计量经济学 受约束回归检验、Eviews6

数学与统计学院实验报告院（系）：数学与统计学学院学号：姓名：实验课程：计量经济学指导教师:实验类型（验证性、演示性、综合性、设计性）：综合性实验时间：2017年3月22日一、实验课题受约束回归检验二、实验目的和意义1.表6.1.2是英国1946〜1963年居民储蓄与收入数据，单位是百万英镑。表6.1.2年份储蓄收入年份储蓄收入19460.368.819550.5915.519470.219.419560.9016.719480.0810.019570.9517.719490.2010.619580.8218.619500.1011.019591.0419.719510.1211.919601.5321.119520.4112.719611.9422.819530.5013.519621.7523.919540.4314.319631.9925.2（1）试建立储蓄关于收入的回归模型，并检验。（2）试分析（1）中建立的模型的参数稳定性。构造约束回归的F统计量进行检验；构造LR统计量进行检验；构造WD统计量进行检验；构造LM统计量进行检验；用Chow检验法或Chow预测检验法检验。Ps：要求写出详细操作步骤、计算结果及结果的分析。三、解题思路1、首先画散点图，观察两变量是否存在一定相关关系；再运用spss进行回归模型检验（输入x、y两变量一quick—estimateequation—ycx）2、通过散点图，明显发现该模型存在结构性变化，断点在1958年；即对数据进行分段参数检验。并用F、LR、WD、LM检验的理论知识进行验算。四、实验过程记录与结果1、试建立储蓄关于收入的回归模型，并检验。•散点图：两变量为正相关，所以存在一定关系。•有条件约束模型：

■Equation:USTITLEDTorkfile:UHTIILED:・・二亘冈View|Proc]Object)(PrintN^me[Freeze]Estimate[ForecastRe5id^Depend已门tVariable:YMethod:LeastSquaresDate:02/22/17Time:15:17Sample:19461963Includedobservations:18Variable匚口efficientStd.Errort-Etatisti匚Prob.匚-1.0820710.145151-7.4548200.0000X0,1178450,00877413,431640.0000R-squared0.918537Me^ndependentvar0.773333AdjustedR-squared0.913446S.D.dependentuar0.642806S.E.ofregression0.189114Akaikeinfocrit已「i□门-0.388493Sumsquaredresid0,572226Schwarzcriterion-0,259563Loglikelihood5.496436Hannan-Quinn匚riter.-0.374852F-statistic180.4090Durbin-Watsonstat0.9477S3Prob(F-5tati5tic)0.000000所以回归模型为：Y=-1・082071+0.117845*X2、试分析（1）中建立的模型的参数稳定性。无条件约束模型：（以19658年为断点）1)1946-1957年■Equation:EQ02Torkfile:UKTITLED:ilTnti...□回区Mi已网,(Proc][Objecl:][Prin「N曰me[Freeze]〔Estimate]|Fcire匚a$日|Flza乜]|氏esids]DependentVariable;丫Method:LeastSquaresDate:03/22/17Time:15:21Sample:19461957Includedobservations:12Variable匚oeffi匚iontStd.Errort-GtatisticProb.-0.710738□.201715-3.5234790.00550,0879610,0155425.6593850.0002R-squared0.762067Meandependentvar0.404167AdjustedR-squared0.738274S.D.dependentvar0.293551S.E.ofregression0,150178Akaikeinfocriterion-0,802977Gumsquaredresid0.225535Schwarzcriterion-0.722160Loglikelihood6.817864Haririan-Quinricriter.-0.832899F-statistic32.02864Durbin-Watsonstat0.954844Proti(F-statistic)□,0002102)1958-1963年

1■Equation:UUTITLEDTorlfile:TJITITLE])::..・口回区]Hl|[view]|PracJobject][Print][Name][Freeze][Estimate][Farecast|[stats][Resids]DependentVariable:丫Method;LeastSquaresDate:03/22/17Time:15:21Sample:19581963I门匚ludedobservations:6VariableCoefflcientStd,Errort-StatisticProb.匚-2.4095000.728676-3.306681□.□297X0.1791850.0331145.4111660.0057R-squared0.879810Meandependentvar1.511667AdjustedR-squared0.849763S.D.dependentvar0.483794S.E.ofregression0.1S752LAkaikeinfocriterion-0.24S654Sumsquaredresid0.14065&5匚hwarzcriterion-0.318067Loglikelihood2,745961Hannan-Quinncriter,-0,526522F-statisti匚29.28071Durbin-Watsonstat1.554983Prob(F-statistic)0.0056503、Chow检验：■EqTiatioiL：EQ01Torkfile:UHTITLED==Unti.・・匚|回区恂|[prcii:||c±ij&zl:]|prinl:||NwnnE|prBEEE]任乩油日怕][尸£|「&1：生1:|[51:日1：3|[艮阴出|ChowBreakpointTest:1958NullHypothesis:Nobreaksat5|ii已dfiedbreakpointsVaryingregressors;AllequationvariablesEquationSample:19461963F-statistic3.938521Prob.F(2,14)0.0440Loglikelihoodratio8.034848Prob.匚hi-Square(2)0.0180WaldStatistic7.577042Prob,匚hi-Square(2)0,01554、Chowforecasttest：\■Equation:EQO1Torifile:UKTITLED::Untitled\s®J[View][Proc|[object][Print][Name][Free2e][EstimatejForecast][stats][ftesids]ChowForecastTest:Forecastfrom1958to1Q62F-statistic2.561998Prob.FtG.lO)0.0907Loglikelihoodratio16,75909Prob.Chi-Square(6)0.0102TestEquation:DependentVariable;YMethod;LeastSquaresDate:02/22/17Time:15:38Sample:19461957Includedobservations:12VariableCoeffi匚imntStd.Errort-StatisticProb.匚-0.710738□.201715-3.5234790.0055X0,0879610,0155425,6593850.0002R-squared0.762067Meandeperidertvar0.404167AdjustedR-squared0.738274S.D.dependentv^r0.293551S.E.ofregression0.150178Akaikeinfocriterion-0.802977Sumsquaredresid0,225535Schwarzcriterion-0,722160Loglikelihood6.817864Hannan-Quinn匚riter.-0.832899F-statistic32.02864Durbin-Watsonstat0.954844Prob(F-stati5tic)0.000210五、结果的讨论和分析1、通过spss检验，发现该结构具有显著性的结构变化。(四1)RSS~0.57R2、以1958年为断点，分别得到两个模型。(四2)RSSu=RSS]+RSS2~0.23+0.14F检验：F=*~F(k+1,(n1+n2)-2(k+1),)=*~3.78〜F(2,14)=3.74F>F0.O5,即可拒绝原假设，所以该模型存在结构性变化LR检验LR=n*In(1+x)〜x2(1)x==18*ln[1+(0.57-0.37)/0.37]~7.78〜x2(1)=3.84通过数据，可以发现，LR检验为显著性检验，即模型具有结构性变化WD检验WD=n*x=9.73>x2(1)通过数据，可以发现，WD检验也为显著性检验，即模型具有结构性变