Arbeitspapier

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

Cheeseman and Peiffer (2022) field a 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, in fact, increase bribes. They further show that these counterproductive 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 shortcomings 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.

Language
Englisch

Bibliographic citation
Series: I4R Discussion Paper Series ; No. 94

Classification
Wirtschaft
Subject
Replication study
Corruption
Nigeria

Event
Geistige Schöpfung
(who)
Bergeron-Boutin, Olivier
Ciobanu, Costin
Cohen, Guila
Erlich, Aaron
Event
Veröffentlichung
(who)
Institute for Replication (I4R)
(where)
s.l.
(when)
2023

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Bergeron-Boutin, Olivier
  • Ciobanu, Costin
  • Cohen, Guila
  • Erlich, Aaron
  • Institute for Replication (I4R)

Time of origin

  • 2023

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