How to Maximize the Likelihood Function for a DSGE Model

CREATES Research Paper 2008-32

32 Pages Posted: 27 Feb 2008

See all articles by Martin M. Andreasen

Martin M. Andreasen

Aarhus University; CREATES, Aarhus University

Date Written: June 19, 2008

Abstract

This paper extends two optimization routines to deal with objective functions for DSGE models. The optimization routines are i) a version of Simulated Annealing developed by Corana, Marchesi & Ridella (1987), and ii) the evolutionary algorithm CMA-ES developed by Hansen, Müller & Koumoutsakos (2003). Following these extensions, we examine the ability of the two routines to maximize the likelihood function for a sequence of test economies. Our results show that the CMA-ES routine clearly outperforms Simulated Annealing in its ability to find the global optimum and in efficiency. With 10 unknown structural parameters in the likelihood function, the CMA-ES routine finds the global optimum in 95% of our test economies compared to 89% for Simulated Annealing. When the number of unknown structural parameters in the likelihood function increases to 20 and 35, then the CMA-ES routine finds the global optimum in 85% and 71% of our test economies, respectively. The corresponding numbers for Simulated Annealing are 70% and 0%.

Keywords: Simulated Annealing, Resampling, CMA-ES, CMA-ES optimization routine,Likelihood function, Multimodel objective function, Non-convex search space, Resampling, The Nelder-Mead simplex routine

JEL Classification: C61, C88, E30

Suggested Citation

Andreasen, Martin M., How to Maximize the Likelihood Function for a DSGE Model (June 19, 2008). CREATES Research Paper 2008-32, Available at SSRN: https://ssrn.com/abstract=1098800 or http://dx.doi.org/10.2139/ssrn.1098800

Martin M. Andreasen (Contact Author)

Aarhus University ( email )

Aarhus
Denmark

CREATES, Aarhus University ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

HOME PAGE: http://econ.au.dk/research/research-centres/creates/people/junior-fellows/martin-andreasen/

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