The Endogenous Kalman Filter

Brad Baxter, Liam Graham and Stephen Wright
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Brad Baxter: Department of Economics, Mathematics & Statistics, Birkbeck

No 719, Birkbeck Working Papers in Economics and Finance from Birkbeck, Department of Economics, Mathematics & Statistics

Abstract: We relax the assumption of full information that underlies most dynamic general equilibrium models, and instead assume agents optimally form estimates of the states from an incomplete information set. We derive a version of the Kalman filter that is endogenous to agents' optimising decisions, and state conditions for its convergence. We show the (restrictive) conditions under which the endogenous Kalman filter will at least asymptotically reveal the true states. In general we show that incomplete information can have significant implications for the time-series properties of economies. We provide a Matlab toolkit which allows the easy implementation of models with incomplete information.

Keywords: Dynamic general equilibrium; Kalman filter; imperfect information; signal extraction (search for similar items in EconPapers)
JEL-codes: E27 E37 (search for similar items in EconPapers)
Date: 2007-11
New Economics Papers: this item is included in nep-dge, nep-ecm, nep-ets and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://eprints.bbk.ac.uk/id/eprint/26893 First version, 2007 (application/pdf)

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