Measuring the Completeness of Economic Models

Drew Fudenberg · Jon Michael Kleinberg · Annie Liang · Sendhil Mullainathan

53 citations0/0 files storedJournal of Political Economy

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Decision-Making and Behavioral Economics Economic Theory and Institutions Experimental Behavioral Economics Studies

Abstract

Economic models are evaluated by testing the correctness of their predictions. We suggest an additional measure, “completeness”: the fraction of the predictable variation in the data that the model captures. We calculate the completeness of prominent models in three problems from experimental economics: assigning certainty equivalents to lotteries, predicting initial play in games, and predicting human generation of random sequences. The completeness measure reveals new insights about these models, including how much room there is for improving their predictions.

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References

1992Advances in prospect theory: Cumulative representation of uncertainty 2007Strictly Proper Scoring Rules, Prediction, and Estimation 1971Belief in the law of small numbers.1998A model of investor sentiment1We are grateful to the NSF for financial support, and to Oliver Blanchard, Alon Brav, John Campbell (a referee), John Cochrane, Edward Glaeser, J.B. Heaton, Danny Kahneman, David Laibson, Owen Lamont, Drazen Prelec, Jay Ritter (a referee), Ken Singleton, Dick Thaler, an anonymous referee, and the editor, Bill Schwert, for comments.1 2004A Cognitive Hierarchy Model of Games 1995On Players′ Models of Other Players: Theory and Experimental Evidence 1994Experimental evidence on players' models of other players 2002Inference by Believers in the Law of Small Numbers

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