計(jì)量經(jīng)濟(jì)學(xué)第三版課后習(xí)題答案解析-文庫(kù)吧資料
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【正文】 XCRsquaredDurbinWatson statProb(Fstatistic)得∑e1i2=2）定義區(qū)間為1218時(shí)，由軟件分析得：Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 14:55Sample: 12 18Included observations: 7VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredTXCRsquared（1）①用圖形法檢驗(yàn)繪制e2的散點(diǎn)圖，用Eviews分析如下：由上圖可知，模型可能存在異方差，② GoldfeldQuanadt檢驗(yàn)1）定義區(qū)間為17時(shí)，由軟件分析得：Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 14:52Sample: 1 7Included observations: 7VariableCoefficientStd. ErrortStatisticProb.并且通過(guò)以上分析，兩兩被解釋變量之間相關(guān)性都很高。由上表可知，CZZC與GDP，CZZC與SSZE，GDP與SSZE之間的相關(guān)系數(shù)都非常高，說(shuō)明確實(shí)存在多重共線性。SSZEGDPCZZC（2）得到相關(guān)系數(shù)矩陣如下：CZSRCZZCGDPSSZECZSR但是t檢驗(yàn)結(jié)果表明，國(guó)內(nèi)生產(chǎn)總值對(duì)財(cái)政收入的影響顯著，但回歸系數(shù)的符號(hào)為負(fù)，與實(shí)際不符合。DurbinWatson statProb(Fstatistic)從回歸結(jié)果可見(jiàn)，模型擬合的很好。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid2866884.. dependent var. of regressionMean dependent varAdjusted RsquaredCZZCGDPSSZECRsquared（1）按照設(shè)計(jì)的理論模型，由Eviews分析得：Dependent Variable: CZSRMethod: Least SquaresDate: 12/24/15 Time: 11:23Sample: 1985 2011Included observations: 27VariableCoefficientStd. ErrortStatisticProb.DurbinWatson statProb(Fstatistic)①得到的回歸方程分別為1）LNY= 2）LNY= 3）LNGDPt= ②對(duì)多重共線性的認(rèn)識(shí)：?jiǎn)畏匠虜M合效果都很好，回歸系數(shù)顯著，判定系數(shù)較高，GDP和CPI對(duì)進(jìn)口的顯著的單一影響，在這兩個(gè)變量同時(shí)引入模型時(shí)影響方向發(fā)生了改變，這只有通過(guò)相關(guān)系數(shù)的分析才能發(fā)現(xiàn)。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredLNCPICRsquaredDurbinWatson statProb(Fstatistic)c)Dependent Variable: LNGDPMethod: Least SquaresDate: 12/24/15 Time: 11:07Sample: 1985 2011Included observations: 27VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredLNCPICRsquaredDurbinWatson statProb(Fstatistic)b)Dependent Variable: LNYMethod: Least SquaresDate: 12/24/15 Time: 10:55Sample: 1985 2011Included observations: 27VariableCoefficientStd. ErrortStatisticProb.HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredLNGDPCRsquared（3）由Eviews得：a）Dependent Variable: LNYMethod: Least SquaresDate: 12/24/15 Time: 10:41Sample: 1985 2011Included observations: 27VariableCoefficientStd. ErrortStatisticProb.LNCPI②得到相關(guān)系數(shù)矩陣如下：LNYLNGDPLNCPILNYDurbinWatson statProb(Fstatistic)得到的模型方程為：LNY= （2）① ，可決系數(shù)很高，明顯顯著。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredLNGDPLNCPICRsquared（1）根據(jù)Eviews分析得到數(shù)據(jù)如下：Dependent Variable: LNYMethod: Least SquaresDate: 12/24/15 Time: 10:39Sample: 1985 2011Included observations: 27VariableCoefficientStd. ErrortStatisticProb.2） F檢驗(yàn)，F(xiàn)=F（）=3,89，回歸方程顯著3） T檢驗(yàn)，X5 ，大于t（12）=，所以系數(shù)是顯著的，即人均GDP對(duì)年底存款余額有顯著影響。2） F檢驗(yàn)，F(xiàn)=F（）=3,89，回歸方程顯著3） T檢驗(yàn)，X1，X2,X3,X4,X5，X6 系數(shù)對(duì)應(yīng)的t值分別為：，均小于t（12）=，所以所得系數(shù)都是不顯著的。DurbinWatson statProb(Fstatistic)①與預(yù)期不相符。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum squared resid. dependent var. of regressionMean dependent varAdjusted RsquaredX2X3X4X5X6CRsquared（1）預(yù)期的符號(hào)是X1，X2,X3,X4,X5的符號(hào)為正，X6的符號(hào)為負(fù)（2）根據(jù)Eviews分析得到數(shù)據(jù)如下：Dependent Variable: YMethod: Least SquaresDate: 12/24/15 Time: 10:13Sample: 1994 2011Included observations: 18VariableCoefficientStd. ErrortStatisticProb.DurbinWatson statProb(Fstatistic)模型為：E1 = + 參數(shù)：，（3）由上可知，β2與α2的系數(shù)是一樣的。HannanQuinn criter.FstatisticSchwarz criterionLog likelihoodAkaike info criterionSum sq
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