Data and Code for: Leaders in Social Movements: Evidence from Unions in Myanmar

Principal Investigator(s): View help for Principal Investigator(s) Laura Boudreau, Columbia University; Rocco Macchiavello, London School of Economics; Virginia Minni, University of Chicago. Booth School of Business; Mari Tanaka, University of Tokyo, Hitotsubashi University

Version: View help for Version V1

Name	File Type	Size	Last Modified
Data			01/14/2025 12:51:PM
DoFiles			03/24/2025 04:43:AM
Output			01/14/2025 12:51:PM
0.README.md	text/x-web-markdown	14.3 KB	03/24/2025 12:41:AM

Project Citation:

Boudreau, Laura, Macchiavello, Rocco, Minni, Virginia, and Tanaka, Mari. Data and Code for: Leaders in Social Movements: Evidence from Unions in Myanmar. Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-05-06. https://doi.org/10.3886/E214181V1

Project Description

Summary:

Social movements are catalysts for crucial institutional changes. To succeed, they must coordinate members’ views (consensus building) and actions (mobilization). We study union leaders within Myanmar’s burgeoning labor movement. Union leaders are positively selected on both ability and personality traits that enable them to influence others, yet they earn lower wages. In group discussions about workers' views on an upcoming national minimum wage negotiation, randomly embedded leaders build consensus around the union’s preferred policy. In an experiment that mimics individual decision-making in a collective action set-up, leaders increase mobilization through coordination.

The code in this replication package cleans all data sources used in the analysis (Stata and R) and reproduces all the tables/figures provided in the paper and Supplementary Appendix.

Funding Sources: International Growth Centre (IGC); Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD); Joint Usage and Research Center (IER, Hitotsubashi University); JSPS Grant Number JP23K20609/21H00723

Scope of Project

JEL Classification:
      C93 Field Experiments
      D23 Organizational Behavior; Transaction Costs; Property Rights
      D70 Analysis of Collective Decision-Making: General
      J51 Trade Unions: Objectives, Structure, and Effects
      J52 Dispute Resolution: Strikes, Arbitration, and Mediation; Collective Bargaining

Geographic Coverage: Myanmar

Time Period(s): 12/2019 – 3/2020

Collection Date(s): 12/8/2019 – 3/15/2020 (December 2019-March 2020)

Universe: Garment workers in factories with unions in Myanmar in 2019-2020.

Data Type(s): audio: sound data; experimental data; observational data; survey data

Methodology

Response Rate: In total, we invited 18 union presidents and 1 secretary (19 factories), all of whom participated. We invited 190 union line leaders (or Executive Team (ET) members) from 19 factories, and 170 participated. For workers,due to COVID-19, we covered 17 factories. We invited 1511 workers and 916 (61%) participated. Among them, we invited 936 union members of which 594 (63%) participated, and 575 non-union members of which 322 (56%) participated.

Sampling:

At the time that the study was conducted, 41 garment factories had a union affiliated with the Confederation of Trade Unions in Myanmar (CTUM). We planned to include all factories sufficiently close to the survey location and with an operating union (some factories were still in the process of finalizing the establishment of the union). Our final list included 28 unions. Unfortunately, due to COVID-19, we had to stop our fieldwork early; 17 unions fully completed the data collection activities while additional 2 unions partially completed them.

Within each factory, we used a sampling protocol designed to obtain a sample that was representative of the populations of interest: union leaders (presidents and line leaders) and sewing section workers (union members and non-members). We conducted a stratified random selection of around 90 workers per factory. Within factory, we stratified by line, union membership, and skill level (for details, see Appendix Section A.1).

Data Source: We generated our data through field activities we implemented with workers employed at garment factories in the Yangon and Bago regions that had a factory-level basic union affiliated with the CTUM from December 2019 to March 2020.

Collection Mode(s): coded on-site observation; computer-assisted personal interview (CAPI); other

Weights: While we invited similar numbers of workers per factory, the turn-out was in part influenced by the union leaders, which raises the concern that factories with more capable union leaders may have larger sample sizes and thus receive more weight in our analysis. Thus, the dataset includes weight variables so that each factory counts equally. The probability weights are calculated as the total number of workers across factories divided by the number of workers in the specific factory. Alternative weights are explored in Appendix Section D.

Unit(s) of Observation: Individual

Related Publications

Download this project

Published Versions

V1 [2025-05-06]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as received from the data depositor. As of April 2026, depositors are required to submit study materials in accessible formats. ICPSR has not reviewed, checked, or processed this material. For additional information about the study, please contact the investigator(s) directly. If you have questions about the accessibility of materials distributed by ICPSR or require further assistance, please visit ICPSR's Accessibility Center.