What if you are not Bayesian? The consequences for decisions involving risk

Paul Goodwin, Dilek Onkal, Herman O. Stekler

Research output: Contribution to journalArticle

Abstract

Many studies have examined the extent to which individuals’ probability judgments depart from Bayes’ theorem when revising probability estimates in the light of new information. Generally, these studies have not considered the implications of such departures for decisions involving risk. We identify when such departures will occur in two common types of decisions. We then report on two experiments where people were asked to revise their own prior probabilities of a forthcoming economic recession in the light of new information. When the reliability of the new information was independent of the state of nature, people tended to overreact to it if their prior probability was low and underreact if it was high. When it was not independent, they tended to display conservatism. We identify the circumstances where discrepancies in decisions arising from a failure to use Bayes’ theorem were most likely to occur in the decision context we examined
LanguageEnglish
Article numberEOR_14705
Pages238-246
JournalEuropean Journal of Operational Research
Volume266
Issue number1
Early online date22 Sep 2017
DOIs
StatusPublished - 1 Apr 2018

Fingerprint

Bayes' Formula
Prior Probability
Discrepancy
Likely
Economics
Estimate
Experiment
Experiments
Bayes' theorem
Context
Judgment
Recession
Probability judgment
Nature
Conservatism

Keywords

  • decision processes
  • Bayes’ theorem
  • judgmental biases
  • risk

Cite this

What if you are not Bayesian? The consequences for decisions involving risk. / Goodwin, Paul; Onkal, Dilek; Stekler, Herman O.

In: European Journal of Operational Research, Vol. 266, No. 1, EOR_14705, 01.04.2018, p. 238-246.

Research output: Contribution to journalArticle

@article{5a9049d23efe464b89382e6a61785dbb,
title = "What if you are not Bayesian? The consequences for decisions involving risk",
abstract = "Many studies have examined the extent to which individuals’ probability judgments depart from Bayes’ theorem when revising probability estimates in the light of new information. Generally, these studies have not considered the implications of such departures for decisions involving risk. We identify when such departures will occur in two common types of decisions. We then report on two experiments where people were asked to revise their own prior probabilities of a forthcoming economic recession in the light of new information. When the reliability of the new information was independent of the state of nature, people tended to overreact to it if their prior probability was low and underreact if it was high. When it was not independent, they tended to display conservatism. We identify the circumstances where discrepancies in decisions arising from a failure to use Bayes’ theorem were most likely to occur in the decision context we examined",
keywords = "decision processes, Bayes’ theorem, judgmental biases, risk",
author = "Paul Goodwin and Dilek Onkal and Stekler, {Herman O.}",
year = "2018",
month = "4",
day = "1",
doi = "10.1016/j.ejor.2017.09.027",
language = "English",
volume = "266",
pages = "238--246",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - What if you are not Bayesian? The consequences for decisions involving risk

AU - Goodwin,Paul

AU - Onkal,Dilek

AU - Stekler,Herman O.

PY - 2018/4/1

Y1 - 2018/4/1

N2 - Many studies have examined the extent to which individuals’ probability judgments depart from Bayes’ theorem when revising probability estimates in the light of new information. Generally, these studies have not considered the implications of such departures for decisions involving risk. We identify when such departures will occur in two common types of decisions. We then report on two experiments where people were asked to revise their own prior probabilities of a forthcoming economic recession in the light of new information. When the reliability of the new information was independent of the state of nature, people tended to overreact to it if their prior probability was low and underreact if it was high. When it was not independent, they tended to display conservatism. We identify the circumstances where discrepancies in decisions arising from a failure to use Bayes’ theorem were most likely to occur in the decision context we examined

AB - Many studies have examined the extent to which individuals’ probability judgments depart from Bayes’ theorem when revising probability estimates in the light of new information. Generally, these studies have not considered the implications of such departures for decisions involving risk. We identify when such departures will occur in two common types of decisions. We then report on two experiments where people were asked to revise their own prior probabilities of a forthcoming economic recession in the light of new information. When the reliability of the new information was independent of the state of nature, people tended to overreact to it if their prior probability was low and underreact if it was high. When it was not independent, they tended to display conservatism. We identify the circumstances where discrepancies in decisions arising from a failure to use Bayes’ theorem were most likely to occur in the decision context we examined

KW - decision processes

KW - Bayes’ theorem

KW - judgmental biases

KW - risk

UR - http://dx.doi.org/10.1016/j.ejor.2017.09.027

U2 - 10.1016/j.ejor.2017.09.027

DO - 10.1016/j.ejor.2017.09.027

M3 - Article

VL - 266

SP - 238

EP - 246

JO - European Journal of Operational Research

T2 - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 1

M1 - EOR_14705

ER -