From Wald to Savage: <i>Homo Economicus</i> Becomes a Bayesian Statistician

Giocoli, Nicola

doi:10.1002/jhbs.21579

Cited by 19 publications

(2 citation statements)

References 58 publications

(89 reference statements)

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“…However, Bayesian inference might be understood as the general process of using new information to revise evaluations of likelihoods of events with known prior base rates ( Brase and Hill, 2015 ). In particular, this describes Bayesian analysis of decision problems incorporated in subjective expected utility theory (SEUT, Savage, 1954 ; Giocoli, 2013 ; Karni, 2013 ). According to this perspective, a Bayesian decision-maker’s subjective beliefs are expressed with probabilities which are updated in line with Bayes rule as new information is gathered.…”

Section: Discussionmentioning

confidence: 99%

Bayesian probability estimates are not necessary to make choices satisfying Bayes’ rule in elementary situations

et al. 2015

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This paper has two aims. First, we investigate how often people make choices conforming to Bayes’ rule when natural sampling is applied. Second, we show that using Bayes’ rule is not necessary to make choices satisfying Bayes’ rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes’ rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes’ rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes’ rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Bayes’ rule to apply. It does not require inversion of conditions [transforming P(H) and P(D|H) into P(H|D)] when computing chances. Study 3 examined the efficiency of three fallacious heuristics (pre-Bayesian, representativeness, and evidence-only) in producing choices concordant with Bayes’ rule. Computer-simulated scenarios revealed that the heuristics produced correct choices reasonably often under specific base rates and likelihood ratios. Summing up we conclude that natural sampling results in most choices conforming to Bayes’ rule. However, people tend to replace Bayes’ rule with simpler methods, and even use of fallacious heuristics may be satisfactorily efficient.

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Section: Discussionmentioning

confidence: 99%

Bayesian probability estimates are not necessary to make choices satisfying Bayes’ rule in elementary situations

et al. 2015

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“…The development of Bayesian decision making in the 1950s has been a major achievement both for theory and for practice (Raiffa & Schlaifer, 1961; Savage, 1951, 1972; Wald, 1950a, 1950b) in deep interaction with management science (Erickson et al, 2013; Giocoli, 2013). In theory, utility functions for probabilistic lotteries allowed to compare decision alternatives facing uncertainties; in addition, the introduction of—so called subjective— prior probabilities of uncertain events made possible to compute, through Bayes's conditional probabilities theorem, the value of a new information about these events.…”

Section: Introductionmentioning

confidence: 99%