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A Maximum Likelihood Approach to Combining Forecasts

Author

Listed:
  • Levy, Gilat

    (Department of Economics, London School of Economiocs)

  • Razin, Ronny

    (Department of Economics, London School of Economiocs)

Abstract

We model an individual who wants to learn about a state of the world. The individual has a prior belief, and has data which consists of multiple forecasts about the state of the world. Our key assumption is that the decision maker identifies explanations that could have generated this data and among these focuses on the ones that maximise the likelihood of observing the data. The decision maker then bases her final prediction about the state on one of these maximum likelihood explanations. We show that in all the maximum likelihood explanations, moderate forecasts are just statistical derivatives of extreme ones. Therefore, the decision maker will base her final prediction only on the information conveyed in the relatively extreme forecasts. We show that this approach to combining forecasts leads to a unique prediction and a simple and dynamically consistent way of aggregating opinions.

Suggested Citation

  • Levy, Gilat & Razin, Ronny, 2021. "A Maximum Likelihood Approach to Combining Forecasts," Theoretical Economics, Econometric Society, vol. 16(1), January.
    • Handle: RePEc:the:publsh:3876
    as

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    File URL: http://econtheory.org/ojs/index.php/te/article/viewFile/20210049/29614/844
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    References listed on IDEAS

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    1. Daniel J. Benjamin & James O. Berger & Magnus Johannesson & Brian A. Nosek & E.-J. Wagenmakers & Richard Berk & Kenneth A. Bollen & Björn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Chr, 2018. "Redefine statistical significance," Nature Human Behaviour, Nature, vol. 2(1), pages 6-10, January.
      • Daniel Benjamin & James Berger & Magnus Johannesson & Brian Nosek & E. Wagenmakers & Richard Berk & Kenneth Bollen & Bjorn Brembs & Lawrence Brown & Colin Camerer & David Cesarini & Christopher Chambe, 2017. "Redefine Statistical Significance," Artefactual Field Experiments 00612, The Field Experiments Website.
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    Cited by:

    1. Marcos R. Fernandes, 2024. "Combining Combined Forecasts: a Network Approach," Papers 2406.13749, arXiv.org, revised Apr 2026.
    2. Kfir Eliaz & Simone Galperti & Ran Spiegler, 2022. "False Narratives and Political Mobilization," Papers 2206.12621, arXiv.org.
    3. Olivier Compte, 2023. "Belief formation and the persistence of biased beliefs," Papers 2310.08466, arXiv.org.
    4. Chiara Aina & Florian H. Schneider, 2025. "Weighting Competing Models," CEBI working paper series 25-04, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    5. Deniz Kattwinkel & Alexander Winter, 2024. "Optimal Decision Mechanisms for Committees: Acquitting the Guilty," Papers 2407.07293, arXiv.org, revised Jan 2026.

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    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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