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  <http://purl.org/dc/terms/title> "Estimating Nonlinear Dynamic Equilibrium Economies: A Likelihood Approach";
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  <http://purl.org/dc/elements/1.1/creator> "Fernandez-Villaverde, Jesus",
    "Rubio-Ramírez, Juan Francisco";
  <http://purl.org/dc/elements/1.1/relation> "Dynamic equilibrium economies",
    "Nonlinear filtering",
    "Likelihood-based inference",
    "Sequential Monte Carlo methods";
  <http://purl.org/dc/elements/1.1/subject> "C15 - Statistical Simulation Methods: General",
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  <http://purl.org/dc/terms/abstract> "This paper presents a method to perform likelihood-based inference in nonlinear dynamic equilibrium economies. This type of models has become a standard  tool in quantitative economics. However, existing literature has been forced so far to use moment procedures or linearization techniques to estimate these  models. This situation is unsatisfactory: moment procedures suffer from strong small samples biases and linearization depends crucially on the shape of the true  policy functions, possibly leading to erroneous answers. We propose the use of Sequential Monte Carlo methods to evaluate the likelihood function implied by the model. Then we can perform likelihood-based inference, either searching for a maximum (Quasi-Maximum Likelihood Estimation) or simulating the posterior using a Markov Chain Monte Carlo algorithm (Bayesian Estimation). We can also compare different models even if they are nonnested and misspecified. To perform classical model selection, we follow Vuong (1989) and use the Kullback-Leibler distance to build Likelihood Ratio Tests. To perform Bayesian model comparison, we build Bayes factors. As an application, we estimate the stochastic neoclassical growth model."^^<http://ns.ontowiki.net/SysOnt/Markdown>;
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  <http://schema.org/keywords> "Dynamic equilibrium economies",
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