計(jì)量經(jīng)濟(jì)學(xué)論文(eviews分析)計(jì)量經(jīng)濟(jì)作業(yè)(編輯修改稿)
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【文章內(nèi)容簡(jiǎn)介】 tisticDurbinWatson statProb(Fstatistic)各項(xiàng)擬合效果都較好。雖然的t檢驗(yàn)不是很顯著，但考慮到其經(jīng)濟(jì)意義在模型中的重要地位，暫時(shí)保留。繼續(xù)引入。Dependent Variable: YMethod: Least SquaresDate: 12/23/10 Time: 02:41Sample: 1994 2003Included observations: 10VariableCoefficientStd. ErrortStatisticProb.CX2X3X4X5X6RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodFstatisticDurbinWatson statProb(Fstatistic)根據(jù)以上回歸結(jié)果可得，的引入使得模型中、的t檢驗(yàn)均不顯著，說(shuō)明、高度相關(guān)，模型產(chǎn)生了多重共線性，因此將去掉。再將代入檢驗(yàn)。Dependent Variable: YMethod: Least SquaresDate: 12/23/10 Time: 02:42Sample: 1994 2003Included observations: 10VariableCoefficientStd. ErrortStatisticProb.CX2X3X4X5X7RsquaredMean dependent varAdjusted Rsquared. dependent var. of regressionAkaike info criterionSum squared residSchwarz criterionLog likelihoodFstatisticDurbinWatson statProb(Fstatistic)的系數(shù)為負(fù)，與經(jīng)濟(jì)意義相悖，因此也去掉。由此確定帶入模型的解釋變量為、。異方差性的檢驗(yàn)：再對(duì)模型的異方差性進(jìn)行檢驗(yàn)：鑒于我們的樣本資料是時(shí)間序列數(shù)據(jù)，選用ARCH檢驗(yàn)。ARCH Test:FstatisticProbabilityObs*RsquaredProbabilityTest Equation:Dependent Variable: RESID^2Method: Least SquaresDate: 12/23/10 Time: 02:43Sample (adjusted): 1995 2003Included observations: 9 after adjustments
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