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Thursday, September 7, 2017 at 11:40am to 1:10pm
Uris Hall, 498
Central Campus
Bartosz Mackowiak
European Central Bank
The Rational Inattention Filter (joint w/Filip Matejka & Mirko Wiederholt)
Dynamic rational inattention problems used to be difficult to solve. This paper provides simple, analytical results for dynamic rational inattention problems. We start from the benchmark rational inattention problem. An agent tracks a variable of interest that follows a Gaussian process. The agent chooses how to pay attention to this variable. The agent aims to minimize, say, the mean squared error subject to a constraint on information flow, as in Sims (2003). We prove that if the variable of interest follows an ARMA(p,q) process, the optimal signal is about a linear combination of {Xt, . . . , Xt−p+1} and {εt, . . . , εt−q+1}, where Xt denotes the variable of interest and εt denotes its period t innovation. The optimal signal weights can be computed from a simple extension of the Kalman filter: the usual Kalman filter equations in combination with first-order conditions for the optimal signal weights. We provide several analytical results regarding those signal weights. We also prove the equivalence of several different formulations of the information flow constraint. We conclude with general equilibrium applications from
Macroeconomics.
Amy Moesch
607-255-5617
Bartosz Mackowiak
European Central Bank
Cornell Economics Community (List Serve Members)