我国货币供给函数的协整与误差校正模型

Co-Integration and Error-Correction Model for China's Money Supply Function

传统的线性回归建模常假定时间序列是平稳的,以保证普通最小二乘法得到的估计量一致.而多数经济时间序列却是非平稳的,对其做线性回归可能产生所谓的“伪回归”.在协整理论基础上,借助统计和整理的经济数据,运用计量经济学的Eviews统计软件对我国货币供给进行实证分析,建立了误差校正模型.对误差校正模型残差的自相关性、异方差性进行检验,结果表明该模型在我国货币供给中是有效的,克服了“伪回归”现象,且具有很好的经济解释意义.

Conventionally, when setting up a linear regression model the time series are usually presumed to be steady to ensure that the variables estimated by common least square method are consistent and in asymptotically normal distribution. However, most economic time series are unsteady and they are easily resulting in so-called ＂false regression＂ when linearly regressed. So, an error-correction model is set up on the basis of the co-integration theory and by virtue of statistics, and handled data, especially the empirical analysis of money supply, which is done by the econometric Eviews statistic software. The autocorrelation and heteroskedasticity of residual of the error-correction model were tested, and the results showed that the model can get rid of the ＂false regression＂ effectively and explain well the economic phenomena.