Scholarly Comments on Academic Economics

Reply to “The Limitations of Growth-Optimal Approaches to Decision Making Under Uncertainty”

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Abstract

In an article appearing concurrently with the present one, Matthew Ford and John Kay put forward their understanding of a decision theory which emerges in ergodicity economics. Their understanding leads them to believe that ergodicity economics evades the core problem of decisions under uncertainty and operates solely in a regime where there is no measurable uncertainty. If this were the case, then the authors’ critical stance would be justified and, as the authors point out, the decision theory would yield only trivial results, identical to a flavor of expected-utility theory. Here we clarify that the critique is based on a theoretical misunderstanding, and that uncertainty—quantified in any reasonable way—is large in the regime where the model operates. Our resolution explains the success of recent laboratory experiments, where ergodicity economics makes predictions different from expected-utility theory, contrary to the claim of equivalence by Ford and Kay. Also, a state of the world is identified where ergodicity economics outperforms expected-utility theory empirically.

This article is a response to The Limitations of Growth-Optimal Approaches to Decision Making Under Uncertainty by Matthew C. Ford and John A. Kay (EJW, September 2023).

Codes to reproduce all data and figures are available here and are archived at Zenodo.

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Volume (Issue)
Pages
335–348
Published
JEL classification
C01, C11, C12, C22, C52, C61, C73, C91, D01, D81, D84, G11
Keywords
Ergodicity economics, stochastic process, random variable, expected utility theory, experiments, random walks
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2,233 article downloads
4,213 complete issue downloads
Total: 6,446

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