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Decision-making Procedures, Rational Choice and Welfare

Last registered on March 01, 2020

Pre-Trial

Trial Information

General Information

Title
Decision-making Process, Rational Choice and Welfare
RCT ID
AEARCTR-0005220
Initial registration date
January 15, 2020

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
January 15, 2020, 11:28 AM EST

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

Last updated
March 01, 2020, 4:13 PM EST

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

Locations

Region

Primary Investigator

Affiliation
University of Kent

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2020-03-06
End date
2020-03-13
Secondary IDs
Abstract
This paper studies the impact of decision-making processes on individuals’ rationality and welfare. We theoretically and experimentally study a specific decision-making process, sequential elimination in which a decision-maker has to sequentially eliminate options that are least preferred in the decision problem, one by one until only one option remains. First, we provide a necessary and sufficient condition that sequential elimination results in consistent choice while direct decision-making may not. Then we experiment to examine the treatment effect of sequential elimination on the choice consistency by comparing choice data in three treatment groups: direct decision-making, sequential elimination and process selection. We also have an incentive-compatible design in which participants can revise their choice to test decision makers' awareness of "mistake" in making choices. We also ask the participants' satisfaction with their choices and decision-making processes as criteria for welfare. We hypothesized decision makers who use sequential elimination have a higher level of consistency, less likely to change their choices and are more satisfied with their decisions. We control for preference for consistency, preference for consequentialism and sunk cost effects,

External Link(s)

Registration Citation

Citation
Guan, Rui. 2020. "Decision-making Process, Rational Choice and Welfare." AEA RCT Registry. March 01. https://doi.org/10.1257/rct.5220-1.4000000000000001
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-03-06
Intervention End Date
2020-03-13

Primary Outcomes

Primary Outcomes (end points)
The key outcome variables in this experiment are consistency scores measured by the choice data, as indicators of rationality. They include Generalized Axiom of Revealed Preference (GARP) violations (Varian 1982), Afriat’s (1967, 1972) critical cost efficiency index (CCEI) and swaps index (Apesteguia and Ballester, 2015). We will compare all consistency scores of individuals under different treatments.
Primary Outcomes (explanation)
We follow the literature to construct our outcome variables with choice data. The GARP violations index counts how many combinations of choices violate GARP. The CCEI measures the proportion of income that a person wasted by making the choice that violated revealed preference. The swaps index finds the minimized weighted sum of numbers of alternatives in a menu that must be swapped with the chosen one in order to make the choice of a consistent with the maximization of a preference.

Secondary Outcomes

Secondary Outcomes (end points)
Our secondary outcomes include individuals' satisfaction with their choice and decision-making processes, choice frequencies, choice changes, awareness of mistake, first-order stochastic dominance, risk preference and elicited preference.
Secondary Outcomes (explanation)
We measure individuals' satisfaction by survey questions after their completions of choice tasks. Participants simply provide their subjective evaluations of satisfaction with their choice and decision-making processes. We measure choice frequencies by computing the frequency of different choices in each menu in different treatment groups. We measure individuals' changes in choices by using an incentivized design. There are two blocks, A and B, each consists of the same 20 decision problems. Participants ex-ante do not know that Block A and B consist of the same decision problem before entering Block B. Depending on the treatments, in Block B, they are presented with their Block A choices (or sequence of eliminated alternatives) and can make different choices (or eliminate alternatives differently). In the end, they are asked to only one of Block A and Block B for payment. We count the number of choices that differ in Block A and Block B as a measure of awareness of "mistake" in making choices. We also check the violation first-order stochastic dominance in every menu. We will estimate risk-preference using the algorithm provided in Halevy, Persitz and Zrill (2018), We will elicit preference of each individual based on the method provided in Apesteguia and Ballester (2015).

Experimental Design

Experimental Design
We design an online experiment via Qualtrics, which will take approximately 40 minutes. We recruit participants from the Behavioral Experimental Sciences Laboratory (BESLab) in Barcelona. Participants will need to come to the lab and complete the experiment on Qualtrics in the lab. The experiment consists of three sections. In Section 1, each participant has to make choices in economic decision problems, either with a randomly assigned decision-making process or with her preferred decision-making process. In Section 2, we have four tests to measure cognitive function, including the International Cognitive Ability Resource (ICAR), the cognitive reflection test (CRT), the Stroop Color and Word Test (SCWT) and the Sternberg task. In Section 3, we collect information about participants’ preference for rational choice and choice process. Lastly, we ask participants for their demographic information, including gender, nationality, age, English level, education level and field of study.
Experimental Design Details
In Section 1, there are two blocks, A and B, each consists of 20 decision problems representing a set of portfolio options associated with two equally probable unknown states. This is the most common design in studying decisions under risk (e.g. Choi et al., 2014; Carvalho et al., 2016; Kim et al., 2018). There are three treatment groups: direct decision-making, sequential elimination and process selection. Participants firstly complete Block A without knowing that Block B consists of the same decision problems as BlockA. In Block B, participants in the direct decision-making group are presented with their Block A choices and can make different choices. Participants in the sequential elimination group are presented with their Part A sequence of eliminated alternatives) and can eliminate alternatives differently. In the end, every participant is asked to choose only one of Block A and B for payment. Then the computer randomly chooses one round from the 20 rounds from the chosen block with equal probability. The participant will get rewarded depending on the outcome of this chosen round.

In Section 2, The ICAR consists of 12 questions about verbal reasoning, letter and number series, matrix reasoning, and three-dimensional rotation (Condon and Revelle, 2014). The CRT measures one’s ability to suppress an intuitive and spontaneous incorrect answer and instead to give the deliberative and reflective correct answer (Frederick 2005). The SCWT and the Sternberg task are standard tests in psychology to measure selective attentions and working memory capacity, respectively.

In Section 3, participants will have to imagine themselves in two sets of hypothetical scenarios and answer a few questions related to the scenarios. First, we present them with two inconsistent choices known as "attraction effects" and ask how comfortable they are. Participants who indicate that they are uncomfortable suggests that they have a strong preference for choice consistency. Second, to control for "consequentialism", we ask them to make a choice between two hypothetical trips in which they will be doing the same things: 1) The trip is planned by the subject herself; 2) The trip is planned by someone else; 3) Indifferent. Participants who select the third option suggests that they are more likely to focus on the consequence. Third, we will also ask a scenario of sunk cost fallacy because it may lead to higher satisfaction under the treatment conditions. I adapt the example from Arkes and Blumer (1985). Subjects are asked to imagine that they have spent $50 on a ticket for concert A and $100 on a ticket for concert B. They are also to imagine that they really prefer A to B, that they have just discovered that the events are mutually exclusive and that the tickets have no salvage value. They are asked which concert they would then choose to go to. Participants who select concert B suggests that they are affected by the sunk cost.
Randomization Method
The randomization will be done by the online survey tool Qualtrics.
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
260 individuals.
Sample size: planned number of observations
260 individuals.
Sample size (or number of clusters) by treatment arms
80 individuals treatment 1 (direct decision-making), 80 individuals treatment 2 (sequential elimination), 100 individuals treatment 3 (process selection)
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
The Institutional Committee for Ethical Review of Projects (CIREP) at Universitat Pompeu Fabra
IRB Approval Date
2020-01-14
IRB Approval Number
137

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials