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Corruption in space: A closer look at the world's subnations

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  • Borsky, Stefan
  • Kalkschmied, Katja
Abstract
Corruption levels differ not only between but also within countries. In this paper we analyze spatial interdependencies in corruption levels for a large sample of 1232 subnational regions from 81 countries. Based on a spatial autoregressive model, which controls for country-fixed effects and corrects for spatial autocorrelation in the error term, we find that a subnational region's corruption level is positively correlated with neighboring subnational regions' corruption levels. Extending the core model and allowing for heterogeneous spatial effects, we find that most spillovers among subnational regions occur within national borders. Moreover, in particular high income subnational regions and subnational regions with relative low corruption levels tend to spill in space. This is due to their high degree of connectivity in terms of economic, sociocultural and political exchange with other subnational regions. Our estimation results underline the importance to consider not only a subnational region's own characteristics, but also spatial interdependencies when implementing efficient anti-corruption policies at the local level.

Suggested Citation

  • Borsky, Stefan & Kalkschmied, Katja, 2019. "Corruption in space: A closer look at the world's subnations," European Journal of Political Economy, Elsevier, vol. 59(C), pages 400-422.
    • Handle: RePEc:eee:poleco:v:59:y:2019:i:c:p:400-422
    DOI: 10.1016/j.ejpoleco.2019.05.004
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    2. Gründler, Klaus & Potrafke, Niklas, 2019. "Corruption and economic growth: New empirical evidence," European Journal of Political Economy, Elsevier, vol. 60(C).
    3. Meierrieks, Daniel & Auer, Daniel, 2022. "Bribes and Bombs: The Effect of Corruption on Terrorism," VfS Annual Conference 2022 (Basel): Big Data in Economics 264084, Verein für Socialpolitik / German Economic Association.
    4. Kshitiz Shrestha & Jorge Martinez‐Vazquez & Charles Hankla, 2023. "Political decentralization and corruption: Exploring the conditional role of parties," Economics and Politics, Wiley Blackwell, vol. 35(1), pages 411-439, March.
    5. Bo Sui & Chun-Ping Chang & Yin Chu, 2021. "Political Stability: an Impetus for Spatial Environmental Spillovers," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 387-415, June.
    6. François, Abel & Méon, Pierre-Guillaume, 2021. "Politicians at higher levels of government are perceived as more corrupt," European Journal of Political Economy, Elsevier, vol. 67(C).
    7. Sajad Rahimian, 2021. "Corruption Determinants, Geography, and Model Uncertainty," Papers 2105.12878, arXiv.org.
    8. Goel, Rajeev K. & Saunoris, James W., 2022. "Corrupt thy neighbor? New evidence of corruption contagion from bordering nations," Journal of Policy Modeling, Elsevier, vol. 44(3), pages 635-652.
    9. Masoud Khodapanah & Zahra Dehghan Shabani & Mohammad Hadi Akbarzadeh & Mahboubeh Shojaeian, 2022. "Spatial spillover effects of corruption in Asian countries: Spatial econometric approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(4), pages 699-717, August.

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    More about this item

    Keywords

    Subnational corruption; Spatial econometrics; Heterogeneous spatial effects;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • P48 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Legal Institutions; Property Rights; Natural Resources; Energy; Environment; Regional Studies

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