Coronavirus, flexibility of work arrangements and financial security
Last registered on March 24, 2020

Pre-Trial

Trial Information
General Information
Title
Coronavirus, flexibility of work arrangements and financial security
RCT ID
AEARCTR-0005581
Initial registration date
March 24, 2020
Last updated
March 24, 2020 10:55 AM EDT
Location(s)
Region
Primary Investigator
Affiliation
University of Oxford
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2020-03-25
End date
2020-05-25
Secondary IDs
Abstract
The proposed study is a survey experiment, which will be carried out in several different countries. In each country, survey participants will be randomized into different information treatments. Individuals in the ‘Treatment 1’ group will receive truthful information on health-related aspects of the coronavirus outbreak. ‘Treatment 2’ will receive the same information as ‘Treatment 1’ and will additionally be informed about economic consequences of the outbreak. ‘Treatment 3’ will receive the same information as ‘Treatment 1’ and will additionally receive information on workers without paid sick leave. The ‘Control’ group will receive none of the above information. The goal of the study is to explore how different treatments affect (1) individual perceptions of the severity of the coronavirus outbreak and the adequacy of the policy response to the crisis, (2) individual valuations of different work arrangements, and (3) individual support for public policies.
External Link(s)
Registration Citation
Citation
Boneva, Teodora. 2020. "Coronavirus, flexibility of work arrangements and financial security." AEA RCT Registry. March 24. https://doi.org/10.1257/rct.5581-1.0.
Experimental Details
Interventions
Intervention(s)
In this survey experiment, survey respondents will be randomized into one of four groups: ‘Control’, ‘Treatment 1’, ‘Treatment 2’, or ‘Treatment 3’. Randomization will be performed at the individual level and each participant will have a 25% chance of being randomized into any given group. Individuals in the ‘Treatment 1’ group will receive truthful information on health-related aspects of the coronavirus outbreak. ‘Treatment 2’ will receive the same information as ‘Treatment 1’ and will additionally be informed about economic consequences of the outbreak. ‘Treatment 3’ will receive the same information as ‘Treatment 1’ and will additionally receive information on workers without paid sick leave. The ‘Control’ group will receive none of the above information.
Intervention Start Date
2020-03-25
Intervention End Date
2020-05-25
Primary Outcomes
Primary Outcomes (end points)
We will estimate the impact of the treatments on several outcomes, which can be categorized into three different groups: (1) Individual perceptions of the severity of the coronavirus outbreak and the adequacy of the policy response to the crisis, (2) individual valuations of different work arrangements, and (3) individual support for public policies.
Primary Outcomes (explanation)
(1) Perceptions about the severity of the coronavirus outbreak and adequacy of policy response to the crisis:
First, respondents are asked how the coronavirus outbreak has already affected their daily lives. Second, we ask for respondents’ subjective likelihood that certain outcomes will occur in the near future. Outcomes include disruptions to labor supply (e.g. having to work fewer hours, having to shut the business or having to rearrange work schedule to care for others) and loss in earnings, as well as estimates of the magnitude of the outbreak in the respondents’ state or region, measured as the perceived percentage of people who will contract the coronavirus in their area.

(2) Individual valuations of different work arrangements:
We follow Mas and Pallais (2017) and elicit individual willingness to pay or willingness to accept for different work attributes by using a simple discrete choice experiment. The work arrangements we consider are entitlement to sick pay, flexible scheduling and a permanent versus zero-hour (or on-call) contract. For each arrangement, respondents who currently have a paid job are presented with the choice between their current work contract and a new contract that excludes (includes) the arrangement under analysis and pays more (less) per hour. Unemployed individuals are offered the choice between two contracts that are similar to their last job contract in all aspects but the arrangement under analysis and wage. We randomly vary the wage difference between the two options and ask respondents which arrangement they would prefer. We implement a between-subject design where each respondent is presented with two options for each job characteristic under analysis, to limit cognitive load.

(3) Individual support for public policies:
Respondents are asked Likert-scale questions on the extent to which they agree or disagree with statements about public policies in support of vulnerable groups. Policies will include measures already taken by the government to tackle the outbreak, as well as proposals to provide government support to self-employed, temporary workers and low-income citizens. We will also use similar Likert-scale questions to measure respondents’ perception about the readiness of the government and the health system to tackle the coronavirus outbreak. Finally, we will measure support for redistributive policies targeted mostly at families or businesses.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Within each country, we will survey 4,000 individuals who are part of an online panel. Individuals will be randomized into one of four groups: ‘Control’, ‘Treatment 1’, ‘Treatment 2’, or ‘Treatment 3’. Randomization will be performed at the individual level and each participant will have a 25% chance of being randomized into any given group. We will estimate the causal impact of the treatments on a range of different outcomes and analyse whether the treatments were more/less effective for different groups in the population. This survey experiment will help us understand how individuals respond to the different treatments.
Experimental Design Details
We will estimate the average treatment effect of the treatments on each outcome by running OLS regressions of the outcome on the treatment dummies. To increase precision of our estimates, we will also perform the analyses controlling for baseline characteristics. In addition, we will look at several dimensions of heterogeneity. More specifically, we are interested in whether the treatments are differentially effective for (i) democrats vs republicans, (ii) men vs women, (iii) above vs below median age, and (iv) people with different work arrangements at baseline.
Randomization Method
Randomization done by the survey software we use to conduct the survey.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
The randomization is performed at the individual level. We do not have any clusters.
Sample size: planned number of observations
4,000 individuals per country
Sample size (or number of clusters) by treatment arms
Approximately 1,000 individuals ‘Control’, 1,000 individuals ‘Treatment 1’, 1,000 individuals ‘Treatment 2’, 1,000 individuals ‘Treatment 3’
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
University of Oxford, Central University Research Ethics Committee (CUREC)
IRB Approval Date
2020-03-20
IRB Approval Number
ECONCIA20-21-09
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is 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