The emergence of "fifty-fifty" probability judgments through Bayesian updating under ambiguity
نویسنده
چکیده
This paper explains the empirical phenomenon of persistent “fifty-fifty”probability judgments through a model of Bayesian updating under ambiguity. To this purpose I characterize an announced probability judgment as a Bayesian estimate given as the solution to a Choquet expected utility maximization problem with respect to a neo-additive capacity that has been updated in accordance with the Generalized Bayesian update rule. Only for the non-generic case, in which this capacity degenerates to an additive probability measure, the agent will learn the event’s true probability if the number of i.i.d. data observations gets large. In contrast, for the generic case in which the capacity is not additive, the agent’s announced probability judgment becomes a persistent “fifty-fifty”probability judgment after finitely many observations.
منابع مشابه
Learning Under Compound Risk vs . Learning Under Ambiguity - An Experiment . 1
We design and conduct an economic experiment to investigate the learning process of the agents under compound risk and under ambiguity. We gather data for subjects choosing between lotteries involving risky and ambiguous urns. Decisions are made in conjunction with a sequence of random draws with replacement, allowing us to estimate the beliefs of the agents at different moments in time. For ea...
متن کاملSubjective probability, confidence, and Bayesian updating
I derive a unique subjective probabilistic belief p and Bayesian updating for this belief from ambiguity averse preferences. To do so, I assume an exogenous information set ∆ of possible probabilistic scenarios on the state space S. Every uncertain prospect f is evaluated via a mixture of the unique subjective belief p with the least favorable scenario for f in the set ∆. The weight of p in thi...
متن کاملDo Bayesians Learn Their Way Out of Ambiguity?
In standard models of Bayesian learning agents reduce their uncertainty about an events true probability because their consistent estimator concentrates almost surely around this probabilitys true value as the number of observations becomes large. This paper takes the empirically observed violations of Savages (1954) sure thing principle seriously and asks whether Bayesian learners with ambi...
متن کاملRevealed Ambiguity and Its Consequences: Updating
We study the updating of beliefs under ambiguity for invariant biseparable preferences. In particular, we show that a natural form of dynamic consistency characterizes the Bayesian updating of these beliefs. JEL classification: D81
متن کاملWhat number is "fifty-fifty"?: redistributing excessive 50% responses in elicited probabilities.
Studies using open-ended response modes to elicit probabilistic beliefs have sometimes found an elevated frequency (or blip) at 50 in their response distributions. Our previous research suggests that this is caused by intrusion of the phrase "fifty-fifty," which represents epistemic uncertainty, rather than a true numeric probability of 50%. Such inappropriate responses pose a problem for decis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Fuzzy Sets and Systems
دوره 223 شماره
صفحات -
تاریخ انتشار 2013