Estimating Nonlinear Economic Models Using Surrogate Transitions
AbstractWe propose a novel combination of algorithms for jointly estimating parameters and unobservable states in a nonlinear state space system. We exploit an approximation to the marginal likelihood to guide a Particle Marginal Metropolis-Hastings algorithm. While this algorithm seemingly targets reduced dimension marginal distributions, it draws from a joint distribution of much higher dimension. The algorithm is demonstrated on a stochastic volatility model and a Real Business Cycle model with robust preferences.
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Bibliographic InfoPaper provided by Society for Economic Dynamics in its series 2012 Meeting Papers with number 494.
Date of creation: 2012
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Postal: Society for Economic Dynamics Christian Zimmermann Economic Research Federal Reserve Bank of St. Louis PO Box 442 St. Louis MO 63166-0442 USA
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-04-13 (All new papers)
- NEP-ECM-2013-04-13 (Econometrics)
- NEP-ETS-2013-04-13 (Econometric Time Series)
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