宏观经济模型多种估计方法的EVIEWS实现1

1、08统计 学号：0807294 吴扬一、 问题综述建立中国宏观经济模型。宏观经济模型，是指以整个国民经济系统为研究对象，从总量水平和经济结构方面来研究国民经济各变量之间的相互作用。它可用来评价宏观经济政策、分析宏观经济结构和国民经济的发展趋势。宏观经济模型的表达可以用单一方程进行表达，也可以用联立方程组表达。本作业建立如下宏观经济模型，完备的结构式模型为其中，包含3个内生变量，即国内生产总值Y，居民消费总额C和投资总额I；3个先决变量，即政府消费G，前期居民消费总额Ct-1和常数项。可以判断，消费方程是恰好识别的方程，投资方程是过度识别的，模型可以识别。数据来自题目提供。导入EVIEWS二、

2、各种方法的EVIEWS实现1. 狭义的工具变量法估计消费方程选取消费方程中未包含的先决变量G作为内生解释变量Y的工具变量；在工作文件主窗口点击quick/estimate equation，选择估计方法TSLS，在equation specification对话框输入消费方程，在instrument list对话框输入工具变量.点击确定，得到：Dependent Variable: C01Method: Two-Stage Least SquaresDate: 06/02/11 Time: 14:08Sample (adjusted): 1979 2009Included observatio

3、ns: 31 after adjustmentsInstrument list: C G C01(-1)VariableCoefficientStd. Errort-StatisticProb.  C1290.053402.73533.2032290.0034Y0.1071330.0231504.6277390.0001C01(-1)0.7857560.07185910.934710.0000R-squared0.998513    Mean dependent var34025.26Adjusted R-squared0.99840

4、7    S.D. dependent var34218.49S.E. of regression1365.679    Sum squared resid52222209F-statistic9402.761    Durbin-Watson stat0.743434Prob(F-statistic)0.000000    Second-Stage SSR53379247得到结构参数的工具变量法估计量：2. 间接最小二乘法估计消费方程

5、消费方程中包含的内生变量的简化方程为参数关系体系为用普通最小二乘法估计第一个简化式：Dependent Variable: C01Method: Least SquaresDate: 06/02/11 Time: 14:46Sample (adjusted): 1979 2009Included observations: 31 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.  C1086.594386.55342.8109810.0089C01(-1)0.9545380.03625626.327

6、720.0000G0.2655810.0580214.5773100.0001R-squared0.998480    Mean dependent var34025.26Adjusted R-squared0.998372    S.D. dependent var34218.49S.E. of regression1380.725    Akaike info criterion17.39037Sum squared resid53379247  &#

7、160; Schwarz criterion17.52914Log likelihood-266.5507    Hannan-Quinn criter.17.43561F-statistic9198.948    Durbin-Watson stat0.743999Prob(F-statistic)0.000000用普通最小二乘法估计第二个简化式：Dependent Variable: YMethod: Least SquaresDate: 06/02/11 Time: 14:47Sample (adj

8、usted): 1979 2009Included observations: 31 after adjustmentsVariableCoefficientStd. Errort-StatisticProb.  C-1899.1342081.958-0.9121860.3695C01(-1)1.5754550.1952738.0679500.0000G2.4789920.3124997.9327940.0000R-squared0.994318    Mean dependent var84244.67Adjusted R-squa

9、red0.993912    S.D. dependent var95306.59S.E. of regression7436.521    Akaike info criterion20.75796Sum squared resid1.55E+09    Schwarz criterion20.89673Log likelihood-318.7484    Hannan-Quinn criter.20.80320F-statistic

10、2449.755    Durbin-Watson stat0.686339Prob(F-statistic)0.000000得到简化式参数估计量为：由参数体系计算得到结构参数间接最小二乘估计值为3. 二阶段最小二乘法点击objects/new object，选择systemSystem: UNTITLEDEstimation Method: Two-Stage Least SquaresDate: 06/02/11 Time: 15:09Sample: 1979 2009Included observations: 31Total system (ba

11、lanced) observations 62CoefficientStd. Errort-StatisticProb.  C(1)1290.053402.73533.2032290.0022C(2)0.1071330.0231504.6277390.0000C(3)0.7857560.07185910.934710.0000C(4)-2538.266948.1448-2.6770870.0097C(5)0.4413900.00753458.585760.0000Determinant residual covariance1.63E+13Equation: C01=C(1

12、)+C(2)*Y+C(3)*C01(-1) Instruments: G C01(-1) CObservations: 31R-squared0.998513    Mean dependent var34025.26Adjusted R-squared0.998407    S.D. dependent var34218.49S.E. of regression1365.679    Sum squared resid52222209Durbin-Watson s

13、tat0.743434Equation: I=C(4)+C(5)*Y Instruments: G C01(-1) CObservations: 31R-squared0.991774    Mean dependent var34646.51Adjusted R-squared0.991491    S.D. dependent var42513.37S.E. of regression3921.722    Sum squared resid4.46E+08Du

14、rbin-Watson stat0.538847消费方程的参数估计量为投资方程的参数估计量为4. 三阶段最小二乘法System: UNTITLEDEstimation Method: Three-Stage Least SquaresDate: 06/02/11 Time: 15:20Sample: 1979 2009Included observations: 31Total system (balanced) observations 62Linear estimation after one-step weighting matrixCoefficientStd. Errort-Stat

15、isticProb.  C(1)1384.346361.67293.8276200.0003C(2)0.1165380.0181096.4351730.0000C(3)0.7563730.05603813.497460.0000C(4)-2538.266917.0495-2.7678610.0076C(5)0.4413900.00728760.572280.0000Determinant residual covariance1.55E+13Equation: C01=C(1)+C(2)*Y+C(3)*C01(-1) Instruments: G C01(-1)

16、CObservations: 31R-squared0.998459    Mean dependent var34025.26Adjusted R-squared0.998349    S.D. dependent var34218.49S.E. of regression1390.396    Sum squared resid54129611Durbin-Watson stat0.672688Equation: I=C(4)+C(5)*Y Instrument

17、s: G C01(-1) CObservations: 31R-squared0.991774    Mean dependent var34646.51Adjusted R-squared0.991491    S.D. dependent var42513.37S.E. of regression3921.722    Sum squared resid4.46E+08Durbin-Watson stat0.538847消费方程的参数估计量为投资方程的参数估计量为5. G

18、MM（广义矩估计）System: UNTITLEDEstimation Method: Generalized Method of MomentsDate: 06/02/11 Time: 15:27Sample: 1979 2009Included observations: 31Total system (balanced) observations 62Identity matrix estimation weights - 2SLS coefs with GMM standard errorsKernel: Bartlett, Bandwidth: Fixed (3), No prewh

19、iteningCoefficientStd. Errort-StatisticProb.  C(1)1290.053616.41172.0928440.0408C(2)0.1071330.0277223.8645370.0003C(3)0.7857560.0939578.3629010.0000C(4)-2538.2661067.430-2.3779230.0208C(5)0.4413900.01342532.878450.0000Determinant residual covariance1.63E+13J-statistic1.21E+13Equation: C01=

20、C(1)+C(2)*Y+C(3)*C01(-1) Instruments: G C01(-1) CObservations: 31R-squared0.998513    Mean dependent var34025.26Adjusted R-squared0.998407    S.D. dependent var34218.49S.E. of regression1365.679    Sum squared resid52222209Durbin-Watson stat0.743434Equation: I=C(4)+C(5)*Y&#