The effect of loss framing on the productivity of high and low performing agents

Last registered on November 08, 2019
View Trial History

Pre-Trial

Trial Information

General Information

Title
The effect of loss framing on the productivity of high and low performing agents
RCT ID
AEARCTR-0005003
Initial registration date
November 07, 2019

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
November 08, 2019, 10:10 AM EST

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

Locations

Country
Switzerland
Region
Country
Germany
Region

Primary Investigator

Name
Andrea Essl
Affiliation
University of Bern
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Stefanie Jaussi
PI Affiliation
University of Bern
Contact Investigator
PI Name
Kathrin Friedrich
PI Affiliation
University of Bern
Contact Investigator
PI Name
Frauke von Bieberstein
PI Affiliation
University of Bern
Contact Investigator
PI Name
Kirsten Thommes
PI Affiliation
PI Name
Christin Hoffmann
PI Affiliation
Contact Investigator

Additional Trial Information

Status
In development
Start date
2019-06-01
End date
2020-12-31
Keywords
Labor
Additional Keywords
Lab experiment, Incentive contracts, Contract framing, Loss aversion
JEL code(s)
Secondary IDs
Abstract
In a laboratory experiment, we examine how introducing a gain and loss contract affects the productivity of high and low performing agents. In the experiment, participants first perform a real-effort task under a fixed wage. The stage is used to measure participants’ baseline performance. In a second stage, participants work on the same real-effort task, but the payment scheme varies across treatments. They now either work under a positively framed gain contract or a negatively framed loss contract. The incentive contracts are payoff equivalent and only differ in terms of framing.
External Link(s)

Registration Citation

Citation
Essl, Andrea et al. 2019. "The effect of loss framing on the productivity of high and low performing agents." AEA RCT Registry. November 08. https://doi.org/10.1257/rct.5003-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
First, participants work on a real-effort task under a fixed wage contract. In this stage, we assess participants’ baseline performance and accordingly, we classify participants in high and low performing agents. Second, participants work on the same task under either a positively framed gain contract (gain treatment) or a negatively framed loss contract (loss treatment). This stage is used to analyze how the introduction of incentive contracts affects the productivity of high and low performing agents.
Intervention Start Date
2019-11-15
Intervention End Date
2020-04-30

Primary Outcomes

Primary Outcomes (end points)
Number of tasks solved in the real-effort task under the incentive contracts compared to baseline productivity under fixed wage contract. We will control for individual differences as given by the questionnaire.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Lab experiment. Between-subject design. Participants are randomized at the session level to either the gain or the loss treatment. Two stages: First, participants work on a real-effort task under a fixed wage contract. In this stage, we assess participants’ baseline performance and accordingly, we classify participants in high and low performing agents. Second, participants work on the same task under either a positively framed gain contract or a negatively framed loss contract. This stage is used to analyze how the introduction of incentive contracts affects the productivity of high and low performing agents. In addition, we elicit individual loss aversion. Participants fill out a non-incentivized questionnaire.

Experimental Design Details
Randomization Method
Computer (lab experiment)
Randomization Unit
Experimental session
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
In total about 300 participants
Sample size: planned number of observations
About 150 participants per treatment
Sample size (or number of clusters) by treatment arms
About 150 participants per treatment
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

Post-Trial

Post Trial Information

Study Withdrawal

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

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