Elicitation of preferences and beliefs in light of new information

Last registered on July 21, 2018

Pre-Trial

Trial Information

General Information

Title
Elicitation of preferences and beliefs in light of new information
RCT ID
AEARCTR-0003030
Initial registration date
June 26, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 27, 2018, 1:29 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
July 21, 2018, 4:02 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region

Primary Investigator

Affiliation
University of Glasgow, Adam Smith Business School

Other Primary Investigator(s)

PI Affiliation
University of Heidelberg
PI Affiliation
Warwick Business School

Additional Trial Information

Status
Completed
Start date
2018-06-27
End date
2018-07-20
Secondary IDs
Abstract
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. First, the experimental subjects will be asked to virtually and repeatedly draw balls from an urn. This will allow them to form beliefs about the proportion of different prizes in the urn. Subsequently, they will repeatedly bet on various prizes drawn from the urn. The subjects’ beliefs about the composition of the urn will also be elicited. The composition of the urn will be changed midpoint during this sequence (by adding a new prize that wasn’t originally present in the urn) so that the experimental subjects subsequently observe events that couldn’t be predicted given their prior information. We will explore how this will change their betting behaviour and their beliefs about the composition of the urn. We will also address the following questions. Do individuals naturally expect events that were previously considered impossible? Do individuals learn to expect what is previously considered impossible? Do individuals attach a positive or negative value to the consequences of such events?

External Link(s)

Registration Citation

Citation
, , Eugenio Proto and Andis Sofianos. 2018. "Elicitation of preferences and beliefs in light of new information." AEA RCT Registry. July 21. https://doi.org/10.1257/rct.3030
Former Citation
, , Eugenio Proto and Andis Sofianos. 2018. "Elicitation of preferences and beliefs in light of new information." AEA RCT Registry. July 21. https://www.socialscienceregistry.org/trials/3030/history/32003
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2018-06-27
Intervention End Date
2018-07-20

Primary Outcomes

Primary Outcomes (end points)
(i) The subjective probability of an impossible event (or prize) in the original urn for treated group
(ii) The subjective probability of an impossible event (or prize) in the updated urn for treated group
(iii) The ratio between subjective probabilities of the prizes 20 and 100 respectively in the original urn for the treated group
(iv) The ratio between subjective probabilities of the prizes 20 and 100 respectively in the updated urn for the treated group
(v) The ratio between subjective probabilities of the prizes 20 and 100 respectively in the urn for the control group
(vi) The willingness to accept to sell the original lottery in the treated group
(vii) The willingness to accept to sell the updated lottery in the treated group
(viii) The willingness to accept to sell the lottery in the control group
Primary Outcomes (explanation)
The subjective probability of the impossible event (or prize) is calculated as 1 minus the subjective probabilities of the observed prizes: 20 and 100 in the original urn; 20, 100 and 200 or 10 (according to whether the treatment is "good-surprise" or "bad-surprise"), in the updated urn.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We design an experiment where subjects are asked to report subjective probabilities of prizes and the certainty equivalent values of lotteries determined by drawing prizes from a virtual urn, from which they observe several realisations prior to making their decisions. These elicitations are incentivised by using methods similar to Becker-DeGroot-Marschak (BDM) to report the subjective probability of prizes and their willingness to accept to sell the lotteries (see the enclosed documents for more details).

There are two main treatments:

In the control treatment: Subjects observe 20 draws from a urn containing 50 prizes of 100 experimental units and 50 prizes of 20 Experimental units and they are explicitly told that they urn contains two and only two prizes. They need to report the subjective probabilities of the two prizes and their willingness to accept for selling the lottery determined by a random draw from the urn.

In the surprise treatment: Subjects observe 20 draws from a urn -- that we call "original urn" containing 50 prizes of 100 experimental units and 50 prizes of 20 Experimental units. They are asked to report the subjective probabilities of the two prizes and their willingness to accept for selling the lottery determined by a random draw from the original urn. Then we add to the original urn -- that we call now "updated" urn -- 50 prizes of E experimental units and we ask subjects to observe a new draw from the updated urn. This is a non random draw featuring the prize E. Subjects after observing E, and without other information are asked again to report the subjective probabilities of the two prizes and their willingness to accept for selling the lottery determined by a random draw from the modified urn.

In the surprise treatment we further distinguish two different sub-treatments one where the prizes added is E = 200 units - the good surprise treatment; and the other where the prizes added is E = 10 units - the bad surprise treatment.

We plan to run this experiment online by using the Amazon MTurk platform
Experimental Design Details
Randomization Method
By a computer, when subjects start their trial, the computer randomly allocates them to one of three different groups (1 control treatment + 2 surprise treatments)
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Online version: about 1200 Mturk Users

Sample size: planned number of observations
Online version = about 1200 valid Mturk Users , this number excludes subjects that will not answer or not answer correctly the 1st Attention test (see the enclosed documents describing the experiment for more details). In total we expect an attrition of about 15%
Sample size (or number of clusters) by treatment arms
Online version: about 400 Mturk Users in the control group, 400 Mturk Users in the treatment with E=200, 400 Mturk Users in the treatment with E=10
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Warwick Humanities and Social Sciences Research Ethics Committee
IRB Approval Date
2018-03-27
IRB Approval Number
94/17-18

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
July 16, 2018, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
July 10, 2018, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1186
Final Sample Size (or Number of Clusters) by Treatment Arms
389 control treatment, 405 "bad-surprise" treatment, 392 "good-surprise" treatment
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials