The impact of the COVID-19 crisis on decision making quality

Last registered on February 11, 2021
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Pre-Trial

Trial Information

General Information

Title
The impact of the COVID-19 crisis on decision making quality
RCT ID
AEARCTR-0006840
Initial registration date
December 07, 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
December 07, 2020, 10:50 AM EST

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

Last updated
February 11, 2021, 9:06 AM EST

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

Locations

Country
Netherlands
Region

Primary Investigator

Name
Sara Arts
Affiliation
Radboud University
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Other Primary Investigator(s)

PI Name
Jana Vyrastekova
PI Affiliation
Radboud University
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PI Name
Jianying Qiu
PI Affiliation
Radboud University
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Additional Trial Information

Status
In development
Start date
2020-12-07
End date
2021-12-31
Keywords
Behavior, Finance & Microfinance, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
We examine the impact of financial difficulty to decision making quality via a large survey to a representative sample of Dutch population. We use the COVID-19 crisis as a natural intervention, since it creates financial difficulty to many households. Decision making quality is measured by violations of Generalized Axiom of Revealed Preferences (GARP), and we assess households’ decision-making quality two times: during and after the COVID-19 crisis. Following cognitive depletion literature, we additionally elicit participants’ cognitive performance. To further examine the source of violations of GARP, we investigate the existence of a well-defined utility function. We discuss policy implications of our results both in the short term and in the long term.
External Link(s)

Registration Citation

Citation
Arts, Sara, Jianying Qiu and Jana Vyrastekova. 2021. "The impact of the COVID-19 crisis on decision making quality." AEA RCT Registry. February 11. https://doi.org/10.1257/rct.6840-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-12-07
Intervention End Date
2021-12-31

Primary Outcomes

Primary Outcomes (end points)
1) Decision Quality
2) Cognitive Performance
3) Financial Situation Assessment
Primary Outcomes (explanation)
1) Following Choi et al. (2007, 2014) participants make several decisions, each reflecting a different budget line. With these decisions we can observe violations of GARP (Generalized Axiom of Revealed Preferences) and compute their Critical Cost Effective Index (CCEI), which will be our main measurement of Decision Quality. A set of 16 decisions is presented to subjects, in the second wave subjects will be presented with the mirrored versions of the decisions.
2) Cognitive performance will be measured based on 5 matrix reasoning tasks and 3 3D Rotation tasks from the International Cognitive Ability Resource (ICAR). In each wave subjects will see different tasks.
3) We have several questions to assess subjects financial situation. We specifically ask subjects to state their satisfaction with their financial situation, whether they feel their financial situation has gotten better or worse compared to a year ago, and how often they worry about their financial situation. Additionally, we ask about some specific aspects of their financial situation: their income, use of savings, use of loans, and trouble with paying bills. For these four aspects we ask about the change compared to a year ago and their expectations for the coming year.

Secondary Outcomes

Secondary Outcomes (end points)
1) Preference for Randomization
2) Inclusion of Others in Self
3) Mental Health / Stress
4) Control Variables
Secondary Outcomes (explanation)
1) As an additional measure of economic rationality (aside from the decision quality measure described previously), we include a measure on preference for randomization. In this task subjects can choose between a lottery and a certain amount of points. The lottery is the same in each choice, while the amount of points increases (or decreases) going through the choices. In addition to the two binary option, subjects can choose to let a computer make the decision for them. This measure is also related to the concept of incomplete preferences.
2) Two items based on Aron et al., 1992; One focused on others in general, one focused on the subject's family.
3) The mental health of subjects is assessed via an existing measure included in the panel on which we conduct our experiment. It is obtained around the same time, and asks subjects how often in the past month they felt a certain way. It consist of five items (e.g. I felt very anxious, I felt happy), and is measured on a 6 item-scale (Never - Continuously).
4) The experiment is conducted with a (subset of) a large representative sample of Dutch households. This means there are many background variables which can be used as control variables, such as income, education, etc.

Experimental Design

Experimental Design
The survey consists of 3 parts:
1) Decision Quality task
2) Preference for Randomization task
3) Cognitive Performance task
And in addition some end of survey questions.
Experimental Design Details
Randomization Method
For each part of the survey different versions were created for the 2 waves. Subjects were randomly assigned to one of the versions for each part. The version they see in Wave 2 will be different to the version they see in Wave 1. This randomization was done by the software used to conduct the survey in the panel.
Randomization Unit
Different versions of the survey.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
750 subjects in the first wave. The same subjects will be approached for the second wave.
Sample size: planned number of observations
Taking into account dropouts for the second wave, we estimate to have 1400 observations (750 first wave, 650 second wave).
Sample size (or number of clusters) by treatment arms
750 subjects in the first wave, 650 in the second wave.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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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