Estimating dynamic equilibrium models with stochastic volatility
AbstractWe propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the properties of the solution to this class of models. Second, we take advantage of the results about the structure of the solution to build a sequential Monte Carlo algorithm to evaluate the likelihood function of the model. The approach, which exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large-scale models, such as those often employed by policy-making institutions. As an application, we use our algorithm and Bayesian methods to estimate a business cycle model of the U.S. economy with both stochastic volatility and parameter drifting in monetary policy. Our application shows the importance of stochastic volatility in accounting for the dynamics of the data.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 13-19.
Date of creation: 2013
Date of revision:
Other versions of this item:
- Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Juan Rubio-Ramirez, 2013. "Estimating Dynamic Equilibrium Models with Stochastic Volatility," Working Papers 2013-23, FEDEA.
- Jesus Fernandez-Villaverde & Pablo Guerrón-Quintana & Juan F. Rubio-Ramírez, 2013. "Estimating Dynamic Equilibrium Models with Stochastic Volatility," PIER Working Paper Archive 13-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Jesus Fernandez-Villaverde & Pablo A. Guerrón-Quintana & Juan Rubio-Ramírez, 2012. "Estimating Dynamic Equilibrium Models with Stochastic Volatility," NBER Working Papers 18399, National Bureau of Economic Research, Inc.
- Fernández-Villaverde, Jesús & Guerron-Quintana, Pablo A. & Rubio-Ramírez, Juan Francisco, 2012. "Estimating Dynamic Equilibrium Models with Stochastic Volatility," CEPR Discussion Papers 9130, C.E.P.R. Discussion Papers.
- E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
- E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-05-24 (All new papers)
- NEP-DGE-2013-05-24 (Dynamic General Equilibrium)
- NEP-ETS-2013-05-24 (Econometric Time Series)
- NEP-ORE-2013-05-24 (Operations Research)
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