Income or Leisure? On the Hidden Benefits of (Un-)Employment

Last registered on December 03, 2021

Pre-Trial

Trial Information

General Information

Title
Income or Leisure? On the Hidden Benefits of (Un-)Employment
RCT ID
AEARCTR-0008638
Initial registration date
November 29, 2021

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 03, 2021, 1:49 PM EST

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

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

Status
In development
Start date
2021-12-01
End date
2021-12-07
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this paper, we investigate the usually assumed trade-off between income and leisure in labor supply decisions based on two different studies. In a first study, we use comprehensive German panel data to compare non-employed individuals after plant closures with employed people regarding both income and time use as well as their subjective perceptions of these two factors. We find that the gain of non-working time translates into higher satisfaction with free time, while time spent on hobbies increases to a lesser extent than home production. Additionally, satisfaction with family life increases, which may be a hidden benefit of being unemployed. In contrast, satisfaction with income strongly declines when becoming jobless. Identity utility from earning a living may play the role of a hidden benefit of employment. To learn more about the role of social pressure to earn a living, we investigate the mechanisms underlying our main results using an experimental approach. In a second study, we therefore conduct a survey experiment based on hypothetical decisions of individuals who either accept or reject job offers. Study participants assess the social appropriateness of these two decisions, which in comparison reveals the social norm against living off other people. By varying the context, our experimental design also allows us to empirically test a possible compensation of social pressure to work via home production and to study the potential role of gender differences. The second study is what we pre-register here.
External Link(s)

Registration Citation

Citation
Chadi, Adrian and Clemens Hetschko. 2021. "Income or Leisure? On the Hidden Benefits of (Un-)Employment." AEA RCT Registry. December 03. https://doi.org/10.1257/rct.8638-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-12-01
Intervention End Date
2021-12-07

Primary Outcomes

Primary Outcomes (end points)
Social appropriateness
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In our survey experiment, we illustrate a decision context of a hypothetical individual (person X) who decides about taking up a job offer or not. Participants of the survey are representative of the German population in several dimensions (such as education) and have to assess the social appropriateness of the decision. The context provides information about the income situation, so that we are able to identify the social norm against dependency on public assistance. For this reason, we clarify that the implications of taking up a job are negligible moneywise but being employed allows for compliance with this particular social norm. Such a scenario is plausible given the institutional background in Germany and hence realistic for survey participants who are asked to assess the social appropriateness of X’s decision to earn money in the labor market or not.
To identify the social pressure to earn a living, we compare the two different decisions as our main experimental treatments. First, X picks up the job, which would be expected as being perceived socially appropriate, despite that this decision is not rewarded by any relevant increase in household income. We test the hypothesis that society expects people to earn a living (vs. relying on society to help via public assistance) empirically by comparing the perceived appropriateness of taking up a job, compared to the alternative decision by X to stay non-employed, which is the second main treatment. Randomness of this manipulation in our experiment allows us to identify the causal effect of (non )employment on the social appropriateness of individual (mis)behavior in the eyes of the public, which indicates the level of social pressure to do what society expects you to do.
To ensure that survey responses of participants inform us about the social norm to earn a living, we ask them first to think about their belief of what the broader population perceives as socially appropriate, before we ask them about their personal views on the matter in a second step. As a well-established tool to foster successful identification of social norm effects, we incentive survey responses by allowing participants to receive a monetary reward if their belief matches the most common answer in all the survey participants (in a given treatment condition). This idea follows a concept by Krupka and Weber (2013) to measure social norms regarding appropriate behavior via an incentivized experimental approach. In our application of this approach, we allow participants to take part in a lottery. A prize of 50 Euro is awarded to each randomly drawn winner (from all the participants in a given treatment condition), provided that this participant reports the ‘correct’ response in the way described above.
In addition to our main manipulation regarding the job decision (take-up of the job offer vs. staying in non-employment), we further manipulate the scenario by providing information about time-use in unemployment. Accordingly, X can either be productive at home (e.g. by taking care of the children) or X enjoys leisure time (e.g. by pursuing hobbies). Furthermore, we manipulate the gender of X by using gender-specific terms like Mr. X vs. Ms. X. Thereby, we have a 2x2x2 experimental design with three different dimensions (job decision / time-use / gender). To complement our dataset, we collect information on the survey respondents including their attitudes towards work as a means to contribute to society (among other reasons why people go to work), which could play a role when assessing behavioral choices in the labor market.
By inspecting varying scenarios, we can learn more about the mechanisms underlying our earlier findings on labor supply decisions in our first study (based on data from the German Socio-Economic Panel study). First and foremost, we empirically test the idea of social pressure to earn a living, which could explain our behavioral evidence on people’s labor supply. Furthermore, our design answers the question whether this pressure could be alleviated by being productive at home (as opposed to leisure enjoyment). This is ex-ante unclear, given that there are reasons why society might not reward unemployed people for being productive at home. A possible explanation could be that doing useful things at home, such as childcare, does not receive the recognition by others, as doing market work does. Finally, our design allows us to study the role of potential gender differences in social pressure and hence labor market behavior. Previous research suggests that traditional gender roles could affect labor market behavior, with men being expected more than women to fulfill a breadwinner role by supplying market work. Due to societal trends and significant changes over time in beliefs regarding the role of women and men in the labor market, however, the existence of gender-specific effects on the assessment of socially appropriate behavior is an open question.
Experimental Design Details
Randomization Method
Computer
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000+
Sample size: planned number of observations
1000+
Sample size (or number of clusters) by treatment arms
100+
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

Post-Trial

Post Trial Information

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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