Estimating Nonlinear Dynamic Equilibrium Economies: A Likelihood Approach

56 Pages Posted: 12 Jan 2004

See all articles by Jesús Fernández-Villaverde

Jesús Fernández-Villaverde

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Juan Francisco Rubio-Ramirez

Federal Reserve Bank of Atlanta - Research Department

Multiple version iconThere are 2 versions of this paper

Date Written: January 6, 2004

Abstract

This paper presents a framework to undertake likelihood-based inference in nonlinear dynamic equilibrium economies. We develop a Sequential Monte Carlo algorithm that delivers an estimate of the likelihood function of the model using simulation methods. This likelihood can be used for parameter estimation and for model comparison. The algorithm can deal both with nonlinearities of the economy and with the presence of non-normal shocks. We show consistency of the estimate and its good performance in finite simulations. This new algorithm is important because the existing empirical literature that wanted to follow a likelihood approach was limited to the estimation of linear models with Gaussian innovations. We apply our procedure to estimate the structural parameters of the neoclassical growth model.

Keywords: Likelihood-Based Inference, Dynamic Equilibrium Economies, Nonlinear Filtering, Sequential Monte Carlo

JEL Classification: C10, C11, C13, C15

Suggested Citation

Fernández-Villaverde, Jesús and Rubio-Ramirez, Juan Francisco, Estimating Nonlinear Dynamic Equilibrium Economies: A Likelihood Approach (January 6, 2004). PIER Working Paper No. 04-001. Available at SSRN: https://ssrn.com/abstract=486083 or http://dx.doi.org/10.2139/ssrn.486083

Jesús Fernández-Villaverde (Contact Author)

University of Pennsylvania - Department of Economics ( email )

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National Bureau of Economic Research (NBER)

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Juan Francisco Rubio-Ramirez

Federal Reserve Bank of Atlanta - Research Department ( email )

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United States
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HOME PAGE: http://www.econ.umn.edu/~rubio

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