Empirical Models of Inattentive Adjustment

Michael Woodford, Luminita Stevens and Mel Win Khaw
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Luminita Stevens: University of Maryland
Mel Win Khaw: Columbia University

No 868, 2017 Meeting Papers from Society for Economic Dynamics

Abstract: We consider empirical tests for a class of models of discrete adjustment in which both the decision when to adjust and the decision where to move conditional on adjustment are assumed to be optimal, but in terms of an objective that includes costs of paying closer attention to both decisions. The particular theory of attention costs that we consider is based on the theory of "rational inattention" proposed by Sims (2003, 2011) and applied to the discrete adjustment of firms' pricing policies by Woodford (2009) and Stevens (2015). We generalize the models of inattentive adjustment used in the latter two papers by relaxing the assumption that agents learn the true state upon adjustment, and by introducing the possibility of intrinsic preference for particular actions. We contrast the implications of this extended model with other models of inattention and with models that feature relative-entropy "control costs," like that of Costain and Nakov (2014).

Date: 2017
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