Estimating Dynamic Equilibrium Models with Stochastic Volatility
71 Pages Posted: 15 Sep 2012 Last revised: 10 Oct 2024
There are 2 versions of this paper
Estimating Dynamic Equilibrium Models with Stochastic Volatility
Estimating Dynamic Equilibrium Models with Stochastic Volatility
Date Written: September 2012
Abstract
We 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.
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
Determining Consumers' Discount Rates with Field Studies
By Song Yao, Carl F. Mela, ...
-
A Structural Model of Sales-Force Compensation Dynamics: Estimation and Field Implementation
By Sanjog Misra and Harikesh Nair
-
By Hanming Fang and Yang Wang
-
By Hanming Fang and Yang Wang
-
By Doug Chung, Thomas J. Steenburgh, ...
-
The Welfare Effects of Incentive Schemes
By Adam M. Copeland and Cyril Monnet
-
Compensation and Peer Effects in Competing Sales Teams
By Tat Y. Chan, Jia Li, ...
-
By Masakazu Ishihara and Andrew T. Ching
-
Individual Preferences, Organization, and Competition in a Model of R&D Incentive Provision
By Nicola Lacetera and Lorenzo Zirulia
-
By Jean-pierre Dubé, Günter J. Hitsch, ...