Estimating nonlinear dynamic equilibrium economies: a likelihood approach

Jesus Fernandez-Villaverde and Juan F Rubio-Ramirez

No 2004-1, FRB Atlanta Working Paper from Federal Reserve Bank of Atlanta

Abstract: This paper presents a framework to undertake likelihood-based inference in nonlinear dynamic equilibrium economies. The authors 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. The authors 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. The authors apply their procedure to estimate the structural parameters of the neoclassical growth model.

Date: 2004
New Economics Papers: this item is included in nep-cmp, nep-dge, nep-ecm and nep-ets
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Citations: View citations in EconPapers (21)

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Working Paper: Estimating Nonlinear Dynamic Equilibrium economies: A Likelihood Approach (2004)
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