计量经济学第三版(庞浩)版课后答案全

第二章2.2（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：Dependent Variable: YMethod: Least SquaresDate: 12/03/14 Time: 17:00Sample (adjusted): 1 33Included observations: 33 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.X0.1761240.00407243.256390.0000C-154.306339.08196-3.9482740.0004R-squared0.983702Mean dependent var902.5148Adjusted R-squared0.983177S.D. dependent var1351.009S.E. of regression175.2325Akaike info criterion13.22880Sum squared resid951899.7Schwarz criterion13.31949Log likelihood-216.2751Hannan-Quinn criter.13.25931F-statistic1871.115Durbin-Watson stat0.100021Prob(F-statistic)0.000000由上可知，模型的参数：斜率系数0.176124，截距为154.3063关于浙江省财政预算收入与全省生产总值的模型，检验模型的显著性：1）可决系数为0.983702，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（2）=43.25639t0.025(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。用规范形式写出检验结果如下：Y=0.176124X154.3063 (0.004072) (39.08196)t= (43.25639) （-3.948274）R2=0.983702 F=1871.115 n=33经济意义是：全省生产总值每增加1亿元，财政预算总收入增加0.176124亿元。（2）当x=32000时，进行点预测，由上可知Y=0.176124X154.3063，代入可得：Y= Y=0.176124*32000154.3063=5481.6617进行区间预测：先由Eviews分析：XYMean6000.441902.5148Median2689.280209.3900Maximum27722.314895.410Minimum123.720025.87000Std. Dev.7608.0211351.009Skewness1.4325191.663108Kurtosis4.0105154.590432Jarque-Bera12.6906818.69063Probability0.0017550.000087Sum198014.529782.99Sum Sq. Dev.1.85E+0958407195Observations3333由上表可知，x2=（XiX）2=2x(n1)= 7608.0212 x (331)=1852223.473(XfX)2=(320006000.441)2=675977068.2当Xf=32000时，将相关数据代入计算得到：5481.66172.0395x175.2325x1/33+1852223.473/675977068.2Yf5481.6617+2.0395x175.2325x1/33+1852223.473/675977068.2即Yf的置信区间为（5481.661764.9649, 5481.6617+64.9649）(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：Dependent Variable: LNYMethod: Least SquaresDate: 12/03/14 Time: 18:00Sample (adjusted): 1 33Included observations: 33 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.LNX0.9802750.03429628.582680.0000C-1.9182890.268213-7.1521210.0000R-squared0.963442Mean dependent var5.573120Adjusted R-squared0.962263S.D. dependent var1.684189S.E. of regression0.327172Akaike info criterion0.662028Sum squared resid3.318281Schwarz criterion0.752726Log likelihood-8.923468Hannan-Quinn criter.0.692545F-statistic816.9699Durbin-Watson stat0.096208Prob(F-statistic)0.000000模型方程为：lnY=0.980275lnX-1.918289由上可知，模型的参数：斜率系数为0.980275，截距为-1.918289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（2）=28.58268t0.025(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。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：Dependent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 12:40Sample: 1 12Included observations: 12VariableCoefficientStd. Errort-StatisticProb.X-64.184004.809828-13.344340.0000C1845.47519.2644695.796880.0000R-squared0.946829Mean dependent var1619.333Adjusted R-squared0.941512S.D. dependent var131.2252S.E. of regression31.73600Akaike info criterion9.903792Sum squared resid10071.74Schwarz criterion9.984610Log likelihood-57.42275Hannan-Quinn criter.9.873871F-statistic178.0715Durbin-Watson stat1.172407Prob(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）首先进行点预测，由Y=1845.475-64.18400X得，当x=4.5，y=1556.647再进行区间估计：用Eviews分析：YXMean1619.3333.523333Median1630.0003.715000Maximum1860.0006.230000Minimum1419.0000.600000Std. Dev.131.22521.989419Skewness0.003403-0.060130Kurtosis2.3465111.664917Jarque-Bera0.2135470.898454Probability0.8987290.638121Sum19432.0042.28000Sum Sq. Dev.189420.743.53567Observations1212由上表可知，x2=（XiX）2=2x(n1)= 1.9894192 x (121)=43.5357(XfX)2=(4.53.523333)2=0.95387843当Xf=4.5时，将相关数据代入计算得到：1556.6472.228x31.73600x1/12+43.5357/0.95387843Yf1556.647+2.228x31.73600x1/12+43.5357/0.95387843即Yf的置信区间为（1556.647478.1231, 1556.647+478.1231）第三章3.2）对出口货物总额计量经济模型，用Eviews分析结果如下：Dependent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 20:25Sample: 1994 2011Included observations: 18VariableCoefficientStd. Errort-StatisticProb.X20.1354740.01279910.584540.0000X318.853489.7761811.9285120.0729C-18231.588638.216-2.1105730.0520R-squared0.985838Mean dependent var6619.191Adjusted R-squared0.983950S.D. dependent var5767.152S.E. of regression730.6306Akaike info criterion16.17670Sum squared resid8007316.Schwarz criterion16.32510Log likelihood-142.5903Hannan-Quinn criter.16.19717F-statistic522.0976Durbin-Watson stat1.173432Prob(F-statistic)0.000000由上可知，模型为：Y = 0.135474X2 + 18.85348X3 - 18231.58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=522.0976F（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：Dependent Variable: LNYMethod: Least SquaresDate: 12/01/14 Time: 20:25Sample: 1994 2011Included observations: 18VariableCoefficientStd. Errort-StatisticProb.LNX21.5642210.08898817.577890.0000LNX31.7606950.6821152.5812290.0209C-20.520485.432487-3.7773630.0018R-squared0.986295Mean dependent var8.400112Adjusted R-squared0.984467S.D. dependent var0.941530S.E. of regression0.117343Akaike info criterion-1.296424Sum squared resid0.206540Schwarz criterion-1.148029Log likelihood14.66782Hannan-Quinn criter.-1.275962F-statistic539.7364Durbin-Watson stat0.686656Prob(F-statistic)0.000000由上可知，模型为：LNY=-20.52048+1.564221 LNX2+1.760695 LNX3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）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）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：Dependent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 20:30Sample: 1 18Included observations: 18VariableCoefficientStd. Errort-StatisticProb.X0.0864500.0293632.9441860.0101T52.370315.20216710.067020.0000C-50.0163849.46026-1.0112440.3279R-squared0.951235Mean dependent var755.1222Adjusted R-squared0.944732S.D. dependent var258.7206S.E. of regression60.82273Akaike info criterion11.20482Sum squared resid55491.07Schwarz criterion11.35321Log likelihood-97.84334Hannan-Quinn criter.11.22528F-statistic146.2974Durbin-Watson stat2.605783Prob(F-statistic)0.000000模型为：Y = 0.086450X + 52.37031T-50.01638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。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：Dependent Variable: YMethod: Least SquaresDate: 12/01/14 Time: 22:30Sample: 1 18Included observations: 18VariableCoefficientStd. Errort-StatisticProb.T63.016764.54858113.854160.0000C-11.5817158.02290-0.1996060.8443R-squared0.923054Mean dependent var755.1222Adjusted R-squared0.918245S.D. dependent var258.7206S.E. of regression73.97565Akaike info criterion11.54979Sum squared resid87558.36Schwarz criterion11.64872Log likelihood-101.9481Hannan-Quinn criter.11.56343F-statistic191.9377Durbin-Watson stat2.134043Prob(F-statistic)0.000000Dependent Variable: XMethod: Least SquaresDate: 12/01/14 Time: 22:34Sample: 1 18Included observations: 18VariableCoefficientStd. Errort-StatisticProb.T123.151631.841503.8676440.0014C444.5888406.17861.0945650.2899R-squared0.483182Mean dependent var1942.933Adjusted R-squared0.450881S.D. dependent var698.8325S.E. of regression517.8529Akaike info criterion15.44170Sum squared resid4290746.Schwarz criterion15.54063Log likelihood-136.9753Hannan-Quinn criter.15.45534F-statistic14.95867Durbin-Watson stat1.052251Prob(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：Dependent Variable: E1Method: Least SquaresDate: 12/03/14 Time: 20:39Sample: 1 18Included observations: 18VariableCoefficientStd. Errort-StatisticProb.E20.0864500.0284313.0407420.0078C3.96E-1413.880832.85E-151.0000R-squared0.366239Mean dependent var2.30E-14Adjusted R-squared0.326629S.D. dependent var71.76693S.E. of regression58.89136Akaike info criterion11.09370Sum squared resid55491.07Schwarz criterion11.19264Log likelihood-97.84334Hannan-Quinn criter.11.10735F-statistic9.246111Durbin-Watson stat2.605783Prob(F-statistic)0.007788模型为：E1 = 0.086450E2 + 3.96e-14参数：斜率系数为0.086450，截距为3.96e-14（3）由上可知，2与2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：Dependent Variable: YMethod: Least SquaresDate: 12/10/14 Time: 16:00Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb.X1.2442810.07903215.744110.0000C242.4488291.19400.8326020.4119R-squared0.895260Mean dependent var4443.526Adjusted R-squared0.891649S.D. dependent var1972.072S.E. of regression649.1426Akaike info criterion15.85152Sum squared resid12220196Schwarz criterion15.94404Log likelihood-243.6986Hannan-Quinn criter.15.88168F-statistic247.8769Durbin-Watson stat1.078581Prob(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）由图形法检验由上图可知，模型可能存在异方差。Goldfeld-Quanadt检验1）定义区间为1-12时，由软件分析得：Dependent Variable: Y1Method: Least SquaresDate: 12/10/14 Time: 11:34Sample: 1 12Included observations: 12VariableCoefficientStd. Errort-StatisticProb.X11.4852960.5003862.9682970.0141C-550.54921220.063-0.4512470.6614R-squared0.468390Mean dependent var3052.950Adjusted R-squared0.415229S.D. dependent var550.5148S.E. of regression420.9803Akaike info criterion15.07406Sum squared resid1772245.Schwarz criterion15.15488Log likelihood-88.44437Hannan-Quinn criter.15.04414F-statistic8.810789Durbin-Watson stat2.354167Prob(F-statistic)0.014087得e1i2=1772245.2）定义区间为20-31时，由软件分析得：Dependent Variable: Y1Method: Least SquaresDate: 12/10/14 Time: 16:36Sample: 20 31Included observations: 12VariableCoefficientStd. Errort-StatisticProb.X11.0869400.1488637.3016230.0000C1173.307733.25201.6001410.1407R-squared0.842056Mean dependent var6188.329Adjusted R-squared0.826262S.D. dependent var2133.692S.E. of regression889.3633Akaike info criterion16.56990Sum squared resid7909670.Schwarz criterion16.65072Log likelihood-97.41940Hannan-Quinn criter.16.53998F-statistic53.31370Durbin-Watson stat2.339767Prob(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=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，用权数w1=1/X,建立回归得：Dependent Variable: YMethod: Least SquaresDate: 12/09/14 Time: 11:13Sample: 1 31Included observations: 31Weighting series: W1VariableCoefficientStd. Errort-StatisticProb.X1.4258590.11910411.971570.0000C-334.8131344.3523-0.9722980.3389Weighted StatisticsR-squared0.831707Mean dependent var3946.082Adjusted R-squared0.825904S.D. dependent var536.1907S.E. of regression536.6796Akaike info criterion15.47102Sum squared resid8352726.Schwarz criterion15.56354Log likelihood-237.8008Hannan-Quinn criter.15.50118F-statistic143.3184Durbin-Watson stat1.369081Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.875855Mean dependent var4443.526Adjusted R-squared0.871574S.D. dependent var1972.072S.E. of regression706.7236Sum squared resid14484289Durbin-Watson stat1.532908对此模型进行White检验得：Heteroskedasticity Test: WhiteF-statistic0.299395Prob. F(2,28)0.7436Obs*R-squared0.649065Prob. Chi-Square(2)0.7229Scaled explained SS1.798067Prob. Chi-Square(2)0.4070Test Equation:Dependent Variable: WGT_RESID2Method: Least SquaresDate: 12/10/14 Time: 21:13Sample: 1 31Included observations: 31Collinear test regressors dropped from specificationVariableCoefficientStd. Errort-StatisticProb.C61927.891045682.0.0592220.9532WGT2-593927.91173622.-0.5060640.6168X*WGT2282.4407747.97800.3776060.7086R-squared0.020938Mean dependent var269442.8Adjusted R-squared-0.048995S.D. dependent var689166.5S.E. of regression705847.6Akaike info criterion29.86395Sum squared resid1.40E+13Schwarz criterion30.00273Log likelihood-459.8913Hannan-Quinn criter.29.90919F-statistic0.299395Durbin-Watson stat1.922336Prob(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=0.6490650.05（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-334.8131 t=（11.97157）（-0.972298）R2=0.875855 F=143.3184 DW=1.369081用权数w2=1/x2,用回归分析得：Dependent Variable: YMethod: Least SquaresDate: 12/09/14 Time: 21:08Sample: 1 31Included observations: 31Weighting series: W2VariableCoefficientStd. Errort-StatisticProb.X1.5570400.14539210.709220.0000C-693.1946376.4760-1.8412720.0758Weighted StatisticsR-squared0.798173Mean dependent var3635.028Adjusted R-squared0.791214S.D. dependent var1029.830S.E. of regression466.8513Akaike info criterion15.19224Sum squared resid6320554.Schwarz criterion15.28475Log likelihood-233.4797Hannan-Quinn criter.15.22240F-statistic114.6875Durbin-Watson stat1.562975Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.834850Mean dependent var4443.526Adjusted R-squared0.829156S.D. dependent var1972.072S.E. of regression815.1229Sum squared resid19268334Durbin-Watson stat1.678365对此模型进行White检验得：Heteroskedasticity Test: WhiteF-statistic0.299790Prob. F(3,27)0.8252Obs*R-squared0.999322Prob. Chi-Square(3)0.8014Scaled explained SS1.789507Prob. Chi-Square(3)0.6172Test Equation:Dependent Variable: WGT_RESID2Method: Least SquaresDate: 12/10/14 Time: 21:29Sample: 1 31Included observations: 31VariableCoefficientStd. Errort-StatisticProb.C-111661.8549855.7-0.2030750.8406WGT2426220.22240181.0.1902620.8505X2*WGT20.1948880.5163950.3774020.7088X*WGT2-583.21512082.820-0.2800120.7816R-squared0.032236Mean dependent var203888.8Adjusted R-squared-0.075293S.D. dependent var419282.0S.E. of regression434780.1Akaike info criterion28.92298Sum squared resid5.10E+12Schwarz criterion29.10801Log likelihood-444.3062Hannan-Quinn criter.28.98330F-statistic0.299790Durbin-Watson stat1.835854Prob(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=0.9993220.05（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-693.1946 t=（10.70922）（-1.841272）R2=0.798173 F=114.6875 DW=1.562975用权数w3=1/sqr（x）,用回归分析得：Dependent Variable: YMethod: Least SquaresDate: 12/09/14 Time: 21:35Sample: 1 31Included observations: 31Weighting series: W3VariableCoefficientStd. Errort-StatisticProb.X1.3301300.09834513.525070.0000C-47.40242313.1154-0.1513900.8807Weighted StatisticsR-squared0.863161Mean dependent var4164.118Adjusted R-squared0.858442S.D. dependent var991.2079S.E. of regression586.9555Akaike info criterion15.65012Sum squared resid9990985.Schwarz criterion15.74263Log likelihood-240.5768Hannan-Quinn criter.15.68027F-statistic182.9276Durbin-Watson stat1.237664Prob(F-statistic)0.000000Unweighted StatisticsR-squared0.890999Mean dependent var4443.526Adjusted R-squared0.887240S.D. dependent var1972.072S.E. of regression662.2171Sum squared resid12717412Durbin-Watson stat1.314859对此模型进行White检验得：Heteroskedasticity Test: WhiteF-statistic0.423886Prob. F(2,28)0.6586Obs*R-squared0.911022Prob. Chi-Square(2)0.6341Scaled explained SS2.768332Prob. Chi-Square(2)0.2505Test Equation:Dependent Variabl