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Prediction: The Long and the Short of It

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  • Antony Millner
  • Daniel Heyen

Abstract

Commentators often lament forecasters' inability to provide precise predictions of the long-run behavior of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. So what is the relative importance of short- and long-run predictability? We study this question in a model of rational dynamic adjustment to a changing environment. Even if adjustment costs, discount factors, and long-run uncertainty are large, short-run predictability can be much more important than long-run predictability.

Suggested Citation

  • Antony Millner & Daniel Heyen, 2021. "Prediction: The Long and the Short of It," American Economic Journal: Microeconomics, American Economic Association, vol. 13(1), pages 374-398, February.
  • Handle: RePEc:aea:aejmic:v:13:y:2021:i:1:p:374-98
    DOI: 10.1257/mic.20180240
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    References listed on IDEAS

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    1. Olivier Jean Blanchard & Stanley Fischer, 1989. "Lectures on Macroeconomics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262022834, April.
    2. Benveniste, L M & Scheinkman, J A, 1979. "On the Differentiability of the Value Function in Dynamic Models of Economics," Econometrica, Econometric Society, vol. 47(3), pages 727-732, May.
    3. Merton, Robert C., 1971. "Optimum consumption and portfolio rules in a continuous-time model," Journal of Economic Theory, Elsevier, vol. 3(4), pages 373-413, December.
    4. Richard M. Adams & Stephen Polasky, 1998. "The Value of El Niño Forecasts in the Management of Salmon: A Stochastic Dynamic Assessment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 765-777.
    5. Gollier, Christian & Jullien, Bruno & Treich, Nicolas, 2000. "Scientific progress and irreversibility: an economic interpretation of the 'Precautionary Principle'," Journal of Public Economics, Elsevier, vol. 75(2), pages 229-253, February.
    6. Kenneth J. Arrow & Anthony C. Fisher, 1974. "Environmental Preservation, Uncertainty, and Irreversibility," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 88(2), pages 312-319.
    7. Epstein, Larry G, 1980. "Decision Making and the Temporal Resolution of Uncertainty," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 269-283, June.
    8. Granger, Clive W.J. & Jeon, Yongil, 2007. "Long-term forecasting and evaluation," International Journal of Forecasting, Elsevier, vol. 23(4), pages 539-551.
    9. Lars Ljungqvist & Thomas J. Sargent, 2004. "Recursive Macroeconomic Theory, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 026212274x, April.
    10. Sargent, Thomas J, 1978. "Estimation of Dynamic Labor Demand Schedules under Rational Expectations," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 1009-1044, December.
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    Cited by:

    1. Linsenmeier, Manuel & Shrader, Jeffrey G., 2023. "Global inequalities in weather forecasts," SocArXiv 7e2jf, Center for Open Science.
    2. Derek Lemoine & Sarah Kapnick, 2024. "Financial markets value skillful forecasts of seasonal climate," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    3. Anand, Vaibhav, 2022. "The Value of Forecast Improvements: Evidence from Advisory Lead Times and Vehicle Crashes," MPRA Paper 114491, University Library of Munich, Germany.
    4. Juha-Pekka Jäpölä & Sophie Schoubroeck & Steven Passel, 2024. "Preferences on funding humanitarian aid and disaster management under climatic losses and damages: A multinational Delphi panel," Climatic Change, Springer, vol. 177(7), pages 1-21, July.

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    More about this item

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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