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Valuing predictability

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  • Antony Millner
  • Daniel Heyen

Abstract

How important is it to be able to predict the distant future? The authors of this paper study this question in a model of an agent who operates in a non-stationary stochastic environment. Payoffs depend on how well adapted activities are to current conditions, and activities may be adjusted to account for anticipated environmental changes, at a cost. The authors compute the value of prediction systems, which produce forecasts of the future with a given profile of accuracy as a function of lead time in every period. This allows them to quantify the importance of predictive accuracy at each lead time. Even if adjustment costs, discount factors and long-run uncertainty are large, short-run predictability is often more important than long-run predictability. ‘If you have to forecast, forecast often.’ Edgar R. Fiedler, The Three Rs of Economic Forecasting: Irrational, Irrelevant and Irreverent, 1977

Suggested Citation

  • Antony Millner & Daniel Heyen, 2017. "Valuing predictability," GRI Working Papers 260, Grantham Research Institute on Climate Change and the Environment.
    • Handle: RePEc:lsg:lsgwps:wp260
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    References listed on IDEAS

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    5. Kenneth J. Arrow & Anthony C. Fisher, 1974. "Environmental Preservation, Uncertainty, and Irreversibility," Palgrave Macmillan Books, in: Chennat Gopalakrishnan (ed.), Classic Papers in Natural Resource Economics, chapter 4, pages 76-84, Palgrave Macmillan.
    6. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
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