联立方程模型估计实验2.doc

联立方程模型估计实验下列为一完备的联立计量经济学模型：Yt=0+1Mt+1Ct+2It+1tMt=0+1 Yt +3Pt+2t其中Mt为货币供给量，Yt为国内生产总值，Ct 和It分别为居民消费与投资。以表中的中国实际数据为资料，估计上述联立方程模型，要求恰好识别的方程按工具变量法与二阶段最小二乘法估计。年份M2/亿元GDP/亿元P/1978年为100CONS/亿元I/亿元M2GDPPCONSI15293.419347.8165.29450.9451719349.922577.4170.810730.65594.525402.227565.2181.713000.18080.134879.836938.1208.516412.113072.346923.550217.4258.721844.217042.160750.563216.9302.928369.720019.376094.974163.6328.133955.922913.590955.381658.5337.336921.524941.1104498.586531.6334.639229.328406.2119897.991125329.941920.429854.7134610.398749331.245854.632917.7158301.9108972.4333.549213.237213.5185007120350.3330.952571.343499.9221222.8136398.8334.856834.455566.6254107160280.4347.963833.570477.4298755.7188692.1354.271217.588773.6345603.6221651.3359.580476.9109998.2403442.2263242.5376.793317.2137323.9第一个方程恰好识别，首先用工具变量法估计。用模型中的价格指数P作为M2的工具。在Eviews软件中，选择“QuickEstimate Equation”,+在新出现的对话框中的“Method”栏内选择“TSLS”再在新出现的对话框的“Equation Specification”栏内输入“GDP C M2 CONS I”,在下面的工具栏（Instrument list）内输入“C P CONS I”,点击OK。得：Dependent Variable: GDPMethod: Two-Stage Least SquaresDate: 04/26/10 Time: 12:16Sample: 1990 2000Included observations: 11Instrument list: C P CONS IVariableCoefficientStd. Errort-StatisticProb.C-1303.738725.1632-1.7978550.1152M2-0.1504550.028804-5.2234890.0012CONS2.0629680.15358613.431990.0000I0.6868530.1661694.1334520.0044R-squared0.999599Mean dependent var54470.82Adjusted R-squared0.999427S.D. dependent var26284.98S.E. of regression628.9616Sum squared resid2769149.F-statistic5820.691Durbin-Watson stat2.279647Prob(F-statistic)0.000000Dependent Variable: GDPMethod: Two-Stage Least SquaresDate: 04/26/13 Time: 21:30Sample: 1990 2000Included observations: 11Instrument list: C P CONS IVariableCoefficientStd. Errort-StatisticProb. C-1303.738725.1632-1.7978550.1152M2-0.1504550.028804-5.2234890.0012CONS2.0629680.15358613.431990.0000I0.6868530.1661694.1334520.0044R-squared0.999599 Mean dependent var54470.82Adjusted R-squared0.999427 S.D. dependent var26284.98S.E. of regression628.9616 Sum squared resid2769149.F-statistic5820.691 Durbin-Watson stat2.279647Prob(F-statistic)0.000000再用两阶段最小二乘法估计。第一阶段，用OLS法估计M的简化方程。Dependent Variable: M2Method: Least SquaresDate: 04/26/10 Time: 12:18Sample: 1990 2000Included observations: 11VariableCoefficientStd. Errort-StatisticProb.C26863.544262.7606.3019130.0004P-359.111031.92965-11.246940.0000CONS4.7256470.44636310.587010.0000I0.7783800.5083121.5313020.1696R-squared0.998499Mean dependent var66241.47Adjusted R-squared0.997855S.D. dependent var41921.39S.E. of regression1941.527Akaike info criterion18.25562Sum squared resid26386686Schwarz criterion18.40031Log likelihood-96.40594F-statistic1551.711Durbin-Watson stat2.043032Prob(F-statistic)0.000000Dependent Variable: M2Method: Least SquaresDate: 04/26/13 Time: 21:33Sample: 1990 2000Included observations: 11VariableCoefficientStd. Errort-StatisticProb. C26863.544262.7606.3019130.0004P-359.111031.92965-11.246940.0000CONS4.7256470.44636310.587010.0000I0.7783800.5083121.5313020.1696R-squared0.998499 Mean dependent var66241.47Adjusted R-squared0.997855 S.D. dependent var41921.39S.E. of regression1941.527 Akaike info criterion18.25562Sum squared resid26386686 Schwarz criterion18.40031Log likelihood-96.40594 F-statistic1551.711Durbin-Watson stat2.043032 Prob(F-statistic)0.000000然后点击工具栏的Forecast按钮，在出现的对话框中，默认软件给出的估计的M2序列名M2F，点击OK。之后用M2F作为解释变量M2的替待变量，代入GDP方程中用OLS法估计GDP方程，结果如下Dependent Variable: GDPMethod: Least SquaresDate: 04/26/10 Time: 12:22Sample: 1990 2000Included observations: 11VariableCoefficientStd. Errort-StatisticProb.M2F-0.1504550.018439-8.1596810.0001C-1303.738464.2193-2.8084530.0262CONS2.0629680.09831920.982290.0000I0.6868530.1063756.4569200.0003R-squared0.999836Mean dependent var54470.82Adjusted R-squared0.999765S.D. dependent var26284.98S.E. of regression402.6351Akaike info criterion15.10923Sum squared resid1134805.Schwarz criterion15.25392Log likelihood-79.10074F-statistic14203.64Durbin-Watson stat2.325917Prob(F-statistic)0.000000Dependent Variable: GDPMethod: Least SquaresDate: 04/26/13 Time: 21:38Sample: 1990 2000Included observations: 11VariableCoefficientStd. Errort-StatisticProb. C-1303.738464.2193-2.8084530.0262M2F-0.1504550.018439-8.1596810.0001CONS2.0629680.09831920.982290.0000I0.6868530.1063756.4569200.0003R-squared0.999836 Mean dependent var54470.82Adjusted R-squared0.999765 S.D. dependent var26284.98S.E. of regression402.6351 Akaike info