Costly Information Processing and Income Expectations

Daniel Gutknecht (), Stefan Hoderlein and Michael Peters ()
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Michael Peters: Yale University

No 861, Boston College Working Papers in Economics from Boston College Department of Economics

Abstract: Do individuals use all information at their disposal when forming expectations about future events? In this paper we present an econometric framework to answer this question. We show how individual information sets can be characterized by simple nonparametric exclusion restrictions and provide a quantile based test for costly information processing. In particular, our methodology does not require individuals' expectations to be rational, and we explicitly allow for individuals to have access to sources of information which the econometrician cannot observe. As an application, we use microdata on individual income expectations to study the information agents employ when forecasting future earnings. Consistent with models where information processing is costly, we find that individuals' information sets are coarse in that valuable information is discarded. To quantify the utility costs, we calibrate a standard consumption life-cycle model. Consumers would be willing to pay 0.04% of their permanent income to incorporate the econometrician’s information set in their forecasts. This represents a lower bound on the costs of information processing.

Keywords: Rational Expectations; Bounded Rationality; Information Set; Costly Information; Consumption (search for similar items in EconPapers)
JEL-codes: C14 D84 D91 (search for similar items in EconPapers)
Date: 2014-10-01
New Economics Papers: this item is included in nep-upt
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