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Projective Measurements in the Elicitation of Preferences
Last registered on November 08, 2019

Pre-Trial

Trial Information
General Information
Title
Projective Measurements in the Elicitation of Preferences
RCT ID
AEARCTR-0005005
Initial registration date
November 07, 2019
Last updated
November 08, 2019 10:10 AM EST
Location(s)

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Primary Investigator
Affiliation
DICE, University of Duesseldorf
Other Primary Investigator(s)
PI Affiliation
DICE, University of Duesseldorf
PI Affiliation
DICE, University of Duesseldorf
Additional Trial Information
Status
In development
Start date
2019-11-14
End date
2021-11-01
Secondary IDs
Abstract
Economic preferences are a fundamental aspect of economic modeling but their measurement presents a number of puzzles such as order and framing effects, and paradoxes like the lack of additivity. This study focuses on how to understand such behavioral patterns as a natural construct of the measurement process itself, and not as an undesirable anomaly. We propose a model that departs from standard probability theory by including projective measurements that do not require a certain boolean structure in the underlying space of events. Instead, we rely on a more general condition of orthomodularity.

In order to illustrate the working of this theoretical setting, we propose a stylized laboratory experiment with three treatments. In all treatments, subjects will first face the same choice task regarding time preferences and they will finish facing the same choice task (Lottery A vs. Lottery B) regarding risk preferences with a neutral frame. There will be no other intermediate steps in baseline Treatment 1. In addition, Treatments 2 and 3 will include an intermediate elicitation task. Subjects will also make a choice between a safe option and a lottery, framed as a gain or a loss: Safe+ vs. Lottery+ in Treatment 2 and Safe- vs. Lottery- in Treatment 3, respectively. We will collect additional control variables in a questionnaire at the end of the sessions.

Comparing the choices in the final task in Treatments 2 and 3 to the outcomes in the final task in Treatment 1 will allow us to identify a potential lack of additivity as a result of order effects. Comparing Treatment 2 to Treatment 3 will allow us to formally include framing as part of a projective measurement. Finally, we aim at assessing the validity of our theoretical framework as a descriptive tool for the measurement of individual preferences by producing a model that incorporates all these building blocks from the experiment in one unified setting, and testing it against the data.
External Link(s)
Registration Citation
Citation
Martínez Martínez, Ismael, Hannah Schildberg-Hörisch and Chi Trieu. 2019. "Projective Measurements in the Elicitation of Preferences." AEA RCT Registry. November 08. https://doi.org/10.1257/rct.5005-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2019-11-14
Intervention End Date
2020-07-31
Primary Outcomes
Primary Outcomes (end points)
Fraction of subjects that select Lottery A or Lottery B in the last measurement (neutral frame) of the three treatments.
Primary Outcomes (explanation)
Comparing the choices in the final task in Treatments 2 and 3 to the choices in the final task in Treatment 1 will allow us to identify a potential lack of additivity as a result of order effects. Comparing choices in Treatment 2 to those in Treatment 3 will allow us to formally include framing as part of a projective measurement.
Secondary Outcomes
Secondary Outcomes (end points)
Fraction of subjects that select Lottery- or Lottery+ instead of the Safe options in the intermediate measurements of the two framed Treatments 2 and 3.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We propose a stylized laboratory experiment with three treatments. In all treatments, subjects will first face the same choice task regarding time preferences and they will finish facing the same choice task (Lottery A vs. Lottery B) regarding risk preferences with a neutral frame. There will be no other intermediate steps in baseline Treatment 1. In addition, Treatments 2 and 3 will include an intermediate elicitation task. Subjects will also make a choice between a safe option and a lottery, framed as a gain or a loss: Safe+ vs. Lottery+ in Treatment 2 and Safe- vs. Lottery- in Treatment 3, respectively. We will collect additional control variables in a questionnaire at the end of the sessions.
Experimental Design Details
Not available
Randomization Method
Invitation of subjects with standard ORSEE procedures. When arriving in the lab, participants will select one computer randomly, by drawing a cabin number blindly. Treatments will also be assigned to each computer randomly at the beginning of the session.
Randomization Unit
Each subject will be one observation.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
We aim at a balanced sample with at least 60–80 subjects per treatment.
Sample size: planned number of observations
We aim at a balanced sample with at least 60–80 subjects per treatment.
Sample size (or number of clusters) by treatment arms
We aim at a balanced sample with at least 60–80 subjects per treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number