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Funding Resilience or Missing the Mark? An Analysis of RRF Allocation and Climate Risk Alignment in Italian Municipalities

Author

Listed:
  • Giulio Breglia

    (Social Sciences Area, Gran Sasso Science Institute)

  • Mariagrazia D’Angeli

    (Department of Economics, Roma Tre University and SEEDS)

  • Giacomo Gazzellone

    (Department of Economics, Roma Tre University)

Abstract

Natural hazards are an increasing concern, placing disaster preparedness and mitigation at the forefront of policy agendas. In this context, Italy’s Recovery and Resilience Plan (NRRP) has allocated €3 billion for explicit disaster prevention, with a primary focus on hydrogeological risks such as floods and landslides. This study evaluates the geographical and thematic distribution of resilience-related funding, examining whether financial resources have been effectively targeted toward municipalities with the highest exposure to environmental hazards. Using a clustering classification, we identify substantial disparities in the allocation of resilience funds, revealing that municipalities with relatively low risk levels often receive disproportionately high funding, while high-risk areas remain underfunded. To explore the underlying drivers of this misalignment, we apply a multinomial logit model to assess the socio-economic and geographic determinants of these funding disparities. Our findings indicate that GDP, macro-regional location, and past disaster occurrences significantly influence whether a municipality falls into a misallocated funding cluster. The misalignment between risk exposure and funding allocation raises questions about the criteria used for distributing adaptation investments and highlights the necessity for a more risk-sensitive and equitable approach.

Suggested Citation

  • Giulio Breglia & Mariagrazia D’Angeli & Giacomo Gazzellone, 2026. "Funding Resilience or Missing the Mark? An Analysis of RRF Allocation and Climate Risk Alignment in Italian Municipalities," Working Papers 2026.08, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2026.08
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    References listed on IDEAS

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    1. Federico Fantechi & Marco Modica, 2023. "Learning from the past: a machine-learning approach for predicting the resilience of locked-in regions after a natural shock," Regional Studies, Taylor & Francis Journals, vol. 57(12), pages 2537-2550, December.
    2. Giulio Breglia & Marco Modica, 2026. "Shifting ground: A counterfactual analysis of recovery in earthquake-affected regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 75(2), pages 1-29, June.
    3. Felbermayr, Gabriel & Gröschl, Jasmin, 2014. "Naturally negative: The growth effects of natural disasters," Journal of Development Economics, Elsevier, vol. 111(C), pages 92-106.
    4. Hallegatte, Stephane & Przyluski, Valentin, 2010. "The economics of natural disasters : concepts and methods," Policy Research Working Paper Series 5507, The World Bank.
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    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • H76 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Other Expenditure Categories
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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