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Estimating Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood

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Author Info
Jesus Fernandez-Villaverde () (Department of Economics, University of Pennsylvania)
Juan F. Rubio-Ramirez () (Federal Reserve Bank of Atlanta)

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Abstract

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernández-Villaverde and Rubio-Ramírez (2004) and the Kalman filter. The Sequential Monte Carlo filter exploits the nonlinear structure of the economy and evaluates the likelihood function of the model by simulation methods. The Kalman filter estimates a linearization of the economy around the steady state. We report two main results. First, both for simulated and for real data, the Sequential Monte Carlo filter delivers a substantially better fit of the model to the data as measured by the marginal likelihood. This is true even for a nearly linear case. Second, the differences in terms of point estimates, even if relatively small in absolute values, have important effects on the moments of the model. We conclude that the nonlinear filter is a superior procedure for taking models to the data.

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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 04-005.

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Length: 37 pages
Date of creation: 20 Jan 2004
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Handle: RePEc:pen:papers:04-005

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Related research
Keywords: Likelihood-Based Inference Dynamic Equilibrium Economies Nonlinear Filtering Kalman Filter Sequential Monte Carlo

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Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    Other versions:
  2. S. Boragan Aruoba & Jesus Fernandez-Villaverde & Juan Francisco Rubio-Ramirez, 2003. "Comparing solution methods for dynamic equilibrium economies," Working Paper 2003-27, Federal Reserve Bank of Atlanta. [Downloadable!]
    Other versions:
  3. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  7. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2004. "Estimating Nonlinear Dynamic Equilibrium economies: A Likelihood Approach," PIER Working Paper Archive 04-001, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania. [Downloadable!]
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Manuel Santos, 2005. "Convergence Properties of the Likelihood of Computed Dynamic Models," Levine's Bibliography 122247000000000822, UCLA Department of Economics. [Downloadable!]
    Other versions:
  2. Hall, Alastair & Inoue, Atsushi & Nason M, James & Rossi, Barbara, 2007. "Information Criteria for Impulse Response Function Matching Estimation of DSGE Models," Working Papers 07-04, Duke University, Department of Economics. [Downloadable!]
    Other versions:
  3. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2006. "The Research Agenda: Jesus Fernandez-Villaverde and Juan F. Rubio-Ramirez on Estimating DSGE Models," EconomicDynamics Newsletter, Review of Economic Dynamics, vol. 8(1), November. [Downloadable!]
  4. Luca Dedola & Stefano Neri, 2006. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Working Paper Series 705, European Central Bank. [Downloadable!]
    Other versions:
  5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," Levine's Bibliography 122247000000000849, UCLA Department of Economics. [Downloadable!]
    Other versions:
  6. Matthias Kredler, 2005. "Bayesian Estimation of a Dynamic Partial-Equilibrium Model for Investment," Econometrics 0509003, EconWPA. [Downloadable!]
  7. Fabio Canova & Luca Sala, 2005. "Back to square one: identification issues in DSGE models," Economics Working Papers 927, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2006. [Downloadable!]
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  8. Jesús Fernández-Villaverde & Juan F Rubio-Ramírez, 2007. "How Structural Are Structural Parameters?," Levine's Bibliography 843644000000000057, UCLA Department of Economics. [Downloadable!]
  9. Timothy Cogley, 2005. "Changing Beliefs and the Term Structure of Interest Rates: Cross-Equation Restrictions with Drifting Parameters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 420-451, April. [Downloadable!] (restricted)
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