Abstract:
In recent decades, the number of people disclosing their LGBTQ identity has increased substantially. We investigate the role of peer effects in coming out decisions using a model of a game social learning via networks. We use newly collected data from two waves of a spontaneous Twitter coming out campaign to test the prediction that observing peers coming out increases the probability of an individual disclosing their LGBTQ identity. We combine data on users' pre-campaign networks with the information on the exact time of costly coming out actions to construct a time-varying measure of the exposure to peers coming out as LGBTQ. A one standard deviation increase in the exposure increases the probability of coming out by almost 20%. We also exploit the non-overlapping network structure of users' peers groups as an exogenous source of variation, and we confirm the baseline results. We argue that the estimated effects are due to changes in beliefs about the costs of disclosure.
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To learn more about our speaker Jan Gromadzki, see his personal website.
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