摘要
本文以新菲利普斯曲线为理论基础,通过建立状态空间模型,利用卡尔曼(kalman)滤波估计中国1995年1月-2012年6月的核心通货膨胀率,并对估计结果进行检验。结果表明这种基于卡尔曼滤波的核心通货膨胀率估计充分考虑到变量之间的联系,比基于一般统计方法估计波动率更小。估计结果符合核心通货膨胀率的趋势平稳性和前瞻性要求,被剔除部分基本上不包含预测未来通货膨胀率的信息,因此对于货币当局的政策决策更有指导意义。
Based on the New-Keynesian Phillips curve,an estimate of core inflation is obtained using a Kalman Filter approach within StateSpace Framework.In empirical research,monthly data are adopted over the period of January 1995 to June 2012 in China.Comparing with various completing approach,empirical result obtained by Kalman Filter procedure has smaller volatility than others,because of the fact that modeling approach can integrate the relations among many variables into estimate procedure.The estimated core inflation arrives at the purpose of trend stability and forward-looking ability,which are essential to monetary policy decision,and those components trimmed from actually measured inflation are almost white noise,for no information left in them to expect future inflation.As result,the estimated core inflation can act as a useful tool to make effective monetary policy decision for the central bank.
出处
《上海金融》
CSSCI
北大核心
2013年第2期48-53,117,共6页
Shanghai Finance
作者简介
陈永志，男，福建泉州人，厦门大学经济学院教授，博士生导师；
吴锦顺，男，福建浦城人，厦门大学经济学院博士研究生，讲师。
