On the functional form of temporal discounting: An optimized adaptive test

Daniel R. Cavagnaro, Gabriel J. Aranovich, Samuel McClure, Mark A. Pitt, Jay I. Myung

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

The tendency to discount the value of future rewards has become one of the best-studied constructs in the behavioral sciences. Although hyperbolic discounting remains the dominant quantitative characterization of this phenomenon, a variety of models have been proposed and consensus around the one that most accurately describes behavior has been elusive. To help bring some clarity to this issue, we propose an Adaptive Design Optimization (ADO) method for fitting and comparing models of temporal discounting. We then conduct an ADO experiment aimed at discriminating among six popular models of temporal discounting. Rather than supporting a single underlying model, our results show that each model is inadequate in some way to describe the full range of behavior exhibited across subjects. The precision of results provided by ADO further identify specific properties of models, such as accommodating both increasing and decreasing impatience, that are mandatory to describe temporal discounting broadly.

Original languageEnglish (US)
Pages (from-to)233-254
Number of pages22
JournalJournal of Risk and Uncertainty
Volume52
Issue number3
DOIs
StatePublished - Jun 1 2016

Keywords

  • Adaptive designs
  • Design optimization
  • Intertemporal choice
  • Model selection
  • Temporal discounting

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

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