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Demand-driven, private sector enforcement of labor law in Bangladesh
Last registered on December 29, 2020


Trial Information
General Information
Demand-driven, private sector enforcement of labor law in Bangladesh
Initial registration date
February 24, 2017
Last updated
December 29, 2020 5:26 PM EST
Primary Investigator
Columbia University
Other Primary Investigator(s)
Additional Trial Information
Start date
End date
Secondary IDs
Weak states with poor institutions often do not have the capacity to implement and/or to enforce labor regulations aimed at improving working conditions. Increasingly, private actors have started enforcing labor standards in these countries, but the effects of their interventions on local firms and workers is currently unknown. This paper partners with a set of multinational retail and apparel firms to enforce local labor laws on their suppliers in Bangladesh. Specifically, I design and implement a randomized controlled trial with Bangladeshi garment factories, randomly enforcing a local labor law on supplier establishments. I aim to measure the impacts of this intervention on factories’ compliance levels and productivity as well as on workers’ welfare. I have also designed the intervention to facilitate exploring the broader equilibrium compliance levels in the sector.
External Link(s)
Registration Citation
Boudreau, Laura. 2020. "Demand-driven, private sector enforcement of labor law in Bangladesh." AEA RCT Registry. December 29. https://doi.org/10.1257/rct.1937-8.1.
Former Citation
Boudreau, Laura. 2020. "Demand-driven, private sector enforcement of labor law in Bangladesh." AEA RCT Registry. December 29. http://www.socialscienceregistry.org/trials/1937/history/83057.
Sponsors & Partners

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Experimental Details
The implementation partner, a coalition of multinational retail and apparel firms, is responsible for the intervention. The coalition is a group of firms that are working together to improve the safety performance of their shared supplier base in Bangladesh. The coalition has several programs designed to bring its suppliers into compliance with local labor laws. I study one of these programs using a randomized-controlled trial.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
The outcome variables for this study will be disclosed via a Pre-Analysis Plan prior to the study completion. I will publicly post the outcome variables following the completion of the trial. Outcome variables are included for factories, workers, and managers.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
I am targeting having 80 factories in the intervention group, with 40 factories randomly assigned to the treatment group and 40 factories randomly assigned to the control group. The randomization procedure blocks factories based on size (binary distinction between factories with less than or equal to 3,000 employees and factories with greater than 3,000 employees) and on “readiness for SC Program,” or when the factory met Alliance prerequisites for participation in the SC Program (factories are randomized to treatment and control conditions in batches). The study duration is for nine months. The randomized assignment to treatment and control statuses will be used to identify the intervention’s effects.

I am implementing independent data collection, with a data collection partner, at factories selected to be in the evaluation group. I am also collecting data from several other sources.
Experimental Design Details
The evaluation group of factories is being selected through a two-step process. The pool of eligible factories is limited to factories that supply exclusively to the Alliance (and do not supply to a separate coalition of multinational firms). This is due to difficulty coordinating evaluation implementation with the other coalition (the eligible pool of factories remains a very relevant population to study). From this pool of about 300 factories, the Alliance verifies that a factory has a separate committee that is formed in compliance with Bangladeshi labor law (more details provided in the Pre-Analysis Plan). This other committee must be elected by workers and is responsible for appointing worker representatives to the SC. Once the Alliance verifies that this committee is compliant, a factory is eligible for the SC Program.

Each time the Alliance has a batch of verified factories, it sends the list to the researcher. The researcher randomly assigns half of the factories to the treatment group and half to control (after blocking on factory size). The non-random selection of factories for the evaluation raises an external validity concern. I have access to numerous data sources that will allow me to compare my sample to the broader populations of Alliance-covered and exporting factories in Bangladesh along many relevant characteristics. I am confident that the factory sample is a relevant population that allows me to make generalizable conclusions.

I am collecting several types of data at varying frequencies. First, I administer baseline and 9-month factory questionnaires to collect factory human resource and production-related data at the monthly frequency, so I will have 9 observations during the evaluation period. Second, factory visits are conducted at baseline, 4 months, and 9 months. At factory visits, surveys are conducted with workers, lower-level managers, SC members, and the factory manager. At factory visits, safety-related documentation required by law and/or the Alliance are also verified. Finally, at eight factories, focus group discussions (FGDs) are conducted with workers and with lower-level managers. Third, I collect Alliance data, including (1) building safety audit performance; (2) building safety remediation progress; (3) number of Alliance members purchasing from the supplier; (4) call logs for the Alliance’s worker helpline; (5) factory escalation and suspension statuses. Data types (2)-(5) are available monthly.
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Randomization to treatment status is conducted at the factory level. The main level of interest is factory-level outcomes. I will also analyze worker- and manager-level outcomes, for which participants are cluster-randomized into assignment (where the factory is the cluster).
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
80 factories.
Sample size: planned number of observations
Repeated cross sections will be taken at each factory. The sample size per factory depends on the number of employees at the factory (due to production disruptions caused by taking workers and managers out of their tasks). At most factories, 20-25 workers and 20-25 managers will be surveyed each data collection round. Under the assumption that all 80 factories can contribute 20-25 worker and 20-25 management participants, the total number of observations will be between 1,600-2,000 observations for workers and managers, respectively, for each round of data collection. Continuing under the same assumption, across all rounds of data collection, the total number of observations of each type will be between 4,800-6,000 observations for workers and managers, respectively. The total number of observations for each group (in particular managers) may be below the estimated amount if a significant number of the evaluation group factories are smaller than I anticipate.
Sample size (or number of clusters) by treatment arms
40 treatment factories and 40 control factories.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
UC Berkeley Committee for Protection of Human Subjects
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
Pre-Analysis Plan: Demand-driven Enforcement of Labor Law in Bangladesh (update June 27, 2017)

MD5: 2c68c178e71c921c9f99b67c9a293ffe

SHA1: b3c69d4ac56174924e3eb8bdf1ce1666710c52ae

Uploaded At: June 27, 2017

Index construction for primary outcome variables

MD5: 3ed28d3543ebd167f84d1af154732b26

SHA1: 880872ff85c6b927c39ec15c66d1f94f6f88b1e0

Uploaded At: July 20, 2017

Index construction for secondary outcome variables

MD5: 5cbfce36ca43be0210cedc8da630e8c3

SHA1: e922a4ec7aea51a9d9d1453834c8281e69eeafbc

Uploaded At: September 04, 2017

Pre-Analysis Plan: Demand-driven Enforcement of Labor Law in Bangladesh

MD5: 3a4e93a7b404d2dd41fa38db0ba73dc1

SHA1: 48ee3c4d69249324ed42412d6b7ca6ce93215a05

Uploaded At: December 11, 2017

Index construction for primary outcome variables

MD5: 644f9f8d6e2fa99540d1e451a833cd88

SHA1: ae0247d194f51d624e51d50c371d04dc3ccbeaaa

Uploaded At: December 11, 2017

Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)