COWLES FOUNDATION FOR RESEARCH IN ECONOMICS
AT YALE UNIVERSITY

Box 208281
New Haven, CT 06520-8281

COWLES FOUNDATION DISCUSSION PAPER NO. 1853

Bounded Rationality and Limited Datasets:
Testable Implications, Identification, and Out-of-Sample Prediction

Geoffroy de Clippel and Kareen Rozen

March 2012
Updated July 2013

Theories of bounded rationality are typically characterized over an exhaustive data set. This paper aims to operationalize such theories in settings where the available data is limited. How does one test whether observed choices are consistent with a theory of bounded rationality if the data is incomplete? What information can be identified about preferences? How can out-of-sample predictions be made? We develop a methodology to address these questions, providing a simple test for various theories. We show that previous attempts overlook out-of-sample restrictions when testing bounded rationality theories, yielding "false positives" and precluding proper identification and prediction.

Keywords: Bounded rationality, Limited datasets

JEL Classification: D01