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Analysing spatial spillovers in corruption: A dynamic spatial panel data approach

Author

Listed:
  • Hermann Pythagore Pierre Donfouet

    (CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux - INRA - Institut National de la Recherche Agronomique - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement)

  • P. Wilner Jeanty

    (Columbus Education and Conference Center - Indiana Wesleyan University)

  • Eric Malin

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

Abstract

Previous studies on the determinants of corruption have seldom addressed cross-border spillovers of corruption in a panel data setting. In this paper, we first propose a theoretical model of spatial corruption spillover based on network analysis. Then, we analyse spatial spillovers in corruption using a dynamic spatial panel approach. The results indicate that corruption not only exhibits spatial spillovers but also a persistent effect over time. More importantly, increase of income per capita, economic freedom, and percentage of women in the parliaments have a long-term effect on the perceived levels of corruption. Policies and programmes aiming at abating corruption must take into consideration those results.

Suggested Citation

  • Hermann Pythagore Pierre Donfouet & P. Wilner Jeanty & Eric Malin, 2018. "Analysing spatial spillovers in corruption: A dynamic spatial panel data approach," Post-Print halshs-01354146, HAL.
    • Handle: RePEc:hal:journl:halshs-01354146
    DOI: 10.1111/pirs.12231
    as

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    Cited by:

    1. Carmelo Algeri & Antonio F. Forgione & Carlo Migliardo, 2022. "Do spatial dependence and market power matter in the diversification of cooperative banks?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    2. Canhoto, Ana Isabel, 2021. "Leveraging machine learning in the global fight against money laundering and terrorism financing: An affordances perspective," Journal of Business Research, Elsevier, vol. 131(C), pages 441-452.
    3. Cong Yu & Linke Hou & Yuxia Lyu & Qi Zhang, 2022. "Political competition, spatial interactions, and default risk of local government debts in China," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 717-743, June.
    4. Julien Hanoteau & Gandhi Pawitan & Virginie Vial, 2021. "Does social capital reduce entrepreneurs' petty corruption? Evidence across Indonesian regions," Papers in Regional Science, Wiley Blackwell, vol. 100(3), pages 651-670, June.

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