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The pioneer evidence of contagious corruption

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Listed:
  • Bo Sui

    (Xi’an Jiaotong University)

  • Gen-Fu Feng

    (Xi’an Jiaotong University)

  • Chun-Ping Chang

    (Xi’an Jiaotong University
    Shih Chien University)

Abstract

We investigate the corruption contagion phenomenon using both the spatial econometric model as well as the dynamic panel GMM approach, employing data on 109 countries from 2002 to 2013. The Moran index supports the spatial corruption autocorrelation among sample countries, while the Moran scatter clearly plots a positive relationship between national corruption and corruption of that country’s neighbors. Our empirical evidence not only confirms contagious corruption through geographic boundaries in our sample countries, but that it also spreads out even for countries having similar levels of GDP per capita and democratic institutions. The policy implication is that controlling corruption is not just the responsibility of a specific country, but also a part of synergistic governance worldwide. We also note that similar degrees of income levels and political systems actually play an important role in corruption diffusion, but traditional works unfortunately ignore them.

Suggested Citation

  • Bo Sui & Gen-Fu Feng & Chun-Ping Chang, 2018. "The pioneer evidence of contagious corruption," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 945-968, March.
  • Handle: RePEc:spr:qualqt:v:52:y:2018:i:2:d:10.1007_s11135-017-0497-4
    DOI: 10.1007/s11135-017-0497-4
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    More about this item

    Keywords

    Contagious corruption; Spatial channels; Panel GMM;
    All these keywords.

    JEL classification:

    • P26 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Property Rights
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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