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Metropolis-Hastings prefetching algorithms
Strid, Ingvar - Economics Institute for Research (SIR), … - 2008
Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based …-Hastings prefetching algorithms are presented and evaluated. It is shown how to use available information to make better predictions of the … future states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the …
Persistent link: https://www.econbiz.de/10005649345
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Metropolis-Hastings prefetching algorithms
Strid, Ingvar (contributor) - 2008 - Rev. December 2, 2009
Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based … on the idea of evaluating the posterior in parallel and ahead of time. Improved Metropolis-Hastings prefetching … states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching …
Persistent link: https://www.econbiz.de/10003779724
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Chapter 9. Solution and Estimation Methods for DSGE Models
Fernández-Villaverde, J.; Rubio-Ramírez, J.F.; … - In: Handbook of macroeconomics : volume 2, v. 2A-2B SET, (pp. 527-724). 2016
This chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field.
Persistent link: https://www.econbiz.de/10014024288
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JBendge: an object-oriented system for solving, estimating and selecting nonlinear dynamic models
Winschel, Viktor; Krätzig, Markus - 2008
We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...
Persistent link: https://www.econbiz.de/10010263731
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JBendge : an object-oriented system for solving, estimating and selecting nonlinear dynamic models
Winschel, Viktor (contributor); Krätzig, Markus (contributor) - 2008
We present an object-oriented software framework allowing to specify, solve, and estimate nonlinear dynamic general equilibrium (DSGE) models. The implemented solution methods for finding the unknown policy function are the standard linearization around the deterministic steady state, and a...
Persistent link: https://www.econbiz.de/10003727355
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Solving, estimating and selecting nonlinear dynamic models without the curse of dimensionality
Winschel, Viktor; Krätzig, Markus - 2008
We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...
Persistent link: https://www.econbiz.de/10010263720
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Solving, estimating and selecting nonlinear dynamic models without the curse of dimensionality
Winschel, Viktor (contributor); Krätzig, Markus (contributor) - 2008
We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...
Persistent link: https://www.econbiz.de/10003636133
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Rising to the Challenge : Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models
Delli Gatti, Domenico - 2019
We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...
Persistent link: https://www.econbiz.de/10012860573
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Rising to the challenge : Bayesian estimation and forecasting techniques for macroeconomic agent-based models
Delli Gatti, Domenico; Grazzini, Jakob - 2019
We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...
Persistent link: https://www.econbiz.de/10012119860
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Stochastic Volatility Estimation with GPU Computing
Santos, António Alberto; Andrade, João - Grupo de Estudos Monetários e Financeiros (GEMF), … - 2014
In this paper, we show how to estimate the parameters of stochastic volatility models using Bayesian estimation and Markov chain Monte Carlo (MCMC) simulations through the approximation of the a-posteriori distribution of parameters. Simulated independent draws are made possible by using...
Persistent link: https://www.econbiz.de/10010765774