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Long‐range subjective‐probability forecasts of slow‐motion variables in world politics: Exploring limits on expert judgment

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  • Philip E. Tetlock
  • Christopher Karvetski
  • Ville A. Satopää
  • Kevin Chen

Abstract

Skeptics see long‐range geopolitical forecasting as quixotic. A more nuanced view is that although predictability tends to decline over time, its rate of descent is variable. The current study gives geopolitical forecasters a sporting chance by focusing on slow‐motion variables with low base rates of change. Analyses of 5, 10, and 25‐year cumulative‐risk judgments made in 1988 and 1997 revealed: (a) specialists beat generalists at predicting nuclear proliferation but not shifting nation‐state boundaries; (b) some counterfactual interventions—for example, Iran gets the bomb before 2022—boosted experts’ edge but others—for example, nuclear war before 2022—eliminated it; (c) accuracy fell faster on topics where expertise conferred no edge in shorter‐range forecasts. To accelerate scientific progress, we propose adversarial collaborations in which clashing schools of thought negotiate Bayesian reputational bets on divisive issues and use Lakatosian scorecards to incentivize the honoring of bets.

Suggested Citation

  • Philip E. Tetlock & Christopher Karvetski & Ville A. Satopää & Kevin Chen, 2024. "Long‐range subjective‐probability forecasts of slow‐motion variables in world politics: Exploring limits on expert judgment," Futures & Foresight Science, John Wiley & Sons, vol. 6(1), March.
    • Handle: RePEc:wly:fufsci:v:6:y:2024:i:1:n:e157
    DOI: 10.1002/ffo2.157
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    References listed on IDEAS

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    1. Keynes, John Maynard, 1919. "The Economic Consequences of the Peace," History of Economic Thought Books, McMaster University Archive for the History of Economic Thought, number keynes1919.
    2. Franz Dietrich, 2010. "Bayesian group belief," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 35(4), pages 595-626, October.
    3. Anil Gaba & Dana G. Popescu & Zhi Chen, 2019. "Assessing Uncertainty from Point Forecasts," Management Science, INFORMS, vol. 65(1), pages 90-106, January.
    4. repec:cup:judgdm:v:11:y:2016:i:5:p:509-526 is not listed on IDEAS
    5. Alison Hubbard Ashton & Robert H. Ashton, 1985. "Aggregating Subjective Forecasts: Some Empirical Results," Management Science, INFORMS, vol. 31(12), pages 1499-1508, December.
    6. repec:cup:judgdm:v:12:y:2017:i:4:p:369-381 is not listed on IDEAS
    7. Carless, Travis S. & Redus, Kenneth & Dryden, Rachel, 2021. "Estimating nuclear proliferation and security risks in emerging markets using Bayesian Belief Networks," Energy Policy, Elsevier, vol. 159(C).
    8. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    9. Ville A. Satopää & Marat Salikhov & Philip E. Tetlock & Barbara Mellers, 2021. "Bias, Information, Noise: The BIN Model of Forecasting," Management Science, INFORMS, vol. 67(12), pages 7599-7618, December.
    10. Bas, Muhammet A. & Coe, Andrew J., 2016. "A Dynamic Theory of Nuclear Proliferation and Preventive War," International Organization, Cambridge University Press, vol. 70(4), pages 655-685, October.
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