学习效应、通胀目标变动与通胀预期形成

发布时间：2018-09-18 06:41

【摘要】：本文在国内首次采用新凯恩斯动态随机一般均衡模型测度我国的季度通胀预期,并运用贝叶斯法估计模型参数。研究发现:时变通胀目标和学习机制能增强新凯恩斯DSGE模型对我国宏观经济的刻画程度,对主要宏观变量提供较好的预测;模型测度的通胀预期较好反映1992年以来实际通胀的变化,具有迟缓性、自我实现性、平稳化和近理性特征,同时,比统计调查法、状态空间模型、SVAR模型和马尔科夫范式转换模型等传统方法的通胀预测能力和测度稳健性更强。本文所揭示的学习机制为中央银行的通胀预期管理提供了理论依据,中央银行应提高货币政策的透明度,构造通胀预期形成的名义瞄,积极向公众宣示坚定的反通胀立场,以实现对通胀预期的有效管理。
[Abstract]:In this paper, the new Keynesian dynamic stochastic general equilibrium model is used to measure the quarterly inflation expectation in China for the first time, and Bayesian method is used to estimate the parameters of the model. It is found that the time-varying inflation target and learning mechanism can enhance the degree of depiction of the new Keynesian DSGE model to the macro economy of our country and provide a good prediction for the main macro variables. The inflation expectations measured by the model better reflect the changes in actual inflation since 1992, and have the characteristics of tardiness, self-actualization, smoothness and near-rationality. At the same time, compared with the statistical survey method, The traditional methods, such as SVAR model and Markov normal form transformation model, have stronger ability to predict inflation and measure robustness. The learning mechanism revealed in this paper provides a theoretical basis for the management of inflation expectations of the central bank. The central bank should enhance the transparency of monetary policy, construct the nominal aim for the formation of inflation expectations, and proclaim a firm anti-inflation stance to the public. To achieve effective management of inflation expectations.
【作者单位】：西安交通大学经济与金融学院;
【基金】：国家社科基金“我国金融监管的制度框架、制衡机制与绩效评价研究”(09AZD020)的资助
【分类号】：F822.5

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