Macroeconomics and Volatility: Data, Models, and Estimation
Rubio-RamÃrez, Juan Francisco and
Fernández-Villaverde, Jesús
Authors registered in the RePEc Author Service: Jesus Fernandez-Villaverde and
Juan F Rubio-Ramirez
No 8169, CEPR Discussion Papers from C.E.P.R. Discussion Papers
Abstract:
One basic feature of aggregate data is the presence of time-varying variance in real and nominal variables. Periods of high volatility are followed by periods of low volatility. For instance, the turbulent 1970s were followed by the much more tranquil times of the great moderation from 1984 to 2007. Modeling these movements in volatility is important to understand the source of aggregate fluctuations, the evolution of the economy, and for policy analysis. In this chapter, we first review the different mechanisms proposed in the literature to generate changes in volatility similar to the ones observed in the data. Second, we document the quantitative importance of time-varying volatility in aggregate time series. Third, we present a prototype business cycle model with time-varying volatility and explain how it can be computed and how it can be taken to the data using likelihood-based methods and non-linear filtering theory. Fourth, we present two 'real life' applications. We conclude by summarizing what we know and what we do not know about volatility in macroeconomics and by pointing out some directions for future research.
Keywords: Bayesian methods; Dsge models; stochastic volatility (search for similar items in EconPapers)
JEL-codes: C11 E10 E30 (search for similar items in EconPapers)
Date: 2010-12
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)
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Working Paper: Macroeconomics and Volatility: Data, Models, and Estimation (2010) 
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