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An empirical analysis of worldwide impunity

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  • Francisco Cribari-Neto

    (Universidade Federal de Pernambuco)

  • Marcelo A. F. L. Santos

    (Universidade Federal de Pernambuco)

Abstract

Our research investigates the relationship between economic and social development indicators and the prevalence of impunity within a country. As countries develop, their institutions tend to function more efficiently and impartially, resulting in less impunity as crimes and violations are more efficiently investigated and prosecuted. We describe a country’s level of economic and social development along seven dimensions and use such a description in a beta regression analysis to predict the level of impunity in 119 countries. We estimate the elasticities of impunity with respect to the variables representing the different dimensions of economic and social progress. We present plots with the estimated elasticity curves for scenarios indicative of less and more socially and economically developed societies and also for the scenario indicative of societies in transition between the two groups. We also identify the countries with the best and worst performance in terms of their levels of impunity in relation to the levels of the conditioning variables. It is shown that Nordic countries exhibit lower impunity than expected based on their economic and social development factors. Conversely, the United States displays a significantly higher level of impunity than expected from its development indicators.

Suggested Citation

  • Francisco Cribari-Neto & Marcelo A. F. L. Santos, 2024. "An empirical analysis of worldwide impunity," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03803-x
    DOI: 10.1057/s41599-024-03803-x
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    References listed on IDEAS

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    1. La Porta, Rafael & Lopez-de-Silanes, Florencio & Shleifer, Andrei & Vishny, Robert, 1999. "The Quality of Government," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 15(1), pages 222-279, April.
    2. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    3. Treisman, Daniel, 2000. "The causes of corruption: a cross-national study," Journal of Public Economics, Elsevier, vol. 76(3), pages 399-457, June.
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