计量经济学第三版(庞浩)版课后答案全

计量经济学第三版(庞浩)版课后答案全第二章2.2（1）①对于浙江省预算收入与全省生产总值的模型，用Eviews分析结果如下：DependentVariable:YMethod:LeastSquaresDate:12/03/14Time:17:00Sample(adjusted):133Includedobservations:33afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.

X0.1761240.00407243.256390.0000C-154.306339.08196-3.9482740.0004R-squared0.983702

Meandependentvar902.5148AdjustedR-squared0.983177

S.D.dependentvar1351.009S.E.ofregression175.2325

Akaikeinfocriterion13.22880Sumsquaredresid951899.7

Schwarzcriterion13.31949Loglikelihood-216.2751

Hannan-Quinncriter.13.25931F-statistic1871.115

Durbin-Watsonstat0.100021Prob(F-statistic)0.000000②由上可知，模型的参数：斜率系数0.176124，截距为—154.3063③关于浙江省财政预算收入与全省生产总值的(3)对于浙江省预算收入对数与全省生产总值对数的模型，由Eviews分析结果如下：DependentVariable:LNYMethod:LeastSquaresDate:12/03/14Time:18:00Sample(adjusted):133Includedobservations:33afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.

LNX0.9802750.03429628.582680.0000C-1.9182890.268213-7.1521210.0000R-squared0.963442

Meandependentvar5.573120AdjustedR-squared0.962263

S.D.dependentvar1.684189S.E.ofregression0.327172

Akaikeinfocriterion0.662028Sumsquaredresid3.318281

Schwarzcriterion0.752726Loglikelihood-8.923468

Hannan-Quinncriter.0.692545F-statistic816.9699

Durbin-Watsonstat0.096208Prob(F-statistic)0.000000①模型方程为：lnY=0.980275lnX-1.918289②由上可知，模型的参数：斜率系数为0.980275，截距为-1.918289③关于浙江省财政预算收入与全省生产总值的模型，检验其显著性：1）可决系数为0.963442，说明所建模型整体上对样本数据拟合较好。2）对于回归系数的t检验：t（β2）=28.58268>t0.025(31)=2.0395，对斜率系数的显著性检验表明，全省生产总值对财政预算总收入有显著影响。④经济意义：全省生产总值每增长1%，财政预算总收入增长0.980275%2.4（1）对建筑面积与建造单位成本模型，用Eviews分析结果如下：DependentVariable:YMethod:LeastSquaresDate:12/01/14Time:12:40Sample:112Includedobservations:12VariableCoefficientStd.Errort-StatisticProb.

X-64.184004.809828-13.344340.0000C1845.47519.2644695.796880.0000R-squared0.946829

Meandependentvar1619.333AdjustedR-squared0.941512

S.D.dependentvar131.2252S.E.ofregression31.73600

Akaikeinfocriterion9.903792Sumsquaredresid10071.74

Schwarzcriterion9.984610Loglikelihood-57.42275

Hannan-Quinncriter.9.873871F-statistic178.0715

Durbin-Watsonstat1.172407Prob(F-statistic)0.000000由上可得：建筑面积与建造成本的回归方程为：Y=1845.475--64.18400X（2）经济意义：建筑面积每增加1万平方米，建筑单位成本每平方米减少64.18400元。（3）①首先进行点预测，由Y=1845.475--64.18400X得，当x=4.5，y=1556.647②再进行区间估计：用Eviews分析： YX

Mean

1619.333

3.523333

Median

1630.000

3.715000

Maximum

1860.000

6.230000

Minimum

1419.000

0.600000

Std.Dev.

131.2252

1.989419

Skewness

0.003403-0.060130

Kurtosis

2.346511

1.664917

Jarque-Bera

0.213547

0.898454

Probability

0.898729

0.638121

Sum

19432.00

42.28000

SumSq.Dev.

189420.7

43.53567

Observations

12

12由上表可知，∑x2=∑（Xi—X）2=δ2x(n—1)=

1.9894192x(12—1)=43.5357(Xf—X)2=(4.5—

3.523333)2=0.95387843当Xf=4.5时，将相关数据代入计算得到：1556.647—2.228x31.73600x√1/12+43.5357/0.95387843≤Yf≤1556.647+2.228x31.73600x√1/12+43.5357/0.95387843即Yf的置信区间为（1556.647—478.1231,1556.647+478.1231）第三章3.2１）对出口货物总额计量经济模型，用Eviews分析结果如下：：DependentVariable:YMethod:LeastSquaresDate:12/01/14Time:20:25Sample:19942011Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

X20.1354740.01279910.584540.0000X318.853489.7761811.9285120.0729C-18231.588638.216-2.1105730.0520R-squared0.985838

Meandependentvar6619.191AdjustedR-squared0.983950

S.D.dependentvar5767.152S.E.ofregression730.6306

Akaikeinfocriterion16.17670Sumsquaredresid8007316.

Schwarzcriterion16.32510Loglikelihood-142.5903

Hannan-Quinncriter.16.19717F-statistic522.0976

Durbin-Watsonstat1.173432Prob(F-statistic)0.000000①由上可知，模型为：Y=0.135474X2+18.85348X3-18231.58②对模型进行检验： 1）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2）F检验，F=522.0976>F（2,15）=4.77，回归方程显著3）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1.928512，小于t（15）=2.131，说明此系数是不显著的。（2）对于对数模型，用Eviews分析结果如下：DependentVariable:LNYMethod:LeastSquaresDate:12/01/14Time:20:25Sample:19942011Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

LNX21.5642210.08898817.577890.0000LNX31.7606950.6821152.5812290.0209C-20.520485.432487-3.7773630.0018R-squared0.986295

Meandependentvar8.400112AdjustedR-squared0.984467

S.D.dependentvar0.941530S.E.ofregression0.117343

Akaikeinfocriterion-1.296424Sumsquaredresid0.206540

Schwarzcriterion-1.148029Loglikelihood14.66782

Hannan-Quinncriter.-1.275962F-statistic539.7364

Durbin-Watsonstat0.686656Prob(F-statistic)0.000000①由上可知，模型为：LNY=-20.52048+1.564221LNX2+1.760695LNX3②对模型进行检验：1）可决系数是0.986295，修正的可决系数为0.984467，说明模型对样本拟合较好。2）F检验，F=539.7364>F（2,15）=4.77，回归方程显著。3）t检验，t统计量分别为-3.777363，17.57789，2.581229，均大于t（15）=2.131，所以这些系数都是显著的。（3）①（1）式中的经济意义：工业增加1亿元，出口货物总额增加0.135474亿元，人民币汇率增加1，出口货物总额增加18.85348亿元。②（2）式中的经济意义：工业增加额每增加1%，出口货物总额增加1.564221%，人民币汇率每增加1%，出口货物总额增加1.760695%3.3（1）对家庭书刊消费对家庭月平均收入和户主受教育年数计量模型，由Eviews分析结果如下：DependentVariable:YMethod:LeastSquaresDate:12/01/14Time:20:30Sample:118Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

X0.0864500.0293632.9441860.0101T52.370315.20216710.067020.0000C-50.0163849.46026-1.0112440.3279R-squared0.951235

Meandependentvar755.1222AdjustedR-squared0.944732

S.D.dependentvar258.7206S.E.ofregression60.82273

Akaikeinfocriterion11.20482Sumsquaredresid55491.07

Schwarzcriterion11.35321Loglikelihood-97.84334

Hannan-Quinncriter.11.22528F-statistic146.2974

Durbin-Watsonstat2.605783Prob(F-statistic)0.000000①模型为：Y=0.086450X+52.37031T-50.01638②对模型进行检验：1）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。2）F检验，F=539.7364>F（2,15）=4.77，回归方程显著。3）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。③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。（2）用Eviews分析：①DependentVariable:YMethod:LeastSquaresDate:12/01/14Time:22:30Sample:118Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

T63.016764.54858113.854160.0000C-11.5817158.02290-0.1996060.8443R-squared0.923054

Meandependentvar755.1222AdjustedR-squared0.918245

S.D.dependentvar258.7206S.E.ofregression73.97565

Akaikeinfocriterion11.54979Sumsquaredresid87558.36

Schwarzcriterion11.64872Loglikelihood-101.9481

Hannan-Quinncriter.11.56343F-statistic191.9377

Durbin-Watsonstat2.134043Prob(F-statistic)0.000000②DependentVariable:XMethod:LeastSquaresDate:12/01/14Time:22:34Sample:118Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

T123.151631.841503.8676440.0014C444.5888406.17861.0945650.2899R-squared0.483182

Meandependentvar1942.933AdjustedR-squared0.450881

S.D.dependentvar698.8325S.E.ofregression517.8529

Akaikeinfocriterion15.44170Sumsquaredresid4290746.

Schwarzcriterion15.54063Loglikelihood-136.9753

Hannan-Quinncriter.15.45534F-statistic14.95867

Durbin-Watsonstat1.052251Prob(F-statistic)0.001364以上分别是y与T，X与T的一元回归模型分别是：Y=63.01676T-11.58171X=123.1516T+444.5888（3）对残差进行模型分析，用Eviews分析结果如下：DependentVariable:E1Method:LeastSquaresDate:12/03/14Time:20:39Sample:118Includedobservations:18VariableCoefficientStd.Errort-StatisticProb.

E20.0864500.0284313.0407420.0078C3.96E-1413.880832.85E-151.0000R-squared0.366239

Meandependentvar2.30E-14AdjustedR-squared0.326629

S.D.dependentvar71.76693S.E.ofregression58.89136

Akaikeinfocriterion11.09370Sumsquaredresid55491.07

Schwarzcriterion11.19264Loglikelihood-97.84334

Hannan-Quinncriter.11.10735F-statistic9.246111

Durbin-Watsonstat2.605783Prob(F-statistic)0.007788模型为：E1=0.086450E2+3.96e-14参数：斜率系数α为0.086450，截距为3.96e-14（3）由上可知，β2与α2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。第五章5.3(1)由Eviews软件分析得：DependentVariable:YMethod:LeastSquaresDate:12/10/14Time:16:00Sample:131Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.

X1.2442810.07903215.744110.0000C242.4488291.19400.8326020.4119R-squared0.895260

Meandependentvar4443.526AdjustedR-squared0.891649

S.D.dependentvar1972.072S.E.ofregression649.1426

Akaikeinfocriterion15.85152Sumsquaredresid12220196

Schwarzcriterion15.94404Loglikelihood-243.6986

Hannan-Quinncriter.15.88168F-statistic247.8769

Durbin-Watsonstat1.078581Prob(F-statistic)0.000000由上表可知，2007年我国农村居民家庭人均消费支出（x）对人均纯收入（y）的模型为：Y=1.244281X+242.4488（2）①由图形法检验由上图可知，模型可能存在异方差。②Goldfeld-Quanadt检验1）定义区间为1-12时，由软件分析得：DependentVariable:Y1Method:LeastSquaresDate:12/10/14Time:11:34Sample:112Includedobservations:12VariableCoefficientStd.Errort-StatisticProb.

X11.4852960.5003862.9682970.0141C-550.54921220.063-0.4512470.6614R-squared0.468390

Meandependentvar3052.950AdjustedR-squared0.415229

S.D.dependentvar550.5148S.E.ofregression420.9803

Akaikeinfocriterion15.07406Sumsquaredresid1772245.

Schwarzcriterion15.15488Loglikelihood-88.44437

Hannan-Quinncriter.15.04414F-statistic8.810789

Durbin-Watsonstat2.354167Prob(F-statistic)0.014087得∑e1i2=1772245.2）定义区间为20-31时，由软件分析得：DependentVariable:Y1Method:LeastSquaresDate:12/10/14Time:16:36Sample:2031Includedobservations:12VariableCoefficientStd.Errort-StatisticProb.

X11.0869400.1488637.3016230.0000C1173.307733.25201.6001410.1407R-squared0.842056

Meandependentvar6188.329AdjustedR-squared0.826262

S.D.dependentvar2133.692S.E.ofregression889.3633

Akaikeinfocriterion16.56990Sumsquaredresid7909670.

Schwarzcriterion16.65072Loglikelihood-97.41940

Hannan-Quinncriter.16.53998F-statistic53.31370

Durbin-Watsonstat2.339767Prob(F-statistic)0.000026得∑e2i2=7909670.3）根据Goldfeld-Quanadt检验，F统计量为：F=∑e2i2/∑e1i2=7909670./1772245=4.4631在α=0.05水平下，分子分母的自由度均为10，查分布表得临界值F0.05（10,10）=2.98，因为F=4.4631>F0.05（10,10）=2.98，所以拒绝原假设，此检验表明模型存在异方差。（3）1）采用WLS法估计过程中，①用权数w1=1/X,建立回归得：DependentVariable:YMethod:LeastSquaresDate:12/09/14Time:11:13Sample:131Includedobservations:31Weightingseries:W1VariableCoefficientStd.Errort-StatisticProb.

X1.4258590.11910411.971570.0000C-334.8131344.3523-0.9722980.3389WeightedStatisticsR-squared0.831707

Meandependentvar3946.082AdjustedR-squared0.825904

S.D.dependentvar536.1907S.E.ofregression536.6796

Akaikeinfocriterion15.47102Sumsquaredresid8352726.

Schwarzcriterion15.56354Loglikelihood-237.8008

Hannan-Quinncriter.15.50118F-statistic143.3184

Durbin-Watsonstat1.369081Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.875855

Meandependentvar4443.526AdjustedR-squared0.871574

S.D.dependentvar1972.072S.E.ofregression706.7236

Sumsquaredresid14484289Durbin-Watsonstat1.532908

对此模型进行White检验得：HeteroskedasticityTest:WhiteF-statistic0.299395

Prob.F(2,28)0.7436Obs*R-squared0.649065

Prob.Chi-Square(2)0.7229ScaledexplainedSS1.798067

Prob.Chi-Square(2)0.4070TestEquation:DependentVariable:WGT_RESID^2Method:LeastSquaresDate:12/10/14Time:21:13Sample:131Includedobservations:31CollineartestregressorsdroppedfromspecificationVariableCoefficientStd.Errort-StatisticProb.

C61927.891045682.0.0592220.9532WGT^2-593927.91173622.-0.5060640.6168X*WGT^2282.4407747.97800.3776060.7086R-squared0.020938

Meandependentvar269442.8AdjustedR-squared-0.048995

S.D.dependentvar689166.5S.E.ofregression705847.6

Akaikeinfocriterion29.86395Sumsquaredresid1.40E+13

Schwarzcriterion30.00273Loglikelihood-459.8913

Hannan-Quinncriter.29.90919F-statistic0.299395

Durbin-Watsonstat1.922336Prob(F-statistic)0.743610从上可知，nR2=0.649065，比较计算的统计量的临界值，因为nR2=0.649065<0.05（2）=5.9915，所以接受原假设，该模型消除了异方差。估计结果为：Y=1.425859X-334.8131t=（11.97157）（-0.972298）R2=0.875855F=143.3184DW=1.369081②用权数w2=1/x2,用回归分析得：DependentVariable:YMethod:LeastSquaresDate:12/09/14Time:21:08Sample:131Includedobservations:31Weightingseries:W2VariableCoefficientStd.Errort-StatisticProb.

X1.5570400.14539210.709220.0000C-693.1946376.4760-1.8412720.0758WeightedStatisticsR-squared0.798173

Meandependentvar3635.028AdjustedR-squared0.791214

S.D.dependentvar1029.830S.E.ofregression466.8513

Akaikeinfocriterion15.19224Sumsquaredresid6320554.

Schwarzcriterion15.28475Loglikelihood-233.4797

Hannan-Quinncriter.15.22240F-statistic114.6875

Durbin-Watsonstat1.562975Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.834850

Meandependentvar4443.526AdjustedR-squared0.829156

S.D.dependentvar1972.072S.E.ofregression815.1229

Sumsquaredresid19268334Durbin-Watsonstat1.678365

对此模型进行White检验得：HeteroskedasticityTest:WhiteF-statistic0.299790

Prob.F(3,27)0.8252Obs*R-squared0.999322

Prob.Chi-Square(3)0.8014ScaledexplainedSS1.789507

Prob.Chi-Square(3)0.6172TestEquation:DependentVariable:WGT_RESID^2Method:LeastSquaresDate:12/10/14Time:21:29Sample:131Includedobservations:31VariableCoefficientStd.Errort-StatisticProb.

C-111661.8549855.7-0.2030750.8406WGT^2426220.22240181.0.1902620.8505X^2*WGT^20.1948880.5163950.3774020.7088X*WGT^2-583.21512082.820-0.2800120.7816R-squared0.032236

Meandependentvar203888.8AdjustedR-squared-0.075293

S.D.dependentvar419282.0S.E.ofregression434780.1

Akaikeinfocriterion28.92298Sumsquaredresid5.10E+12

Schwarzcriterion29.10801Loglikelihood-444.3062

Hannan-Quinncriter.28.98330F-statistic0.299790

Durbin-Watsonstat1.835854Prob(F-statistic)0.825233从上可知，nR2=0.999322，比较计算的统计量的临界值，因为nR2=0.999322<0.05（2）=5.9915，所以接受原假设，该模型消除了异方差。估计结果为：Y=1.557040X-693.1946t=（10.70922）（-1.841272）R2=0.798173F=114.6875DW=1.562975③用权数w3=1/sqr（x）,用回归分析得：DependentVariable:YMethod:LeastSquaresDate:12/09/14Time:21:35Sample:131Includedobservations:31Weightingseries:W3VariableCoefficientStd.Errort-StatisticProb.

X1.3301300.09834513.525070.0000C-47.40242313.1154-0.1513900.8807WeightedStatisticsR-squared0.863161

Meandependentvar4164.118AdjustedR-squared0.858442

S.D.dependentvar991.2079S.E.ofregression586.9555

Akaikeinfocriterion15.65012Sumsquaredresid9990985.

Schwarzcriterion15.74263Loglikelihood-240.5768

Hannan-Quinncriter.15.68027F-statistic182.9276

Durbin-Watsonstat1.237664Prob(F-statistic)0.000000UnweightedStatisticsR-squared0.890999

Meandependentvar4443.526AdjustedR-squared0.887240

S.D.dependentvar1972.072S.E.ofregression662.2171

Sumsquaredresid12717412Durbin-Watsonstat1.314859

对此模型进行White检验得：HeteroskedasticityTest:WhiteF-statistic0.423886

Prob.F(2,28)0.6586Obs*R-squared0.911022

Prob.Chi-Square(2)0.6341ScaledexplainedSS2.768332

Prob.Chi-Square(2)0.2505TestEquation:DependentVariable:WGT_RESID^2Method:LeastSquaresDate:12/09/14Time:20:36Sample:131Includedobservations:31CollineartestregressorsdroppedfromspecificationVariableCoefficientStd.Errort-StatisticProb.

C1212308.2141958.0.5659810.5759WGT^2-715673.01301839.-0.5497400.5869X^2*WGT^2-0.0151940.082276-0.1846770.8548R-squared0.029388

Meandependentvar322289.8AdjustedR-squared-0.039942

S.D.dependentvar863356.7S.E.ofregression880429.8

Akaikeinfocriterion30.30597Sumsquaredresid2.17E+13

Schwarzcriterion30.44475Loglikelihood-466.7426

Hannan-Quinncriter.30.35121F-statistic0.423886

Durbin-Watsonstat1.887426Prob(F-statistic)0.658628从上可知，nR2=0.911022，比较计算的统计量的临界值，因为nR2=0.911022<0.05（2）=5.9915，所以接受原假设，该模型消除了异方差。估计结果为：Y=1.330130X-47.40242t=（13.52507）（-0.151390）R2=0.863161F=182.9276DW=1.237664经过检验发现，用权数w1的效果最好，所以综上可知，即修改后的结果为：Y=1.425859X-334.8131t=（11.97157）（-0.972298）R2=0.875855F=143.3184DW=1.369081第六章6.1(1)建立居民收入-消费模型，用Eviews分析结果如下：DependentVariable:YMethod:LeastSquaresDate:12/20/14Time:14:22Sample:119Includedobservations:19VariableCoefficientStd.Errort-StatisticProb.

X0.6904880.01287753.620680.0000C79.9300412.399196.4463900.0000R-squared0.994122

Meandependentvar700.2747AdjustedR-squared0.993776

S.D.dependentvar246.4491S.E.ofregression19.44245

Akaikeinfocriterion8.872095Sumsquaredresid6426.149

Schwarzcriterion8.971510Loglikelihood-82.28490

Hannan-Quinncriter.8.888920F-statistic2875.178

Durbin-Watsonstat0.574663Prob(F-statistic)0.000000所得模型为： Y=0.690488X+79.93004Se=(0.012877)(12.39919)

t=(53.62068)(6.446390)R2=0.994122F=2875.178DW=0.574663（2）1）检验模型中存在的问题①做出残差图如下：残差的变动有系统模式，连续为正和连续为负，表明残差项存在一阶自相关。②该回归方程可决系数较高，回归系数均显著。对样本量为19，一个解释变量的模型，5%的显著水平，查DW统计表可知，dL=1.180，dU=1.401，模型中DW=0.574663,<dL,显然模型中有自相关。③对模型进行BG检验，用Eviews分析结果如下：Breusch-GodfreySerialCorrelationLMTest:F-statistic4.811108

Prob.F(2,15)0.0243Obs*R-squared7.425088

Prob.Chi-Square(2)0.0244TestEquation:DependentVariable:RESIDMethod:LeastSquaresDate:12/20/14Time:15:03Sample:119Includedobservations:19Presamplemissingvaluelaggedresidualssettozero.VariableCoefficientStd.Errort-StatisticProb.

X-0.0032750.010787-0.3035860.7656C1.92954610.355930.1863230.8547RESID(-1)0.6088860.2927072.0801890.0551RESID(-2)0.0899880.2911200.3091100.7615R-squared0.390794

Meandependentvar-1.65E-13AdjustedR-squared0.268953

S.D.dependentvar18.89466S.E.ofregression16.15518

Akaikeinfocriterion8.587023Sumsquaredresid3914.848

Schwarzcriterion8.785852Loglikelihood-77.57671

Hannan-Quinncriter.8.620672F-statistic3.207406

Durbin-Watsonstat1.570723Prob(F-statistic)0.053468如上表显示，LM=TR2=7.425088，其p值为0.0244，表明存在自相关。2）对模型进行处理：①采取广义差分法a)为估计自相关系数ρ。对et进行滞后一期的自回归，用EViews分析结果如下：DependentVariable:EMethod:LeastSquaresDate:12/20/14Time:15:04Sample(adjusted):219Includedobservations:18afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.

E(-1)0.6573520.1776263.7007590.0018R-squared0.440747

Meandependentvar1.717433AdjustedR-squared0.440747

S.D.dependentvar17.85134S.E.ofregression13.34980

Akaikeinfocriterion8.074833Sumsquaredresid3029.692

Schwarzcriterion8.124298Loglikelihood-71.67349

Hannan-Quinncriter.8.081653Durbin-Watsonstat1.634573由上可知，ρ=0.657352b)对原模型进行广义差分回归，用Eviews进行分析所得结果如下：DependentVariable:Y-0.657352*Y(-1)Method:LeastSquaresDate:12/20/14Time:15:04Sample(adjusted):219Includedobservations:18afteradjustmentsVariableCoefficientStd.Errort-StatisticProb.

C35.977618.1035464.4397370.0004X-0.657352*X(-1)0.6686950.02064232.395120.0000R-squared0.984983

Meandependentvar278.1002AdjustedR-squared0.984044

S.D.dependentvar105.1781S.E.ofregression13.28570

Akaikeinfocriterion8.115693Sumsquaredresid2824.158

Schwarzcriterion8.214623Loglikelihood-71.04124

Hannan-Quinncriter.8.129334F-statistic1049.444

Durbin-Watsonstat1.830746Prob(F-statistic)0.000000由上图可知回归方程为：Yt*=35.97761+0.668695Xt*Se=(8.103546)(0.020642)t=(4.439737)(32.39512)R2=0.984983F=1049.444DW=1.830746式中，Yt*=Yt-0.657352Yt-1,Xt*=Xt-0.657352Xt-1由于使用了广义差分数据，样本容量减少了1个，为18个。查5%显著水平的DW统计表可知，dL=1.158,dU=1.391模型中DW=1,830746，du<DW<4-dU，说明在5%的显著水平下广义差分模型中已无自相关。可决系数R2，t，F统计量也均达到理想水平。由差分方程，β1=35.97761/(1-0.657352)=104.9987由此最终的消费模型为：Yt=104.9987+0.668695Xt

②用科克伦-奥克特迭代法，用EVIews分析结果如下：DependentVariable:YMethod:LeastSquaresDate:12/20/14Time:15:15Sample(adjusted):219Includedobservations:18afteradjustmentsConvergenceachievedafter5iterationsVariableCoefficientStd.Errort-StatisticProb.

C104.044923.876184.3576870.0006X0.6692620.02083132.127570.0000AR(1)0.6300150.1642183.8364620.0016R-squared0.997097

Meandependentvar719.1867AdjustedR-squared0.996710

S.D.dependentvar238.9866S.E.ofregression13.70843

Akaikeinfocriterion8.224910Sumsquaredresid2818.814

Schwarzcriterion8.373306Loglikelihood-71.02419

Hannan-Quinncriter.8.245372F-statistic2575.896

Durbin-Watsonstat1.787878Prob(F-statistic)0.000000InvertedARRoots

.63所得方程为：Yt=104.0449+0.669262Xt

（3）经济意义：人均实际收入每增加1元，平均说来人均时间消费支出将增加0.669262元。6.4（1）针对对数模型，用Eviews分析结果如下：DependentVariable:LNYMethod:LeastSquaresDate:12/27/14Time:16:13Sample:19802000Includedobservations:21VariableCoefficientStd.Errort-StatisticProb.

LNX0.9510900.03889724.451230.0000C2.1710410.2410259.0075290.0000R-squared0.969199

Meandependentvar8.039307AdjustedR-squared0.967578

S.D.dependentvar0.565486S.E.ofregression0.101822

Akaikeinfocriterion-1.640785Sumsquaredresid0.196987

Schwarzcriterion-1.541307Loglikelihood19.22825

Hannan-Quinncriter.-1.619196F-statistic597.8626

Durbin-Watsonstat1.159788Prob(F-statistic)0.000000所得模型为：lnY=0,951090lnX+2.171041se=(0.038897)(0.241025)t=(24.45123)(9.007529)R2=0.969199F=597.8626DW=1.159788

2）检验模型的自相关性该回归方程可决系数较高，回归系数均显著。对样本量为21，一个解释变量的模型，5%的显著水平，查DW统计表可知，dL=1.221，dU=1.420，模型中DW=1.159788<dL,显然模型中有自相关。

(2)用广义差分法处理模型：1）为估计自相关系数ρ。对et进行滞后一期的自回归，用EViews分析结果如下：DependentVariable:EMethod:LeastS