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Creating Cohesive Communities: A Youth Camp Experiment in India

Arkadev Ghosh, Prerna Kundu, Matt Lowe, and Gareth Nellis

Non-family-based institutions for socializing young people may play a vital role in creating close-knit, inclusive communities. We study the potential for youth camps—integrating rituals, sports, and civics training—to strengthen intergroup cohesion. We randomly assigned Hindu and Muslim adolescent boys, from West Bengal, India, to two-week camps or to a pure control arm. To isolate mechanisms, we cross-randomized collective rituals (such as singing the national anthem, wearing uniforms, chanting support during matches, and synchronous dancing) and the intensity of intergroup contact.

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The Value of Privacy in Cartels: An Analysis of the Inner Workings of a Bidding Ring

Kei Kawai, Jun Nakabayashi, and Juan Ortner

We study how incentive constraints can be relaxed by randomization in a repeated-game setting. Our study is motivated by the workings of a detected bidding cartel that adopted a protocol of keeping the winning bid secret from the designated losers when defection was a concern. Keeping the winning bid secret makes accurately undercutting the winning bid more difficult and makes defection less attractive as potential defectors risk not winning the auction even if they deviate.

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How People Use Statistics

Pedro Bordalo, John Conlon, Nicola Gennaioli, Spencer Kwon, and Andrei Shleifer

For standard statistical problems, we provide new evidence documenting i) multi-modality and ii) instability in probability estimates, including from irrelevant changes in problem description. The evidence motivates a model in which, when solving a problem, people represent each hypothesis by attending to its salient features while neglecting other, potentially more relevant, ones. Only the statistics associated with salient features are used.

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This paper started with data. We were convinced that the discrepancy between book and market values of banks was key to understanding the data. We then developed a theory where, with a simple model, only one state variable driving Tobin's Q, you can explain several data moments.

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"We provide a guide for researchers on how to estimate gene-environment (GxE) interplay, using school-starting age as a case study. We argue that gene-environment (G x E) studies can help

(i) assess treatment effect heterogeneity,
(ii) test theoretical predictions, and 👇

1/

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"We are thrilled to share that our latest research is now published in @RevEconStudies! 🎉Check it out here:
https://www.restud.com/a-q-theory-of-banks/

We look forward to hearing your thoughts! "

@JulianeBegenau, @SakiBigio, Majerovitz, and Vieyra

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