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I4R Discussion Paper Series #94


Olivier Bergeron-Boutin (Dartmouth College), Costin Ciobanu (Royal Holloway, University of London), Guila Cohen (McGill University), Aaron Erlich (McGill University)

Replicating Backfire Effects in Anti-Corruption Messaging: A Comment on Cheeseman and Peiffer (2022)

Cheeseman and Peiffer (2022) fielda survey experiment in Nigeria to test the effect of five different anti-corruption messages on participants’ willingness to bribe public officials. They find that these messages generally fail to reduce bribes and could, infact, increase bribes. They further show that these counter productive effects of anti-corruption messages are especially pernicious for participants who believe corruption is widespread, whom they call “Pessimistic Perceivers.” We find that Cheeseman and Peiffer’s findings are computationally reproducible: using the same data and estimation procedures, we arrive at the same output reported in the original article. Furthermore, we find that following Cheeseman and Peiffer’s strategy to dichotomize a three-item scale used as a moderating variable, their results are robust to different estimation strategies. However, we draw attention to several short-comings of the original analysis. First, the distribution of the moderating variable is highly skewed: on a 0-1 scale, the mean value is 0.81. Cheeseman and Peiffer’s dichotomization procedure is also sensitive to the cutoff threshold and produces unstable results. Similarly, when we employ more flexible estimation strategies for heterogeneous treatment effects when the moderator is measured on a continuous scale, the results appear less robust.