Solving, Estimating, and Selecting Nonlinear Dynamic Models Without The Curse of Dimensionality.
We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids to overcome the curse of dimensionality for approximations. We apply sparse grids to a global polynomial approximation of the model solution, to the quadrature of integrals ar...
| Publicado en: | Econometrica Vol. 78; no. 2; pp. 803 - 822 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
March 2010
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=511483217&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 511483217 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00129682 ECN jtl: Econometrica issn: 00129682 maglogo: N pubinfo: dt: March 2010 vid: 78 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 511483217 10.3982/ECTA6297 ppf: 803 ppct: 19 formats: tig: atl: Solving, Estimating, and Selecting Nonlinear Dynamic Models Without The Curse of Dimensionality. aug: au: Winschel, Viktor Krätzig, Markus su: Bayesian analysis Economic equilibrium Estimation theory sug: subj: Bayesian analysis Economic equilibrium Estimation theory ab: We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids to overcome the curse of dimensionality for approximations. We apply sparse grids to a global polynomial approximation of the model solution, to the quadrature of integrals arising as rational expectations, and to three new nonlinear state space filters which speed up the sequential importance resampling particle filter. The posterior of the structural parameters is estimated by a new Metropolis–Hastings algorithm with mixing parallel sequences. The parallel extension improves the global maximization property of the algorithm, simplifies the parameterization for an appropriate acceptance ratio, and allows a simple implementation of the estimation on parallel computers. Finally, we provide all algorithms in the open source software JBendge for the solution and estimation of a general class of models. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|