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

Daniel R. Cavagnaro (), Gabriel J. Aranovich, Samuel M. McClure, Mark A. Pitt and Jay I. Myung
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Daniel R. Cavagnaro: California State University Fullerton
Gabriel J. Aranovich: University of California, San Francisco
Samuel M. McClure: Arizona State University
Mark A. Pitt: The Ohio State University
Jay I. Myung: The Ohio State University

Journal of Risk and Uncertainty, 2016, vol. 52, issue 3, No 3, 233-254

Abstract: 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.

Keywords: Temporal discounting; Intertemporal choice; Adaptive designs; Design optimization; Model selection; C91; C52; D90 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s11166-016-9242-y

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