計(jì)量經(jīng)濟(jì)學(xué)第三版[龐浩]版課后答案解析全(編輯修改稿)
2025-07-15 19:46 本頁(yè)面
【文章內(nèi)容簡(jiǎn)介】 ethod: Least SquaresDate: 12/10/14 Time: 16:36Sample: 20 31Included observations: 12VariableCoefficientStd. ErrortStatisticProb.X1CRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared resid7909670.Schwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson 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。（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：Dependent Variable: YMethod: Least SquaresDate: 12/09/14 Time: 11:13Sample: 1 31Included observations: 31Weighting series: W1VariableCoefficientStd. ErrortStatisticProb.XCWeighted StatisticsRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared resid8352726.Schwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)Unweighted StatisticsRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionSum squared resid14484289DurbinWatson stat對(duì)此模型進(jìn)行White檢驗(yàn)得：Heteroskedasticity Test: WhiteFstatisticProb. F(2,28)Obs*RsquaredProb. ChiSquare(2)Scaled explained SSProb. ChiSquare(2)Test Equation:Dependent Variable: WGT_RESID^2Method: Least SquaresDate: 12/10/14 Time: 21:13Sample: 1 31Included observations: 31Collinear test regressors dropped from specificationVariableCoefficientStd. ErrortStatisticProb.C1045682.WGT^21173622.X*WGT^2RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared resid+13Schwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson 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。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: 12/09/14 Time: 21:08Sample: 1 31Included observations: 31Weighting series: W2VariableCoefficientStd. ErrortStatisticProb.XCWeighted StatisticsRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared resid6320554.Schwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson statProb(Fstatistic)Unweighted StatisticsRsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionSum squared resid19268334DurbinWatson stat對(duì)此模型進(jìn)行White檢驗(yàn)得：Heteroskedasticity Test: WhiteFstatisticProb. F(3,27)Obs*RsquaredProb. ChiSquare(3)Scaled explained SSProb. ChiSquare(3)Test Equation:Dependent Variable: WGT_RESID^2Method: Least SquaresDate: 12/10/14 Time: 21:29Sample: 1 31Included observations: 31VariableCoefficientStd. ErrortStatisticProb.CWGT^22240181.X^2*WGT^2X*WGT^2RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared resid+12Schwarz criterionLog likelihoodHannanQuinn criter.FstatisticDurbinWatson 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
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