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Forward guidance in climate policy

Author

Listed:
  • Riccardo Degasperi

    (Bank of Italy)

  • Tara Hamadi

    (Queen Mary University of London)

  • Filippo Natoli

    (Bank of Italy)

  • Valerio Nispi Landi

    (Bank of Italy)

  • Kevin Pallara

    (Bank of Italy)

Abstract

We examine the macroeconomic implications of the green transition, focusing on the role of carbon policy. Using high-frequency surprises around regulatory events in the EU Emissions Trading System and a Proxy-SVAR framework, we identify two distinct shocks: one to the current policy stance (current stance shocks) and another to the expected path of the green transition (expected path shocks). Both types of shocks reduce greenhouse gas emissions and economic activity, but differ in their inflationary effects. Current stance shocks raise inflation, while expected path shocks are deflationary. A structural scenario analysis shows that monetary policy easing following a path shock substantially mitigates output losses and moderates the decline in inflation. Moreover, path shocks lower expected growth, depress economic sentiment and increase uncertainty, while also encouraging a reallocation towards greener assets and reducing climate-related risks. These findings align with the predictions of an environmental New Keynesian model. Our results highlight the importance of forward guidance in climate policy, emphasizing its role in shaping macroeconomic expectations and accelerating the transition to a low-carbon economy.

Suggested Citation

  • Riccardo Degasperi & Tara Hamadi & Filippo Natoli & Valerio Nispi Landi & Kevin Pallara, 2026. "Forward guidance in climate policy," Temi di discussione (Economic working papers) 1540, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_1540_26
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    References listed on IDEAS

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    1. Dang, Tam Hoang-Nhat & Nguyen, Canh Phuc & Lee, Gabriel S. & Nguyen, Binh Quang & Le, Thuy Thu, 2023. "Measuring the energy-related uncertainty index," Energy Economics, Elsevier, vol. 124(C).
    2. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    3. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    4. Giovanna Bua & Daniel Kapp & Federico Ramella & Lavinia Rognone, 2024. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," The European Journal of Finance, Taylor & Francis Journals, vol. 30(17), pages 2076-2110, November.
    5. Diego R. Känzig, 2023. "The Unequal Economic Consequences of Carbon Pricing," NBER Working Papers 31221, National Bureau of Economic Research, Inc.
    6. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    7. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    8. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
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    Keywords

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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