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Time will tell: Recovering preferences when choices are noisy

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Time will tell: Recovering preferences when choices are noisy. / Alós-Ferrer, C.; Fehr, E.; Netzer, N.
In: Journal of Political Economy, Vol. 129, No. 6, 01.06.2021, p. 1828-1877.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Alós-Ferrer, C, Fehr, E & Netzer, N 2021, 'Time will tell: Recovering preferences when choices are noisy', Journal of Political Economy, vol. 129, no. 6, pp. 1828-1877. https://doi.org/10.1086/713732

APA

Alós-Ferrer, C., Fehr, E., & Netzer, N. (2021). Time will tell: Recovering preferences when choices are noisy. Journal of Political Economy, 129(6), 1828-1877. https://doi.org/10.1086/713732

Vancouver

Alós-Ferrer C, Fehr E, Netzer N. Time will tell: Recovering preferences when choices are noisy. Journal of Political Economy. 2021 Jun 1;129(6):1828-1877. Epub 2021 Apr 28. doi: 10.1086/713732

Author

Alós-Ferrer, C. ; Fehr, E. ; Netzer, N. / Time will tell: Recovering preferences when choices are noisy. In: Journal of Political Economy. 2021 ; Vol. 129, No. 6. pp. 1828-1877.

Bibtex

@article{a430b693575d4f5889d496e48e293fed,
title = "Time will tell: Recovering preferences when choices are noisy",
abstract = "When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.",
author = "C. Al{\'o}s-Ferrer and E. Fehr and N. Netzer",
year = "2021",
month = jun,
day = "1",
doi = "10.1086/713732",
language = "English",
volume = "129",
pages = "1828--1877",
journal = "Journal of Political Economy",
issn = "0022-3808",
publisher = "University of Chicago",
number = "6",

}

RIS

TY - JOUR

T1 - Time will tell: Recovering preferences when choices are noisy

AU - Alós-Ferrer, C.

AU - Fehr, E.

AU - Netzer, N.

PY - 2021/6/1

Y1 - 2021/6/1

N2 - When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.

AB - When choice is stochastic, revealed preference analysis often relies on random utility models. However, it is impossible to infer preferences without assumptions on the distribution of utility noise. We show that this difficulty can be overcome by using response time data. A simple condition on response time distributions ensures that choices reveal preferences without distributional assumptions. Standard models from economics and psychology generate data fulfilling this condition. Sharper results are obtained under symmetric or Fechnerian noise, where response times allow uncovering preferences or predicting choice probabilities out of sample. Application of our tools is simple and generates remarkable prediction accuracy.

U2 - 10.1086/713732

DO - 10.1086/713732

M3 - Journal article

VL - 129

SP - 1828

EP - 1877

JO - Journal of Political Economy

JF - Journal of Political Economy

SN - 0022-3808

IS - 6

ER -