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Forest Fires Across Italian Regions and Implications for Climate Change: A Panel Data Analysis

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  • Melania Michetti

    (Centro Euro-mediterraneo sui Cambiamenti Climatici (CMCC))

  • Mehmet Pinar

    (Edge Hill University)

Abstract

In this paper, we analyze the determinants of monthly variations in forest fire frequency and on the size of the area burnt for Italian regions between 2000 and 2011. We employ panel data techniques, which allow capturing the dynamics of fire danger due to changes in past climatic conditions, after accounting for regional fixed effects to control region-specific unobserved and time-invariant factors. Results highlight a significant heterogeneity of the effects of driving factors across the Italian peninsula and weather seasons. Climatic conditions also show lasting effects within the year. Using climate change projections for 2016–2035, we then obtain the projected forest fire frequency and total area burnt across the Italian peninsula for the same period. Climate change is expected to increase the number of forest fires across the whole peninsula, which is more evident for the central part of Italy. Even though most of annual increases in fire events relate to the summer period, intensifications in frequency during autumn become more evident in the southern Italy. We extend finally our analysis to investigate the contribution of socio-economic factors to fire regime and the role of education and the containment of fraudulent activity is also highlighted.

Suggested Citation

  • Melania Michetti & Mehmet Pinar, 2019. "Forest Fires Across Italian Regions and Implications for Climate Change: A Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 207-246, January.
  • Handle: RePEc:kap:enreec:v:72:y:2019:i:1:d:10.1007_s10640-018-0279-z
    DOI: 10.1007/s10640-018-0279-z
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    Cited by:

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    3. Jaime de Diego & Antonio Rúa & Mercedes Fernández, 2021. "Vulnerability Variables and Their Effect on Wildfires in Galicia (Spain). A Panel Data Analysis," Land, MDPI, vol. 10(10), pages 1-17, September.
    4. Elettra Agliardi & Anastasios Xepapadeas, 2019. "Introduction: Special Issue on the Economics of Climate Change and Sustainability," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 1-4, January.
    5. Maria Lanfredi & Rosa Coluzzi & Vito Imbrenda & Bogdana Nosova & Massimiliano Giacalone & Rosario Turco & Marcela Prokopovà & Luca Salvati, 2023. "In-between Environmental Sustainability and Economic Viability: An Analysis of the State, Regulations, and Future of Italian Forestry Sector," Land, MDPI, vol. 12(5), pages 1-21, May.
    6. Alessandra Canepa, 2024. "Socio-economic risk factors and wildfire crime in Italy: a quantile panel approach," Empirical Economics, Springer, vol. 66(1), pages 431-465, January.
    7. Thiago Morello, 2023. "An Agri-environmental Scheme for Reducing Inputs Subjected to Accidental Spillage: An Application to Agricultural Burnings by Smallholders," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(2), pages 383-408, February.
    8. Gianluigi Busico & Elisabetta Giuditta & Nerantzis Kazakis & Nicolò Colombani, 2019. "A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    9. Canepa, Alessandra & Drogo, Federico, 2021. "Wildfire crime, apprehension and social vulnerability in Italy," Forest Policy and Economics, Elsevier, vol. 122(C).
    10. Canepa,Alessandra & Drogo,Federico, 2019. "Wildfire Crime and Social Vulnerability in Italy: A Panel Investigation," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202005, University of Turin.

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    More about this item

    Keywords

    Forest fires; Forestry; Climate change; Panel-data estimation;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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