A Markov-Switching DSGE model for measuring the output gap in Brazil

Eleonora de Oliveira , Andreza A. Palma , Marcelo S. Portugal
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Abstract

The output gap, while inherently unobservable, plays a pivotal role in informing policymakers due to its significant implications for forecasting inflation rates and understanding the mechanisms of monetary policy transmission. Traditional filters frequently employed in estimating the output gap face criticism for being purely statistical and lacking economic theory. Conversely, estimates derived from Dynamic Stochastic General Equilibrium (DSGE) models encounter challenges stemming from the assumption of constant parameters over time. This study focuses on estimating the output gap for Brazil, employing a full specified DSGE model that incorporates Markov-Switching elements (MS-DSGE) to account for potential regime shifts. We introduce four model versions, some of which incorporate variations in volatilities and Taylor’s rule parameters. In order to compare our output gap estimate with other approaches, we perform prediction tests, both with the central bank’s reaction function and with the free price inflation Phillips curve. Our results in the first test indicate that the HP (Hodrick–Prescott) filter estimate performs better in the short and mid-term, but the MS-DSGE estimate presented better results in the long run. In the second exercise, no output gap series stands out among the approaches considered. In this context, the estimated output gap from the MS-DSGE framework emerges as a valuable asset within the arsenal available to policymakers, contributing meaningfully to their analytical toolkit.

衡量巴西产出缺口的马尔科夫-转换 DSGE 模型
产出缺口虽然本质上是不可观测的,但由于其对预测通货膨胀率和了解货币政策传导机制具有重要影响,因此在为决策者提供信息方面发挥着关键作用。在估算产出缺口时经常使用的传统滤波器因纯粹的统计方法和缺乏经济理论而受到批评。相反,从动态随机一般均衡(DSGE)模型中得出的估计值也会遇到因假设参数随时间变化而不变而产生的挑战。本研究侧重于估算巴西的产出缺口,采用了一个包含马尔科夫转换要素(MS-DSGE)的完全指定的 DSGE 模型,以考虑潜在的制度转换。我们引入了四个模型版本,其中一些包含了波动率和泰勒规则参数的变化。为了将我们的产出缺口估计与其他方法进行比较,我们使用中央银行的反应函数和自由价格通胀菲利普斯曲线进行了预测测试。第一个测试结果表明,HP(霍德里克-普雷斯科特)滤波估计在短期和中期表现更好,但 MS-DSGE 估计在长期表现更好。在第二项测试中,没有任何产出缺口序列在所考虑的方法中脱颖而出。在这种情况下,MS-DSGE 框架估算的产出缺口成为决策者可利用的宝贵资产,为他们的分析工具包做出了有意义的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.70
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