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Estimating Nonlinear Dynamic Equilibrium economies: A Likelihood Approach

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  • Jesus Fernandez-Villaverde

    (Department of Economics, University of Pennsylvania)

  • Juan F. Rubio-Ramirez

    (Federal Reserve Bank of Atlanta)

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.

Suggested Citation

  • 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.
    • Handle: RePEc:pen:papers:04-001
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    Cited by:

    1. Ferrari Minesso, Massimo & Pagliari, Maria Sole, 2023. "No country is an island. International cooperation and climate change," Journal of International Economics, Elsevier, vol. 145(C).
    2. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2001. "Comparing dynamic equilibrium economies to data," FRB Atlanta Working Paper 2001-23, Federal Reserve Bank of Atlanta.
    3. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    4. Alejandro Justiniano & Giorgio E. Primiceri, 2008. "The Time-Varying Volatility of Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 98(3), pages 604-641, June.
    5. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Manuel S. Santos, 2006. "Convergence Properties of the Likelihood of Computed Dynamic Models," Econometrica, Econometric Society, vol. 74(1), pages 93-119, January.
    6. Thomas Lubik & Frank Schorfheide, 2006. "A Bayesian Look at New Open Economy Macroeconomics," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 313-382, National Bureau of Economic Research, Inc.
    7. Michael P. Keane & Robert M. Sauer, 2009. "Classification Error in Dynamic Discrete Choice Models: Implications for Female Labor Supply Behavior," Econometrica, Econometric Society, vol. 77(3), pages 975-991, May.
    8. Linnea Polgreen & Pedro Silos, 2008. "Capital-Skill Complementarity and Inequality: A Sensitivity Analysis," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(2), pages 302-313, April.
    9. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    10. Hong, Han & Preston, Bruce, 2012. "Bayesian averaging, prediction and nonnested model selection," Journal of Econometrics, Elsevier, vol. 167(2), pages 358-369.
    11. Pytlarczyk, Ernest, 2005. "An estimated DSGE model for the German economy within the euro area," Discussion Paper Series 1: Economic Studies 2005,33, Deutsche Bundesbank.
    12. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
    13. 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.
    14. Frank Schorfheide, 2005. "Learning and Monetary Policy Shifts," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 392-419, April.
    15. Caiani, Alessandro & Godin, Antoine & Caverzasi, Eugenio & Gallegati, Mauro & Kinsella, Stephen & Stiglitz, Joseph E., 2016. "Agent based-stock flow consistent macroeconomics: Towards a benchmark model," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 375-408.
    16. Juan F. Rubio-Ramirez & Jesus Fernández-Villaverde, 2005. "Estimating dynamic equilibrium economies: linear versus nonlinear likelihood," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 891-910.
    17. Pau Rabanal & Juan F. Rubio-Ramirez, 2001. "Nominal versus real wage rigidities: A Bayesian approach," FRB Atlanta Working Paper 2001-22, Federal Reserve Bank of Atlanta.

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    More about this item

    Keywords

    Likelihood-Based Inference; Dynamic Equilibrium Economies; Nonlinear Filtering; Sequential Monte Carlo);
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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