Choosing a Good Toolkit: An Essay in Behavioral Economics

Alejandro Francetich and David Kreps

No 524, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University

Abstract: The problemof choosing an optimal toolkit day after day,when there is uncertainty concerning the value of different tools that can only be resolved by carrying the tools, is a multi-armed bandit problem with nonindependent arms. Accordingly, except for very simple specifications, this optimization problem cannot (practically) be solved. Decision takers facing this problem presumably resort to decision heuristics, “sensible” rules fordeciding which tools to carry, based on past experience. In this paper, we examine and compare the performance of a variety of heuristics, some very simple and others inspired by the computer-science literature on these problems. Some asymptotic results are obtained, especially concerning the long-run outcomes of using the heuristics, hence these results indicate which heuristics do well when the discount factor is close to one. But our focus is on the relative performance of these heuristics for discount factors bounded away from one, which we study through simulation of the heuristics on a collection of test problems.

Date: 2014
New Economics Papers: this item is included in nep-cbe, nep-cmp, nep-evo and nep-mic
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