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計(jì)量經(jīng)濟(jì)學(xué)第三版課后習(xí)題答案解析(參考版)

2025-06-21 19:13本頁面
  

【正文】 DurbinWatson statProb(Fstatistic)得∑e2i2=3)根據(jù)GoldfeldQuanadt檢驗(yàn),F(xiàn)統(tǒng)計(jì)量為:F=∑e2i2 /∑e1i2 =在α=,分子分母的自由度均為11,(11,11)=,因?yàn)镕= (11,11)=,所以拒絕原假設(shè),此檢驗(yàn)表明模型存在異方差。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredXCRsquaredDurbinWatson statProb(Fstatistic)得∑e1i2=2)當(dāng)定義區(qū)間為113時(shí),由軟件分析得:Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 19:34Sample: 22 34Included observations: 13VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredXCRsquaredDurbinWatson statProb(Fstatistic)得回歸模型為:Y= X+b)檢驗(yàn)是否存在異方差:①用GoldfeldQuanadt檢驗(yàn)如下:1)當(dāng)定義區(qū)間為113時(shí),由軟件分析得:Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 19:27Sample: 1 13Included observations: 13VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredXCRsquared估計(jì)結(jié)果為: Y= t=()()R2= F= DW=經(jīng)過檢驗(yàn)發(fā)現(xiàn),用權(quán)數(shù)w1的效果最好,所以綜上可知,即修改后的結(jié)果為:Y= t=()()R2= F= DW=(1)a)用Eviews模型分析得:Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 19:16Sample: 1978 2011Included observations: 34VariableCoefficientStd. ErrortStatisticProb.DurbinWatson statProb(Fstatistic)從上可知,nR2=,比較計(jì)算的統(tǒng)計(jì)量的臨界值,因?yàn)閚R2=(2)=,所以接受原假設(shè),該模型消除了異方差。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid+12. dependent var. of regressionMean dependent varAdjusted RsquaredCWGT^22240181.X^2*WGT^2X*WGT^2RsquaredProb. ChiSquare(3)Test Equation:Dependent Variable: WGT_RESID^2Method: Least SquaresDate: 12/24/15 Time: 16:45Sample: 1 31Included observations: 31VariableCoefficientStd. ErrortStatisticProb.Prob. ChiSquare(3)Scaled explained SSProb. F(3,27)Obs*RsquaredSum squared resid19268334DurbinWatson stat對此模型進(jìn)行White檢驗(yàn)得:Heteroskedasticity Test: WhiteFstatistic. dependent var. of regressionMean dependent varAdjusted RsquaredDurbinWatson statProb(Fstatistic)Unweighted StatisticsRsquaredHannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid6320554.. dependent var. of regressionMean dependent varAdjusted RsquaredXCWeighted StatisticsRsquared估計(jì)結(jié)果為: Y= t=()()R2= F= DW=②用權(quán)數(shù)w2=1/x2,用回歸分析得:Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 16:40Sample: 1 31Included observations: 31Weighting series: W2VariableCoefficientStd. ErrortStatisticProb.DurbinWatson statProb(Fstatistic)得∑e2i2=7909670.3)根據(jù)GoldfeldQuanadt檢驗(yàn),F(xiàn)統(tǒng)計(jì)量為:F=∑e2i2 /∑e1i2 =7909670./ 1772245=在α=,分子分母的自由度均為10,(10,10)=,因?yàn)镕= (10,10)=,所以拒絕原假設(shè),此檢驗(yàn)表明模型存在異方差。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid7909670.. dependent var. of regressionMean dependent varAdjusted RsquaredX1CRsquaredDurbinWatson statProb(Fstatistic)得∑e1i2=1772245.2)定義區(qū)間為2031時(shí),由軟件分析得:Dependent Variable: Y1Method: Least SquaresDate: 12/24/15 Time: 16:16Sample: 20 31Included observations: 12VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid1772245.. dependent var. of regressionMean dependent varAdjusted RsquaredX1CRsquared②GoldfeldQuanadt檢驗(yàn)1)定義區(qū)間為112時(shí),由軟件分析得:Dependent Variable: Y1Method: Least SquaresDate: 12/24/15 Time: 16:05Sample: 1 12Included observations: 12VariableCoefficientStd. ErrortStatisticProb.回歸方程是顯著的。DurbinWatson statProb(Fstatistic)得∑e2i2=3)根據(jù)GoldfeldQuanadt檢驗(yàn),F(xiàn)統(tǒng)計(jì)量為:F=∑e2i2 /∑e1i2 =在α=,分子分母的自由度均為4,(4,4)=,因?yàn)镕= (4,4)=,所以接受原假設(shè),此檢驗(yàn)表明模型不存在異方差。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredT
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