0

-82.2849????Hannan-Quinn8.88892

LoglikelihoodOcriter.