宏觀經(jīng)濟模型多種估計方法的EVIEWS實現(xiàn)

1、08統(tǒng)計 學號：0807294 吳揚一、 問題綜述建立中國宏觀經(jīng)濟模型。宏觀經(jīng)濟模型，是指以整個國民經(jīng)濟系統(tǒng)為研究對象，從總量水平和經(jīng)濟結構方面來研究國民經(jīng)濟各變量之間的相互作用。它可用來評價宏觀經(jīng)濟政策、分析宏觀經(jīng)濟結構和國民經(jīng)濟的發(fā)展趨勢。宏觀經(jīng)濟模型的表達可以用單一方程進行表達，也可以用聯(lián)立方程組表達。本作業(yè)建立如下宏觀經(jīng)濟模型，完備的結構式模型為其中，包含3個內(nèi)生變量，即國內(nèi)生產(chǎn)總值Y，居民消費總額C和投資總額I；3個先決變量，即政府消費G，前期居民消費總額Ct-1和常數(shù)項?？梢耘袛?，消費方程是恰好識別的方程，投資方程是過度識別的，模型可以識別。數(shù)據(jù)來自題目提供。導入EVIEWS二、

2、各種方法的EVIEWS實現(xiàn)1. 狹義的工具變量法估計消費方程選取消費方程中未包含的先決變量G作為內(nèi)生解釋變量Y的工具變量；在工作文件主窗口點擊quick/estimate equation，選擇估計方法TSLS，在equation specification對話框輸入消費方程，在instrument list對話框輸入工具變量.點擊確定，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得到結構參數(shù)的工具變量法估計量：2. 間接最小二乘法估計消費方程

5、消費方程中包含的內(nèi)生變量的簡化方程為參數(shù)關系體系為用普通最小二乘法估計第一個簡化式：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計第二個簡化式：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得到簡化式參數(shù)估計量為：由參數(shù)體系計算得到結構參數(shù)間接最小二乘估計值為3. 二階段最小二乘法點擊objects/new object，選擇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消費方程的參數(shù)估計量為投資方程的參數(shù)估計量為4. 三階段最小二乘法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消費方程的參數(shù)估計量為投資方程的參數(shù)估計量為5. G

18、MM（廣義矩估計）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&#