计量经济学案例分析 课程报告 论文

1、中国经济增长影响因素实证分析一、研究对象经济增长问题既受各国政府和居民的关注,也是经济学理论研究的一个重要方面。在19782008年的31中,我国经济年均增长率高达9.6%,综合国力大大增强,居民收入水平与生活水平不断提高,居民的消费需求的数量和质量有了很大的提高。但是,我国目前仍然面临消费需求不足问题。因此,研究消费需求对经济增长的影响,并对我国消费需求对经济增长的影响程度进行实证分析，可以更好的理解消费对我国经济增长的作用。二、数据收集与模型的建立（一）数据收集表2.1 中国经济增长影响因素模型时间序列表年份国内生产总值（y）年末从业人员数（x1）全社会固定资产投资总额(x2)居民消费价格

2、指数（上年=100）(x3)19804545.642361910.9107.519814891.643725961102.519825323.4452951230.410219835962.7464361430.110219847208.1481971832.9102.719859016498732543.2109.3198610275.2512823120.6106.5198712058.6527833791.7107.3198815042.8543344753.8118.8198916992.3553294410.4118199018667.8647494517103.1199121781

3、.5654915594.5103.4199226923.5661528080.1106.4199335333.96680813072.3114.7199448197.96745517042.1124.1199560793.76806520019.3117.1199671176.66895022913.5108.31997789736982024941.1102.8199884402.37063728406.299.2199989677798.6200099214.67208532917.7100.42001109655.27302537213.5100.7200212

4、0332.77374043499.999.22003135822.87443255566.6101.22004159878.37520070477.4103.92005184937.47582588773.6101.82006216314.476400109998.2101.52007265810.376990137323.9104.82008314045.477480172828.4105.9200934090377995224598.899.3（二）模型设计 采用的模型如下：y= 1+2x1+3x2+4x3+ui 我们通过对该模型的回归分析，得出各个变量与我国经济增长的变动关系。三、模型估

5、计和检验（一）模型初始估计表3.1 模型初始估计结果Dependent Variable: YMethod: Least SquaresDate: 06/27/12 Time: 00:01Sample: 1980 2009Included observations: 30CoefficientStd. Errort-StatisticProb.C-16197.4741510.11-0.3902050.6996X11.6839720.2560656.5763360.0000X21.4204450.05488625.879790.0000X3-580.7369355.4395-1.6338560.

6、1143R-squared0.985665Mean dependent var85805.26Adjusted R-squared0.984011S.D. dependent var95097.07S.E. of regression12024.95Akaike info criterion21.75092Sum squared resid3.76E+09Schwarz criterion21.93775Log likelihood-322.2638Hannan-Quinn criter.21.81069F-statistic595.9008Durbin-Watson stat0.968679

7、Prob(F-statistic)0.000000由上表可以看出，R2=0.985665，接近于1。F=595.9008 说明拟合程度很好。进行t检验：t(28)=2.048对于参数c假设: H0: c(1)=0. 对立假设:H1: c(1)0对于参数x1假设: H0: c(2)=0. 对立假设:H1: c(2)0对于参数x2假设: H0: c(3)=0. 对立假设:H1: c(3)0对于c,t=0.390205t(n-2)=t(28)=2.048因此拒绝H0: c0,接受对立假设:H1: c=0对于x1,t=6.576336t(n-2)=t(28)=2.048 因此拒绝H0: x1=0,接受

8、对立假设: H1: x10对于x2,t=25.87979t(n-2)=t(28)=2.048 因此拒绝H0: x2=0,接受对立假设: H1: x20对于x3,t=1.633856t(n-2)=t(28)=2.048 因此拒绝H0: x20,接受对立假设: H1: x2=0由此可知，x3没有经过t检验。（二）多重共线性检验表3.2 相关系数矩阵X1X2X3X11.000000 0.665094-0.219318X2 0.665094 1.000000-0.291137X3-0.219318-0.291137 1.000000根据多重共线性检验，解释变量之间存在着线性相关。通过采用剔除变量法，多

9、重共线性的修正结果如下：剔除X3。.表3.3 修正多重共线性后的模型Dependent Variable: YMethod: Least SquaresDate: 06/28/12 Time: 23:17Sample: 1980 2009Included observations: 30CoefficientStd. Errort-StatisticProb.C-79282.7915704.05-5.0485550.0000X11.6990130.2636936.4431580.0000X21.4383250.05542225.952220.0000R-squared0.984193Mean

10、dependent var85805.26Adjusted R-squared0.983022S.D. dependent var95097.07S.E. of regression12391.14Akaike info criterion21.78199Sum squared resid4.15E+09Schwarz criterion21.92211Log likelihood-323.7299Hannan-Quinn criter.21.82682F-statistic840.5434Durbin-Watson stat0.689221Prob(F-statistic)0.000000由

11、表可得，x1和x2的t检验值都很显著。（3） 异方差检验ARCH检验：Heteroskedasticity Test: ARCHF-statistic5.690752Prob. F(1,27)0.0243Obs*R-squared5.048272Prob. Chi-Square(1)0.0247Test Equation:Dependent Variable: RESID2Method: Least SquaresDate: 06/28/12 Time: 23:48Sample (adjusted): 1981 2009Included observations: 29 after adjus

12、tmentsCoefficientStd. Errort-StatisticProb.C49385817560101980.8817290.3857RESID2(-1)0.8990980.3768972.3855300.0243R-squared0.174078Mean dependent var1.39E+08Adjusted R-squared0.143489S.D. dependent var2.41E+08S.E. of regression2.23E+08Akaike info criterion41.35408Sum squared resid1.35E+18Schwarz cri

13、terion41.44838Log likelihood-597.6342Hannan-Quinn criter.41.38362F-statistic5.690752Durbin-Watson stat1.336249Prob(F-statistic)0.024334从上表可以得到数据：(n-p)R2=5.048272,查表得2（p）=5.9915, (n-p)R2=5.0482722（p）=5.9915,则接受原假设，不存在异方差。（四）序列相关检验已知：DW=0.689221，查表得dL=1.270，dU=1.563。由此可知，存在相关性。修正如下：表3.5 修正序列相关后的模型Depe

14、ndent Variable: YMethod: Least SquaresDate: 06/07/11 Time: 17:00Sample(adjusted): 1981 2009Included observations: 29 after adjusting endpointsFailure to improve SSR after 18 iterationsVariableCoefficientStd. Errort-StatisticProb. C21524.051.27E+091.70E-051.0000X10.6126941.0519580.5824320.5655X20.999

15、5450.3097523.2269230.0035AR(1)1.0000190.1111908.9937700.0000R-squared0.992728Mean dependent var88607.31Adjusted R-squared0.991855S.D. dependent var95511.65S.E. of regression8619.708Akaike info criterion21.08893Sum squared resid1.86E+09Schwarz criterion21.27752Log likelihood-301.7895F-statistic1137.6

16、13Durbin-Watson stat0.989263Prob(F-statistic)0.000000Inverted AR Roots 1.00Estimated AR process is nonstationary四、结论分析和政策建议（一）主要结论1、固定资产投资是经济增长的重要原动力。经济发展取决于投入资金的数量和资金的利用效率。固定资产投资是经济增长的重要原动力，它对经济运行具有先导作用，并以其乘数效应拉动经济增长。2、劳动力对GDP有一定的促进作用但对经济增长的贡献率却微不足道。这是因为我国劳动力结构总量巨大、供给充足、流动性强, 对GDP 影响很大。但是劳动力的人力资本含量、高技术含量偏低,劳动力素质结构存在严重缺陷, 会直接影响了经济的增长。3、消费需求对经济的拉动作用消费需求是三大需求要素中所占份额最大、波动幅度最小的部分，是国民经济的重要支 柱和最主要的组成部分，同时也是最为明显地反映经济自发增长态势的宏观经济指标。（二）政策建议就业是民生之本，有效促进就业，保持经济增长良好势头成为我国当前乃至今后