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Data and methods to evaluate climate-related and environmental risks in Italy

Author

Listed:
  • Luciano Lavecchia

    (Bank of Italy)

  • Jacopo Appodia

    (Bank of Italy)

  • Paolo Cantatore

    (Bank of Italy)

  • Rita Cappariello

    (Bank of Italy)

  • Stefano Di Virgilio

    (Bank of Italy)

  • Alberto Felettigh

    (Bank of Italy)

  • Andrea Giustini

    (Bank of Italy)

  • Valeria Guberti

    (Bank of Italy)

  • Danilo Liberati

    (Bank of Italy)

  • Giorgio Meucci

    (Bank of Italy)

  • Stefano Piermattei

    (Bank of Italy)

  • Federico Schimperna

    (Bank of Italy)

  • Katia Specchia

    (IVASS)

Abstract

Monitoring climate-related (and environmental) financial risks requires high quality and highly granular data. However, these are scarcely available, except for little data on a small number of counterparty firms. This paper sheds light on the sustainable data gap in Italy, with a special focus on the climate and environmental components. First, we take stock of the data needs arising from firms’ transition plans, commitments to net zero, and financial analyses, to which the requirements arising from international, European and national regulations, as well as from supervisory demands, were added. Second, we map the existing and available data regarding climate, energy, GHG emissions, climate-related financial risks, as well as existing but inaccessible data. Finally, we highlight any missing data, pointing out the areas that are most affected by the data gap.

Suggested Citation

  • Luciano Lavecchia & Jacopo Appodia & Paolo Cantatore & Rita Cappariello & Stefano Di Virgilio & Alberto Felettigh & Andrea Giustini & Valeria Guberti & Danilo Liberati & Giorgio Meucci & Stefano Pierm, 2022. "Data and methods to evaluate climate-related and environmental risks in Italy," Questioni di Economia e Finanza (Occasional Papers) 732, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:opques:qef_732_22
    as

    Download full text from publisher

    File URL: https://www.bancaditalia.it/pubblicazioni/qef/2022-0732/QEF_732_22_EN.pdf?language_id=1
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    References listed on IDEAS

    as
    1. Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2021. "Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach," Energy Economics, Elsevier, vol. 95(C).
    2. Florian Berg & Julian F Kölbel & Roberto Rigobon, 2022. "Aggregate Confusion: The Divergence of ESG Ratings [Corporate social responsibility and firm risk: theory and empirical evidence]," Review of Finance, European Finance Association, vol. 26(6), pages 1315-1344.
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    4. Timo Busch & Matthew Johnson & Thomas Pioch, 2022. "Corporate carbon performance data: Quo vadis?," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 350-363, February.
    5. Tommaso Loizzo & Federico Schimperna, 2022. "ESG disclosure: regulatory framework and challenges for Italian banks," Questioni di Economia e Finanza (Occasional Papers) 744, Bank of Italy, Economic Research and International Relations Area.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    sustainable data gap; climate change; sustainable finance; physical risk; transition risk; GHG emissions; energy;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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