TSLS法估计宏观经济模型一例

1、第一题：表 10-610-6 给出了 1978-20001978-2000 年我国宏观经济统计数据资料，试根据这些数据判断模型的识别性，再用 2SLS2SLS 法估计下列宏观经济模型：Ct01 丫丫uitIt02Yt1U2t丫丫CtItGtXt表 10-610-6 我国 1978200019782000 年的宏观经济数据年份YtCtItGtXt19783605.62239.11377.9480.0-19.819794074.02619.41474.2614.0-31.219804551.32976.11590.0659.0-27.619814901.43309.11581.0705.0-0.1

2、19825489.23637.91760.2770.056.319836076.34020.52005.0838.016.519847164.44694.52468.61020.0-40.019858792.15773.03386.01184.0-448.9198610132.86542.03846.01367.0-416.2198711784.77451.24322.01490.0-144.2198814704.09360.15495.01727.0-288.4198916466.010556.56095.02033.0-243.9199018319.511365.26444.02252.0

3、411.5199121280.413145.97517.02830.0428.4199225863.715952.19636.03492.3233.0199334500.720182.114998.04499.7-701.4199446690.726796.019260.65986.2461.7199558510.533635.023877.06690.51403.7199668330.440003.926867.27851.61019.0199774894.243579.428457.68724.83354.2199879003.346405.929545.99484.83605.51999

4、82673.149722.730701.610388.32423.3200089340.954600.932499.811705.31995.6一、进行模型识别1 1）阶识别随机方程模型中的变量数方程中的变量数阶条件k-ki=mi-1结论mkmiki消费332031过度识别投资332121过度识别阶条件识别结果为消费方程、投资方程都过度识别。2)2)秩识别将模型方程组改成以下形式0CtItiY0Gt2Y10Xtu2t0Ct01ttY0Gt0%0Xt%0CtIt 丫丫G0Yixt0写出联立方程的结构参数矩阵:方程中内生变量 m=3m=3分析消费方程识别问题,分析投资方程识别问题,Rank(A1)

5、=2,Rank(A1)=2,说明消费方程可识别。Rank(A2)=2,Rank(A2)=2,说明投资方程可识别。结合阶条件识别结果，可以判断宏观经济联立方程组模型是过度识别的,需要用二阶段最小乘法进行估计。二、二阶段最小二乘法在 Eviews6Eviews6 新建 WorkfileWorkfile 之后，导入数据。对消费方程进行 TSLSTSLS 古计得：Equation;EQOEquation;EQO orfrflie:EJNTITLED:(Jntorfrflie:EJNTITLED:(JntEjfx蛇匚 RobjEtHPrint 泗&画回收词比优 im/恒正 oret 日式回 at

6、ERReskfeInstrumentlist.YT(-1)GTCVariableCoefficientSM.Errort-StallsticProb.YT0.5579B10.004S35127133B0.0000C386.7657193.40141.959491口.0641R-squared0998765Meandependentvar18924.06AdjustedR-squared0.393703S.D.defjendentvar17525.29S.E.ofregression631.1573Sumsquaredresid796T151F-statistic101C2.95Durbin-W

7、atsonstat0.5U314Prob(F-statistic)c.oaooooSecord-St3qe-SSF11191507基于以上结果，写出消费方程 TSLSTSLS 古计式为：Ct388.76570.587961YtDependentvariable:CTMethod:Two-StageSquaresDate:12/00/11Time:15:33Sample(adjusted):19792000Includedobsen/ations.31afteradjustments对投资方程进行 TSLSTSLS 古计得:不EQO2EQO2 ! ! orkflie:ONTITLED:orkfl

8、ie:ONTITLED:;:Onti.;:Onti.一n回冈Ob 怡山Print时占meFreese5tat|DependentVariable:ITMethodTwo-StageLeastSquaresqDate:12/08/11Time15:45Sample(adjusted)19792000Includedobservations:22afteradjustmentsInstrutrionUitt:IT/TCVahableCoefficientStd.ErrortStatisticProb.YT06765560.03536&1S130250.0000*O.32J1440.036511-8.3&0878U,0000C-IOe.3413143.9114-2.074500.0105R-squared0.999690Meandependantvar11992.17AdiustedR-sauared0.999552S.D.dependentvsr1140G.DES.E.ofregresslan433,3691Sumsquaredresid25G605.F-statislic7249.163Ddrbln-Watsonstal1552776Prab(F-stat3siic)0,000000Second-StageSSR3