Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/154440
Authors: 
Maćkowiak, Bartosz
Matějka, Filip
Wiederholt, Mirko
Year of Publication: 
2017
Series/Report no.: 
ECB Working Paper 2007
Abstract: 
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 {<em>X<sub>t</sub>,…,X<sub>t-p+1</sub></em>} and {<em>ε<sub>t</sub>,…, ε<sub>t-q+1</sub></em>}, where <em>X<sub>t</sub></em> denotes the variable of interest and <em>ε<sub>t</sub></em> denotes its period <em>t</em> 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.
Subjects: 
Kalman filter
macroeconomics
rational inattention
JEL: 
D83
E32
Persistent Identifier of the first edition: 
ISBN: 
978-92-899-2728-4
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.