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Estimating Models with Dispersed Information †

Estimating Models with Dispersed Information † Abstract We conduct likelihood evaluation of a DSGE model in which firms have imperfect common knowledge. Imperfect common knowledge is found to be more successful than price stickiness à la Calvo to account for the highly persistent effects of nominal shocks on output and inflation. Our likelihood analysis suggests that firms pay little attention to aggregate nominal conditions. This paper shows that such allocation of attention is plausible because it is optimal for firms with a reasonably small size of information frictions and a size of idiosyncratic uncertainty that is in line with the micro evidence on price changes. (JEL C51, D83, E13, E23, E31 ) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Economic Journal: Macroeconomics American Economic Association

Estimating Models with Dispersed Information †

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Publisher
American Economic Association
Copyright
Copyright © 2014 by the American Economic Association
Subject
Articles
ISSN
1945-7715
eISSN
1945-7715
DOI
10.1257/mac.6.1.1
Publisher site
See Article on Publisher Site

Abstract

Abstract We conduct likelihood evaluation of a DSGE model in which firms have imperfect common knowledge. Imperfect common knowledge is found to be more successful than price stickiness à la Calvo to account for the highly persistent effects of nominal shocks on output and inflation. Our likelihood analysis suggests that firms pay little attention to aggregate nominal conditions. This paper shows that such allocation of attention is plausible because it is optimal for firms with a reasonably small size of information frictions and a size of idiosyncratic uncertainty that is in line with the micro evidence on price changes. (JEL C51, D83, E13, E23, E31 )

Journal

American Economic Journal: MacroeconomicsAmerican Economic Association

Published: Jan 1, 2014

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