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Redefining the degree of industry greenness using input–output tables

Author

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  • Penikas, Henry
  • Vasilyeva, Ekaterina

Abstract

Climate risk is a novel exposure that may rock the financial stability world-wide. For this reason the world banking regulation standards-setter – the Basel Committee on Banking Supervision (BCBS) – suggested considering pricing in the climate risk and adopting its relevant regulation. It listed input–output tables as one of the key tools to measure the climate riskiness of a borrower. However, most of the prior research considered carbon dioxide emissions when applying input–output tables. Same time there is a significant volume of research focusing on climate (or environmental) risk ratings. Nevertheless, both approaches might present only part of the larger climate-related financial risk implications. That is why, our research purpose is to develop full climate risk estimate by leveraging on the input–output tables and climate risk ratings. By doing so, we intend to demonstrate when the existing approaches yield sufficient information to make financial risk-related decision and when those should be improved by considering full climate risk justified in the current paper. The novelty of this work is the amalgamation of a known data source on environmental (climate) risk scores from Sustainalytics.com with the world input–output database (WIOD) for 2000–2014. The major finding of ours is that the greenness of industries is materially perturbed when considering WIOD-based full climate risk estimates as follows from an equivalent to the Leontief full production costs. We specifically find that aluminium as a commodity occurs much’browner’ from full climate risk perspective, than it seems from the marginal climate risk one. Hence, the steps taken by Australia to reduce aluminium production are necessary, but not sufficient. For the global welfare China has adopt a negative emission target (i.e., reduce more carbon dioxide, than is produced) to attain the objective of noticeable improvement in the global carbon footprint, particularly the one related to aluminium production. Our results are solicited by the Central Banks to accurately design the specialized lending facilities to truly green industries and projects.

Suggested Citation

  • Penikas, Henry & Vasilyeva, Ekaterina, 2024. "Redefining the degree of industry greenness using input–output tables," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1073-1090.
  • Handle: RePEc:eee:reveco:v:89:y:2024:i:pa:p:1073-1090
    DOI: 10.1016/j.iref.2023.08.008
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    Keywords

    Sustainalytics; Climate risk; Input–output; Poisson regression; Aluminium; Australia; China; Negative emission goal;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth

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