Preferences of the Central Bank of Brazil under the inflation targeting regime: Estimation using a DSGE model for a small open economy

The main objective of this paper is to estimate the preferences of the Central Bank of Brazil after the inflation targeting regime (January 2000 to December 2013), using a DSGE model with microeconomic foundations for a small open economy, based especially on the work of Kam et al. (2009). The model used in this study considers that the Central Bank minimizes a loss function, taking into account the deviation of inflation from its target, output stabilization, the interest rate smoothing and, unlike the previous works, the exchange rate. The results show that the major concern of the monetary authority in the period was the stabilization of inflation, followed by interest rate smoothing, exchange stabilization and, finally, output stabilization. The large value for the exchange rate smoothing parameter suggests the presence of fear of floating in the Brazilian case. An improved inflation targeting strategy should allow for less Central Bank intervention in the exchange rate market.     

房价波动、宏观审慎及与货币政策的协调

运用QVAR模型和内嵌宏观审慎工具的DSGE模型,阐释了宏观审慎调控对房价波动的作用机制、政策效率以及与货币政策的协调。研究表明,宏观审慎政策通过规范居民住房融资行为,削弱了抵押品渠道所产生的金融加速器效应,从而实现了稳定房价波动和改善居民福利状况的调控目标。当存在供给侧价格黏性时,货币政策对房价波动作出反应有助于提升宏观审慎调控效果。因此,为实现宏观经济与金融体系的稳定,货币当局应采用盯住房价波动的货币政策来配合宏观审慎调控,充分发挥政策组合的协同效应。     

Bayesian Analysis of DSGE Models by S. An and F. Schorfheide

The paper that An and Schorfheide have written is an excellent piece of work and will become a useful reference for teaching and consultation purposes. The paper discusses in an articulate and convincing manner almost everything that one could think of covering in such a review. This makes the task of the commentator difficult. Nevertheless, I will attempt to add few insights on three issues which, in my opinion, play an important role in applied work and in the interpretation of the estimation result. In particular, I will discuss a) the sensitivity of posterior distributions to prior spreads; b) the effects of model misspecification and an approach to model respecification; c) parameter identification and its consequences for posterior inference.     

The Changing Transmission of Uncertainty Shocks in the U.S.

This article investigates if the impact of uncertainty shocks on the U.S. economy has changed over time. To this end, we develop an extended factor augmented vector autoregression (VAR) model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on a range of variables. We find that the impact of uncertainty shocks on real activity and financial variables has declined systematically over time. In contrast, the response of inflation and the short-term interest rate to this shock has remained fairly stable. Simulations from a nonlinear dynamic stochastic general equilibrium (DSGE) model suggest that these empirical results are consistent with an increase in the monetary authorities’ antiinflation stance and a “flattening” of the Phillips curve. Supplementary materials for this article are available online.     

基于DSGE模型的利率传导机制研究

动态随机一般均衡模型对中国的经济数据拟合较好,可用来分析中国的经济问题;利率作为中国货币政策的中介目标是适宜的,泰勒规则可以用来指导中国的货币政策实践;利率冲击通过影响资本投资价值进而投资而对产出产生影响,消费的传导作用相对较小。     

利率平价偏离、资本账户开放与经济波动——基于小国DSGE模型的分析

基于中国资本管制、意愿结售汇改革、冲销干预等特征,引入国际风险溢价构建一个小国开放经济DSGE模型,分析了利率平价偏离时资本账户开放对中国经济波动和社会福利的影响.理论分析和数值模拟表明:1)利率平价偏离程度上升会增加本国通胀风险,加剧经济波动,伴随社会福利水平下降,如果央行忽略利率平价偏离的影响,将低估外国货币政策冲击对本国通胀和经济波动,以及社会福利的影响;2)资本账户开放会减小本国通胀风险,降低本国经济波动,提高社会福利水平.因此,中国应该坚持资本账户开放,稳步推进利率和汇率市场化改革,减小利率平价偏离程度,进一步提高资本账户开放的收益.     

情绪冲击、资产泡沫与经济波动:基于贝叶斯DSGE的分析

本文在Smets和Wouters(2003)、Christiano等(2005)模型基础上，引入驱动股价泡沫的情绪冲击，构建了情绪冲击通过资产价格渠道影响经济波动的动态随机一般均衡模型，并采用我国2000-2016年的季度数据对模型进行贝叶斯估计。研究表明，由于企业面临融资约束，正向情绪冲击带来股价泡沫的上升起到了放松信贷约束的作用，因而企业投资增加，进而触发一系列经济变量的顺周期波动。情绪冲击能够解释我国股票价格波动的552%以及顺周期性；劳动供给冲击、技术冲击、投资专有冲击、金融冲击都是我国经济波动的来源，尽管其对产出、消费、投资、劳动时间和股票价格波动的贡献存在异质性。     

Bayesian Analysis of DSGE Models—Rejoinder

We would like to thank all the discussants for their stimulating comments. While our article to a large extent reviews current practice of Bayesian analysis of Dynamic Stochastic General Equilibrium (DSGE) models the discussants provide many ideas to improve upon the current practice, thereby outlining a research agenda for the years to come. In our rejoinder we will briefly revisit some of the issues that were raised.     

Solving,Estimating, and Selecting Nonlinear Dynamic Models Without the Curse of Dimensionality

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids to overcome the curse of dimensionality for approximations. We apply sparse grids to a global polynomial approximation of the model solution, to the quadrature of integrals arising as rational expectations, and to three new nonlinear state space filters which speed up the sequential importance resampling particle filter. The posterior of the structural parameters is estimated by a new Metropolis–Hastings algorithm with mixing parallel sequences. The parallel extension improves the global maximization property of the algorithm, simplifies the parameterization for an appropriate acceptance ratio, and allows a simple implementation of the estimation on parallel computers. Finally, we provide all algorithms in the open source software JBendge for the solution and estimation of a general class of models.     

不同黏性对中国经济波动和货币政策的影响——基于贝叶斯估计的新凯恩斯 DSGE 模型

考察了中国宏观经济波动和货币政策． 研究结果显示: 包含 3 种黏性机制的 DSGE 模型比传统的仅含一种黏性机制的 DSGE 模型能更好地拟合和解释中国现实经济特征; 黏性信息企业占中国全部企业 54． 01% ，混合黏性价格企业占 43． 63% ，弹性价格企业占 2． 36% ; 不同黏性机制下，外生冲击对经济变量波动的解释度存在显著差异，并且经济变量对外生冲击的脉冲响应及动态调整路径存在显著差异; 对不同黏性机制行业的通胀做出系统性反应能够提高中国货币政策有效性．