Context
The elections are US data from 1961–2025. The estimate is local to close elections and state–industry cells.
SOCIAL LEARNING / FILE 01
In NLRB data from 1961–2025, a close win is followed by 0.284–0.689 additional wins in the same state–industry cell over the next three years. In a separate experiment, information about wins moved support and beliefs about coworkers, but not significantly the interest in contacting an organizer.
NBER Working Paper 35571 · August 2026 · 1961–2025 NLRB elections · 9,089 hourly US retail/service workers · working paper, not peer-reviewed
A win can travel through results and through people’s expectations. The study’s boundary appears at the last step: a change in opinion is not proof of costly local action.
Two measured steps.
The last stays open.
First, through the election record: close wins are followed by more wins in the same state–industry combination. Then, through workers’ minds: information about wins changes stated support and expectations about coworkers.
These are different outcomes. The page keeps them together so a change in opinion does not become a promise about union formation.
Start with the election thresholdA close win opens a path to later wins.
Win information moves support and beliefs about coworkers.
Interest in contacting an organizer does not rise significantly.
The authors compare NLRB elections clustered around the 50% threshold. When a few votes change the result, the comparison can isolate what follows a win that almost did not happen.
The reported estimate is 0.284–0.689 additional wins in the same state–industry cell over the next three years. It is not a multiplier for every workplace: it is a range across specifications in a local setting.
SWITCH WHAT CHANGES AT THE THRESHOLD?
The interaction changes the scenario; it does not invent an estimate for a loss.
CLOSE WIN
+0.284–0.689
additional wins in the same state–industry cell over the next three years.
In an experiment with 9,089 hourly workers in US retail and service jobs, participants received information about union wins, how easy it was to find a job, both, or neither.
The switch below puts the same measures on one stage. Support values are standard deviations; the contact-interest value is in percentage points.
6,000 YouGov + 3,089 Prolific. The main support analysis starts with participants who underestimated union activity.
SWITCH WHAT INFORMATION DO YOU GET?
Results are effects relative to control, not absolute support scores.
UNION-WIN INFORMATION
Support and expectations about coworkers move after information about wins.
No statistically significant effect for contact interest. The control baseline for this measure is 23.9%.
For interest in contacting an organizer, the union-win information effect is +0.3 percentage points and is not statistically significant. The control group mean is 23.9%.
That does not mean information can never change action. It means this experiment measures a precise boundary: support and beliefs about coworkers move more clearly than reported interest in contacting an organizer.
MEASURED / UNMEASURED
Each row answers a different question. Mix them together and the story becomes larger than the source.
Additional wins over 3 years, same state–industry cell. Not a universal multiplier.
Union support and perceived coworker support after win information. Not union formation.
Interest in contacting an organizer. “Not significant” does not mean “zero,” and this is not observed action.
The elections are US data from 1961–2025. The estimate is local to close elections and state–industry cells.
The experiment uses online-recruited hourly workers in retail and service jobs. It is not an estimate for all workers or for Romania.
The source is an August 2026 NBER working paper, not a peer-reviewed article. The tables and PDF may change.
The page’s figures come from one primary source, checked and archived locally for audit. The unit conversions are explained in the evidence ledger.
Winning is Contagious: Social Learning and the Dynamics of Union Support
Ellora Derenoncourt, Arindrajit Dube, Suresh Naidu, Heather Sarsons and Niharika Singh · NBER Working Paper 35571 · DOI 10.3386/w35571 · August 2026.
This project synthesizes reported results and does not republish individual data, identities, or source figures. For definitions, formulas and limits, open the Markdown version or the NBER source.