Efficient likelihood evaluation of state-space representations

David N. DeJong; Hariharan Dharmarajan; Roman Liesenfeld; Guilherme V. Moura; Jean-François Richard

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure approximates necessary integrals using continuous approximations of target densities. Construction is achieved via efficient importance sampling, and approximating densities are adapted to fully incorporate current information. We illustrate our procedure in applications to dynamic stochastic general equilibrium models. -- particle filter ; adaption ; efficient importance sampling ; kernel density approximation ; dynamic stochastic general equilibrium model

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Year of publication:	2009
Authors:	DeJong, David Neil ; Dharmarajan, Hariharan ; Liesenfeld, Roman ; Moura, Guilherme Valle ; Richard, Jean-François
Publisher:	Kiel : Univ., Dep. of Economics
Subject:	Zustandsraummodell \| State space model \| Analysis \| Mathematical analysis \| Allgemeines Gleichgewicht \| General equilibrium \| Dynamische Wirtschaftstheorie \| Economic dynamics \| Stochastischer Prozess \| Stochastic process \| Theorie \| Theory