Robust inference on parameters via particle filters and sandwich covariance matrices

Neil Shephard () and Arnaud Doucet

No 606, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: Likelihood based estimation of the parameters of state space models can be carried out via a particle filter. In this paper we show how to make valid inference on such parameters when the model is incorrect. In particular we develop a simulation strategy for computing sandwich covariance matrices which can be used for asymptotic likelihood based inference. These methods are illustrated on some simulated data.

Keywords: Quasi-likelihood; Particle filter; Sandwich matrix; Sequential Monte Carlo (search for similar items in EconPapers)
JEL-codes: C11 C15 C53 C58 (search for similar items in EconPapers)
Date: 2012-06-01
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (6)

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Working Paper: Robust inference on parameters via particle filters and sandwich covariance matrices (2012)
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