Solving, Estimating, and Selecting Nonlinear Dynamic Models Without the Curse of Dimensionality

DOI10.3982/ECTA6297zbMath1229.91210OpenAlexW3022496575MaRDI QIDQ3564700

Markus Krätzig, Viktor Winschel

Publication date: 26 May 2010

Published in: Econometrica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3982/ecta6297

zbMATH Keywords

curse of dimensionalityBayesian structural time series econometricsdynamic stochastic general equilibrium (DSGE) models

Mathematics Subject Classification ID

Bayesian inference (62F15) Economic time series analysis (91B84) Dynamic stochastic general equilibrium theory (91B51)

Related Items (9)

Likelihood approximation by numerical integration on sparse grids ⋮ Nonlinear adventures at the zero lower bound ⋮ DEEP EQUILIBRIUM NETS ⋮ Executions in (Semi-)Integer Petri Nets are Compact Closed Categories ⋮ Solving the multi-country real business cycle model using a monomial rule Galerkin method ⋮ Unnamed Item ⋮ Stable and efficient cubature rules by metaheuristic optimization with application to Kalman filtering ⋮ A computationally efficient fixed point approach to dynamic structural demand estimation ⋮ Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain

Uses Software

• CompEcon
• Dynare
• JBendge
• nwSpGr

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