The Endogenous Kalman Filter

39 Pages Posted: 18 Apr 2007

See all articles by Brad Baxter

Brad Baxter

University of London - Economics, Mathematics and Statistics

Liam Graham

University College London - Department of Economics

Stephen H. Wright

Birkbeck College, University of London

Date Written: April 12, 2007

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

JEL Classification: E27, E37

Suggested Citation

Baxter, Brad and Graham, Liam and Wright, Stephen H., The Endogenous Kalman Filter (April 12, 2007). Available at SSRN: https://ssrn.com/abstract=980962 or http://dx.doi.org/10.2139/ssrn.980962

Brad Baxter

University of London - Economics, Mathematics and Statistics ( email )

Malet Street
London, WC1E 7HX
United Kingdom

Liam Graham (Contact Author)

University College London - Department of Economics ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Stephen H. Wright

Birkbeck College, University of London ( email )

Malet St
London, WC1 E7HX
United Kingdom

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