数据修订、实时估计与时变参数货币政策规则抉择

本文拓展构建了后顾、同期和前瞻三种类型的货币政策规则，并基于实时数据和最终数据实证分析数据修订和实时估计对货币政策参数的影响效应。研究结果发现，数据修订对泰勒规则的影响取决于不同模型，而且在三种模型设定中，盯住产出缺口和通胀目标的时变参数均在不同程度上受数据修订的影响。特别是，对于最终数据，采用同期性货币政策规则展开估计最为有效；而对于实时数据，则基于后顾性货币政策规则模型估计是最佳的。最后，本文在数据选择和模型匹配上提出相应的对策建议。

Data Revision,Real-time Estimation and the Identification of Time-Varying Parameters Monetary Policy

This paper extends to build three models, such as backward-looking, synchronism and forward-looking time-varying Taylor rule, then uses them to estimate the time-varying monetary policy of China based on ex-post data and real-time data, and final investigates the influences of data-revision and real-time estimation on the Taylor rule. The estimated results show that the effects of data-revision on the Taylor rule estimation depends on the choice of the models, furthermore, the time-varying parameters of targeting to inflation and output gap are all influenced by data-revision in the three models. In particular, it’s suitable for the ex-post data to choose synchronism Taylor rule model, while the backward-looking Taylor rule model is much better for the real-time data. Finally, this paper puts forward the corresponding suggestions of model selection based on different data.