Back to History Current Version

Peers and Motivation at Work

Last registered on September 02, 2018

Pre-Trial

Trial Information

General Information

Title
Peers and Motivation at Work
RCT ID
AEARCTR-0001105
Initial registration date
March 07, 2016

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
March 07, 2016, 1:06 AM EST

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

Last updated
September 02, 2018, 2:30 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Washington

Other Primary Investigator(s)

PI Affiliation
University of Michigan
PI Affiliation
Yale University

Additional Trial Information

Status
Completed
Start date
2015-02-02
End date
2016-03-31
Secondary IDs
Abstract
This study comprises two experiments. The first experiment randomly assigns tea-harvesting workers to locations on fields to estimate peer effects in output. The second is an incentivized choice experiment that measures workers' willingness to pay for higher-ability peers.
External Link(s)

Registration Citation

Citation
Brune, Lasse, Eric Chyn and Jason Kerwin. 2018. "Peers and Motivation at Work." AEA RCT Registry. September 02. https://doi.org/10.1257/rct.1105-3.0
Former Citation
Brune, Lasse, Eric Chyn and Jason Kerwin. 2018. "Peers and Motivation at Work." AEA RCT Registry. September 02. https://www.socialscienceregistry.org/trials/1105/history/199481
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
There are two experiments in this study:

1. Our first experiment randomly assigns tea-harvesting workers to locations on fields to estimate peer effects. To conduct our study, we partnered with Lujeri Tea Estates, a large agricultural firm in Malawi. Our sample is a group of roughly 1,000 employees who hand-pick ("pluck") leaves from tea bushes (hereafter, we refer to these workers as pluckers). Workers temporarily store plucked leaves in baskets and empty their baskets at a central weighing station. There is no explicit cooperation involved in this process, and pay is a constant piece rate for each kilogram of plucked tea.

Production at the firm is organized by assigning workers to "gangs" which are each managed by a supervisor. The size of a gang is typically around 45 pluckers, but the sizes range from 29 on the low end to 76 on the high end. Each gang is responsible for plucking tea from a pre-determined set of fields over the course of a harvesting "cycle" (7 to 12 calendar days). In our analysis sample, there are 78 fields for the 22 gangs we study.

On each tea field for a gang, the supervisor assigns workers to pluck tea from a specific set of plots (between 1 and 3 per harvest cycle day, depending on the characteristics of the field). The assignment of workers to plots for given field is done at the beginning of the main season and generally remains in place throughout the season. Each field has between 30 and 120 plots, and workers must finish plucking their assigned plots before moving on to other plots. At the completion of a harvesting cycle (most commonly 6 work days, or 7 calendar days, since Sunday is a day off), the gang returns to the initial field for a new round of plucking - unlike other crops that are harvested once or a few times, tea bushes grow continuously throughout the season.

We designed our experimental intervention to randomly assign workers to plots on tea fields to generate exogenous variation in exposure to workplace peers. To implement this, we obtained the roster of workers in each gang and a "plucking program" for each gang. The plucking program is a predetermined list of which field (or fields) a gang works on during each day of its cycle and the number of pluckers that should be assigned to each field. In the simplest case, there is one field on each cycle day with all the pluckers working on it. We use this information to generate randomly-ordered lists of pluckers for each day of a gang's harvesting cycle. On cycle days where a gang works on multiple fields, we also randomly determine which workers are on each field.

We used these randomized lists to determine the order in which supervisors assign pluckers to plots on each field. The random assignment took advantage of the usual assignment process in which pluckers stand in a queue and receive plot assignments in the order that they are standing. The supervisor makes the assignments by ``snaking'' back and forth across the field and taking the next plucker from the queue for each plot. Our random assignment scheme altered this system by giving the supervisors a randomly-ordered list to use in this snake pattern. Each gang supervisor assigned workers using the randomly generated list of worker assignments in February 2015. We verified compliance with these assignments by having our project managers visit each gang in the week after randomization. In addition, project staff confirmed compliance with the assignment via random spot checks several weeks after the initial assignment. As a result of our intervention, workers are assigned randomly to plots within a field for different cycle days.

2. The incentivized choice experiment uses a survey of the same sample of workers to elicit incentivized choices about whether they prefer higher-ability peers (faster pluckers). Workers are offered six different choices over potential peers that might want to switch places to work next to. One of those choices, selected at random, is implemented for 10% or workers. Workers know these probabilities ex ante and thus the optimal response is to truthfully reveal their preferences. We use the elicited choices to estimate the mean willingness to pay for faster peers, and the marginal willingness to pay for an improvement in peer quality.
Intervention Start Date
2016-03-07
Intervention End Date
2016-03-31

Primary Outcomes

Primary Outcomes (end points)
Our outcome for the peer effects estimation experiment is the daily log output of tea.

Our key outcome for the incentivized choice experiment is the willingness to pay for higher-ability peers. See the pre-analysis plan for details.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our peer effects estimation experiment consists of two steps:
1. Random assignment of workers to peers.
2. Using randomly-assigned peers and daily output data to estimate a linear-in-means model of peer effects.

Our incentivized choice experiment consists of three steps:
1. Random assignment of workers to peers. This was implemented starting in late February.
2. A survey containing the incentivized choice experiment to elicit WTP. This begins on March 7, 2016.
3. Workers’s positions are changed to implement the choices for the 10% of people who chose faster peers. This happens immediately after the survey ends, and is done to make the elicited choices incentive-compatible.
Experimental Design Details
Randomization Method
Randomization done in office by a computer (for random peer assignment).
Randomization done in the field on tablets (for implementation of the incentivized choices with p=0.1)
Randomization Unit
For the first experiment, randomization is within-individual at a level of cycle day.

For the second experiment, randomization is at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
999 workers
Sample size: planned number of observations
999 workers
Sample size (or number of clusters) by treatment arms
Not applicable – no treatment arms. Each worker is randomly assigned to peers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Health Sciences and Behavioral Sciences, University of Michigan
IRB Approval Date
2015-02-02
IRB Approval Number
HUM00095368
Analysis Plan

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

Request Information

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?
Yes
Intervention Completion Date
April 30, 2015, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
April 30, 2015, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
999 workers
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
999 workers
Final Sample Size (or Number of Clusters) by Treatment Arms
999 workers randomized to peers by cycle day
Data Publication

Data Publication

Is public data available?
Yes

Program Files

Program Files
Yes
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
This paper studies workplace peer effects by randomly varying work assignments at a tea estate in Malawi. We find that increasing mean peer ability by 10 percent raises productivity by 0.3 percent. This effect is driven by the responses of women. Neither production nor compensation externalities cause the effect because workers receive piece rates and do not work in teams. Additional analyses provide no support for learning or socialization as mechanisms. Instead, peer effects appear to operate through “motivation”: given the choice to be reassigned, most workers prefer working near high-ability co-workers because these peers motivate them to work harder.
Citation
Brune, L., Chyn, E., & Kerwin, J. (2022). Peers and Motivation at Work Evidence from a Firm Experiment in Malawi*. Journal of Human Resources, 0919-10416R2. https://doi.org/10.3368/jhr.57.4.0919-10416R2

Reports & Other Materials