Eliciting interval beliefs: An experimental study

Ronald Peeters, L. Wolk

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this paper we study the interval scoring rule as a mechanism to elicit subjective beliefs
under varying degrees of uncertainty. In our experiment, subjects forecast the termination
time of a time series to be generated from a given but unknown stochastic process. Subjects
gradually learn more about the underlying process over time and hence the true distribution
over termination times. We conduct two treatments, one with a high and one with a low volatility
process. We find that elicited intervals are better when subjects are facing a low volatility
process. In this treatment, participants learn to position their intervals almost optimally
over the course of the experiment. This is in contrast with the high volatility treatment, where
subjects, over the course of the experiment, learn to optimize the location of their intervals
but fail to provide the optimal length.
LanguageEnglish
Article numbere0175163
Pages1-15
Number of pages15
JournalPLoS ONE
Volume12
Issue number4
DOIs
Publication statusPublished - 2017

Fingerprint

stochastic processes
time series analysis
uncertainty
Stochastic Processes
Volatilization
Experiments
Random processes
Uncertainty
Time series

Cite this

Peeters, Ronald ; Wolk, L. / Eliciting interval beliefs: An experimental study. In: PLoS ONE. 2017 ; Vol. 12, No. 4. pp. 1-15.
@article{c11047aa0041406798cd4683f5e7df84,
title = "Eliciting interval beliefs: An experimental study",
abstract = "In this paper we study the interval scoring rule as a mechanism to elicit subjective beliefsunder varying degrees of uncertainty. In our experiment, subjects forecast the terminationtime of a time series to be generated from a given but unknown stochastic process. Subjectsgradually learn more about the underlying process over time and hence the true distributionover termination times. We conduct two treatments, one with a high and one with a low volatilityprocess. We find that elicited intervals are better when subjects are facing a low volatilityprocess. In this treatment, participants learn to position their intervals almost optimallyover the course of the experiment. This is in contrast with the high volatility treatment, wheresubjects, over the course of the experiment, learn to optimize the location of their intervalsbut fail to provide the optimal length.",
author = "Ronald Peeters and L. Wolk",
year = "2017",
doi = "10.1371/journal.pone.0175163",
language = "English",
volume = "12",
pages = "1--15",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

Eliciting interval beliefs: An experimental study. / Peeters, Ronald; Wolk, L.

In: PLoS ONE, Vol. 12, No. 4, e0175163, 2017, p. 1-15.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Eliciting interval beliefs: An experimental study

AU - Peeters, Ronald

AU - Wolk, L.

PY - 2017

Y1 - 2017

N2 - In this paper we study the interval scoring rule as a mechanism to elicit subjective beliefsunder varying degrees of uncertainty. In our experiment, subjects forecast the terminationtime of a time series to be generated from a given but unknown stochastic process. Subjectsgradually learn more about the underlying process over time and hence the true distributionover termination times. We conduct two treatments, one with a high and one with a low volatilityprocess. We find that elicited intervals are better when subjects are facing a low volatilityprocess. In this treatment, participants learn to position their intervals almost optimallyover the course of the experiment. This is in contrast with the high volatility treatment, wheresubjects, over the course of the experiment, learn to optimize the location of their intervalsbut fail to provide the optimal length.

AB - In this paper we study the interval scoring rule as a mechanism to elicit subjective beliefsunder varying degrees of uncertainty. In our experiment, subjects forecast the terminationtime of a time series to be generated from a given but unknown stochastic process. Subjectsgradually learn more about the underlying process over time and hence the true distributionover termination times. We conduct two treatments, one with a high and one with a low volatilityprocess. We find that elicited intervals are better when subjects are facing a low volatilityprocess. In this treatment, participants learn to position their intervals almost optimallyover the course of the experiment. This is in contrast with the high volatility treatment, wheresubjects, over the course of the experiment, learn to optimize the location of their intervalsbut fail to provide the optimal length.

U2 - 10.1371/journal.pone.0175163

DO - 10.1371/journal.pone.0175163

M3 - Article

VL - 12

SP - 1

EP - 15

JO - PLoS ONE

T2 - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 4

M1 - e0175163

ER -