Decomposing Models of Bounded Rationality

This paper illustrates a general disconnection between many models of bounded rationality and human decision making. A new mathematical approach allows for any game to be decomposed into unique components. The strategic component of a game contains the necessary and su cient information to determine the prediction for a broad class of models focused on bounded rationality. Among others, this class of models includes the most commonly used speci cations for Quantal Response (QRE), Noisy Introspection (NI), level-k, and Cognitive Hierarchy (CH). These bounded rationality models are shown to exhibit a mathematical invariance to changes in a game's nonstrategic components, and this paper's primary hypothesis is that humans do not exhibit this invariance. Using a laboratory experiment consisting of simple 2×2 games, we nd that human subjects systematically respond a game's behavioral component, which is ignored by the QRE, NI, level-k, and CH models. We show that previous results and puzzles related to these models are special cases of our general nding. In addition, our approach can predict the settings in which contemporaneous models of bounded rationality will generate good (and poor) ts of human behavior before the data is collected, making it a valuable tool for future research. ∗International Institute for Applied Systems Analysis (IIASA). Laxenburg, Austria. Email: jessie@iiasa.ac.at †Postdoctoral Research Associate. Department of Economics. University of Southern California. Los Angeles Behavioral Economics Laboratory (LABEL). Email: rakendal@usc.edu