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Field
Abstract
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Before
Bayesian Updating is the dominant theory of learning in economics and other disciplines. According to this theory, decision-makers have prior beliefs which they update according to Bayes rule after receiving new information. The theory is silent about how individuals react to receiving information that the subjects have not observed previously and, hence, which they may deem impossible. Recent theoretical literature has put forth a possible mechanism, called “reverse Bayesianism”, which decision-makers may use to react to unforeseen events. However, these and other possible mechanisms have not been experimentally tested. The project will fill this large gap in the literature by running a series of economic experiments.
We started to explore this matter in a previous experiment (AEARCTR-0003030) using Amazon MTurk to obtain some preliminary evidence in understanding decision-making behaviour in such situations. Given these findings, we fine-tuned our experimental design to implement in a lab setting. However, we found a large variation in the elicited Willingness to Accept with several unrealistically high and unrealistically low values. This could possibly be because MTurk subjects, notoriously less attentive than laboratory subjects, did not fully understand our methods of elicitation. A further important concern is that using a virtual urn instead of a real one may have induced the subjects to question the randomness of the draws they observed. This laboratory experiment is set to overcome both of the above concerns.
A summary description of our design follows. First, a randomly chosen subject will be asked to repeatedly draw balls from an urn in front of all other subjects in each experimental session. This will allow subjects to form beliefs about the proportion of different prizes in the urn. Subsequently, subjects’ beliefs about the composition of the urn and their willingness to accept for lotteries rewarding them according to draws out of urn are elicited. At this point, a new urn with several balls representing one new prize is presented and the subject responsible to make draws is asked to draw from the new urn. Subsequently, the contents of the new urn are poured into the old one (with the explicit note that the new urn does not contain any previously observed prizes) and subjects are told that they will be paid according to the draws from the resulting combined urn. Finally, we elicit subjects’ willingness to accept for a lottery rewarding them according to a draw out of the urn again (based on observations of drawings from the old urn and the subsequent draw from the combined urn) as well as their perceived likelihoods of each prize.
We have two "surprise" treatments and two control treatments. In the "good surprise" treatment the new prize will be higher than the one observed in the "bad surprise" treatment. In the control treatments, we reveal ex-ante the urn compositions.
This design will allow us to explore how adding an unexpected prize changes subjects’ beliefs about the composition of the urn. We will in particular address the following questions. Do individuals naturally expect events that were previously considered impossible? Do individuals learn to expect what is previously considered impossible? How individuals update their beliefs about the urn composition after an unexpected event takes place? Do individuals attach a positive or negative value to the consequences of such events?
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After
Bayesian Updating is the dominant theory of learning in economics and other disciplines. According to this theory, decision-makers have prior beliefs which they update according to Bayes rule after receiving new information. The theory is silent about how individuals react to receiving information that the subjects have not observed previously and, hence, which they may deem impossible. Recent theoretical literature has put forth a possible mechanism, called “reverse Bayesianism”, which decision-makers may use to react to unforeseen events. However, these and other possible mechanisms have not been experimentally tested. The project will fill this large gap in the literature by running a series of economic experiments.
A summary description of our design follows. First, a randomly chosen subject will be asked to repeatedly draw balls from an urn in front of all other subjects in each experimental session. This will allow subjects to form beliefs about the proportion of different prizes in the urn. Subsequently, subjects’ beliefs about the composition of the urn and their willingness to accept for lotteries rewarding them according to draws out of urn are elicited. At this point, a new urn with several balls representing one new prize is presented and the subject responsible to make draws is asked to draw from the new urn. Subsequently, the contents of the new urn are poured into the old one (with the explicit note that the new urn does not contain any previously observed prizes) and subjects are told that they will be paid according to the draws from the resulting combined urn. Finally, we elicit subjects’ willingness to accept for a lottery rewarding them according to a draw out of the urn again (based on observations of drawings from the old urn and the subsequent draw from the combined urn) as well as their perceived likelihoods of each prize.
We have two "surprise" treatments and two control treatments. In the "good surprise" treatment the new prize will be higher than the one observed in the "bad surprise" treatment. In the control treatments, we reveal ex-ante the urn compositions.
This design will allow us to explore how adding an unexpected prize changes subjects’ beliefs about the composition of the urn. We will in particular address the following questions. Do individuals naturally expect events that were previously considered impossible? Do individuals learn to expect what is previously considered impossible? How individuals update their beliefs about the urn composition after an unexpected event takes place? Do individuals attach a positive or negative value to the consequences of such events?
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