基于实时数据的货币政策规则研究——以泰勒规则为例

The Study of Monetary Policy Rule Based On Real Time Data:Case of Taylor Rule

随着我国利率市场化进程加快,基于利率的泰勒规则在货币政策决策中重要性日益凸显。泰勒规则基于产出缺口的估计,其有效性严重依赖于估计方法和可得数据。货币政策基于当期数据,无法对实际经济状况做出正确判断。实时数据具有时效强、信息量大、能够分离噪音的优点,有效利用实时数据是货币政策新的发展方向。针对中国经济特征,本文构建实际季度GDP实时数据集,应用比较六种非线性估计方法,评估实时泰勒规则在中国的适用性,旨在考察中国数据环境提升能否提高货币政策的有效性。本文基于年度与季度Denton衔接法,构建了中国实际季度GDP实时数据集。构建我国实时货币政策反应函数,考察泰勒规则在我国的适用性。基于产出缺口序列,分别估计了基于实时数据和最近数据的后顾性、同期和前瞻性泰勒规则,探讨了不同退势方法、实时数据和最近数据对估计货币政策反应函数的影响。利用Granger一Newbold,Diebold-Mariaro检验,结果表明基于实时数据的前瞻性泰勒规则可以起到稳定经济的作用,能够作为我国货币政策的一个参照尺度,而后顾性和同期泰勒规则是不稳定的。

With speed up the process of marketization of interest rate,monetary policy decision based on Taylor rule has play an increasingly role.The estimation on Taylor rule is based on the estimated output gap,which is heavily dependent on available data and estimation methods.For Chinese economic characteristics,the paper build the actual quarterly GDP data sets in real time based on annual and quarterly Denton method,compare the application of six nonlinear estimation method,the monetary policy reaction function,real-time assessment of the applicability of the Taylor rule in China.Based on the output gap sequences were estimated based on backward,forward-looking Taylor rule the real-time data and the most recent data,and compare the different detrend methods,real-time data and the impact of recent data on the estimated monetary policy reaction function.Using Granger-Newbold and Diebold-Mariaro test,forward-looking Taylor rule based real-time data play a role in stabilizing the economy,which can be used as a reference of China's monetary policy.