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Robust inference on parameters via particle filters and sandwich covariance matrices.

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.

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Publisher:
Department of Economics (University of Oxford)
Series:
Discussion paper series
Publication date:
2012-01-01
Language:
English
UUID:
uuid:c1488540-b5f4-4126-8eee-17878ddbfb28
Local pid:
oai:economics.ouls.ox.ac.uk:15399
Deposit date:
2013-04-20

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