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Lost in Corruption. Evidence from EU Funding to Southern Italy

Author

Listed:
  • Ilaria Angelis

    (Bank of Italy, DG Economics, Statistics and Research, Structural Economic Analysis Directorate)

  • Guido Blasio

    (Bank of Italy, DG Economics, Statistics and Research, Structural Economic Analysis Directorate)

  • Lucia Rizzica

    (Bank of Italy, DG Economics, Statistics and Research, Structural Economic Analysis Directorate)

Abstract

Windfall government revenues may generate an increase in the occurrence of corruption by reducing the degree of political accountability. This paper empirically investigates the relationship between the accrual of large financial transfers from a central level of government and the incidence of corruption at the local level. To this purpose we analyze the case of EU funding to Southern Italy and exploit within municipality variation in the flow of funds between 2007 and 2014. Our estimates show a statistically significant positive effect of transfers on corruption crimes: in the absence of EU funds disbursements the yearly number of white collar crimes in the South of Italy would have been 4% lower.

Suggested Citation

  • Ilaria Angelis & Guido Blasio & Lucia Rizzica, 2020. "Lost in Corruption. Evidence from EU Funding to Southern Italy," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 355-377, July.
    • Handle: RePEc:spr:italej:v:6:y:2020:i:2:d:10.1007_s40797-020-00123-2
    DOI: 10.1007/s40797-020-00123-2
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    Cited by:

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    2. Cerqua, A. & Ferrante, C. & Letta, M., 2021. "Electoral Earthquake: Natural Disasters and the Geography of Discontent," GLO Discussion Paper Series 790, Global Labor Organization (GLO).
    3. Audinga Baltrunaite & Tommaso Orlando & Gabriele Rovigatti, 2021. "The implementation of public works in Italy: institutional features and regional characteristics," Questioni di Economia e Finanza (Occasional Papers) 659, Bank of Italy, Economic Research and International Relations Area.
    4. Guido de Blasio & Alessio D'Ignazio & Marco Letta, 2020. "Predicting Corruption Crimes with Machine Learning. A Study for the Italian Municipalities," Working Papers 16/20, Sapienza University of Rome, DISS.
    5. Deiana, Claudio & Geraci, Andrea, 2021. "Are wind turbines a mafia windfall? The unintended consequences of green incentives," Regional Science and Urban Economics, Elsevier, vol. 89(C).
    6. Tancredi Buscemi & Giulia Romani, 2022. "Allocation of authority and tactical redistribution of public investments: A historical quasi-experiment," Working Papers 2022:18, Department of Economics, University of Venice "Ca' Foscari", revised 2024.
    7. Paolo Pinotti, 0. "The Credibility Revolution in the Empirical Analysis of Crime," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 0, pages 1-14.
    8. Giuseppe Albanese & Guglielmo Barone & Guido de Blasio, 2023. "The impact of place‐based policies on interpersonal income inequality," Economica, London School of Economics and Political Science, vol. 90(358), pages 508-530, April.
    9. de Blasio, Guido & D'Ignazio, Alessio & Letta, Marco, 2022. "Gotham city. Predicting ‘corrupted’ municipalities with machine learning," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Paolo Pinotti, 2020. "The Credibility Revolution in the Empirical Analysis of Crime," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 207-220, July.
    11. Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2021. "A Machine Learning Approach to Analyze and Support Anti-Corruption Policy," CESifo Working Paper Series 9015, CESifo.
    12. Giuseppe Albanese & Guglielmo Barone & Guido DeBlasio, 2021. "The impact of place-based policies on income distribution," Discussion Paper series in Regional Science & Economic Geography 2021-04, Gran Sasso Science Institute, Social Sciences, revised Mar 2021.

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    More about this item

    Keywords

    Regional transfers; Corruption; EU funds;
    All these keywords.

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents
    • H7 - Public Economics - - State and Local Government; Intergovernmental Relations

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