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Measuring the Completeness of Economic Models

Author

Listed:
  • Drew Fudenberg
  • Jon Kleinberg
  • Annie Liang
  • Sendhil Mullainathan

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.

Suggested Citation

  • Drew Fudenberg & Jon Kleinberg & Annie Liang & Sendhil Mullainathan, 2022. "Measuring the Completeness of Economic Models," Journal of Political Economy, University of Chicago Press, vol. 130(4), pages 956-990.
    • Handle: RePEc:ucp:jpolec:doi:10.1086/718371
    DOI: 10.1086/718371
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    Cited by:

    1. Healy, Paul J. & Park, Hyoeun, 2023. "Model selection accuracy in behavioral game theory: A simulation," European Economic Review, Elsevier, vol. 152(C).
    2. Jian-Qiao Zhu & Joshua C. Peterson & Benjamin Enke & Thomas L. Griffiths, 2024. "Capturing the Complexity of Human Strategic Decision-Making with Machine Learning," Papers 2408.07865, arXiv.org.
    3. Caliari, Daniele, 2023. "Behavioural welfare analysis and revealed preference: Theory and experimental evidence," Discussion Papers, Research Unit: Economics of Change SP II 2023-303, WZB Berlin Social Science Center.
    4. Isaiah Andrews & Drew Fudenberg & Lihua Lei & Annie Liang & Chaofeng Wu, 2022. "The Transfer Performance of Economic Models," Papers 2202.04796, arXiv.org, revised Jul 2024.
    5. Heller, Yuval & Tubul, Itay, 2023. "Strategies in the repeated prisoner’s dilemma: A cluster analysis," MPRA Paper 117444, University Library of Munich, Germany.

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