Discrete Adjustment to a Changing Environment: Experimental Evidence

56 Pages Posted: 27 Dec 2016 Last revised: 15 Apr 2023

See all articles by Mel Khaw

Mel Khaw

Duke University

Luminita Stevens

University of Maryland

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics

Multiple version iconThere are 3 versions of this paper

Date Written: December 2016

Abstract

We conduct a laboratory experiment to shed light on the cognitive limitations that may affect the way decision makers respond to changes in their economic environment. The subjects solve a tracking problem: they estimate the probability of a binary event, which changes stochastically. The subjects observe draws and indicate their draw-by-draw estimate. Our subjects depart from the optimal Bayesian benchmark in systematic ways, but these deviations are not simply the result of some boundedly rational, but deterministic rule. Rather, there is a random element in the subjects' response to any given history of evidence. Moreover, subjects adjust their forecast in discrete jumps rather than after each new ring draw, even though there are no explicit adjustment costs. They adjust by both large and small amounts, contrary to the predictions of a simple Ss model of optimal adjustment subject to a fixed cost. Finally, subjects prefer to report "round number" probabilities, even though that requires exerting additional effort. Each of these regularities resembles the behavior of firms setting prices for their products. We develop a model of inattentive adjustment and compare its quantitative fit with alternative models of stochastic discrete adjustment.

Suggested Citation

Khaw, Mel Win and Stevens, Luminita and Woodford, Michael, Discrete Adjustment to a Changing Environment: Experimental Evidence (December 2016). NBER Working Paper No. w22978, Available at SSRN: https://ssrn.com/abstract=2890082

Mel Win Khaw (Contact Author)

Duke University ( email )

B355, 308 Research Dr
Durham, NC 27607
United States

Luminita Stevens

University of Maryland ( email )

Department of Economics
4121C Tydings Hall
College Park, MD 20742
United States

HOME PAGE: http://econweb.umd.edu/~stevens/

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

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