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Global Economic Impacts of Physical Climate Risks on Agriculture and Energy

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  • Roshen Fernando

Abstract

Climate change continues to be an existential threat to humanity. With intrinsic linkages to the natural environment, food and energy supply chains are two fundamental channels via which climate risks could spill over into the economy. This paper explores the global economic consequences of the physical climate impacts on agriculture and energy. Firstly, we construct a range of chronic and extreme climate risk indicators. Secondly, we incorporate those climate risk indicators, alongside the historical data on global agriculture and energy, in machine learning algorithms to estimate the historical responsiveness of agriculture and energy to climate risks. Thirdly, we project agriculture and energy production changes under three Shared Socioeconomic Pathways (SSPs). Finally, the derived shocks are introduced as economic shocks to the G-Cubed model, which is a global multisectoral intertemporal general equilibrium model. We evaluate the G-Cubed model simulation results for various economic variables, including real GDP, consumption, investment, exports and imports, real interest rates, and sectoral production. We observe substantial losses to all economies and adjustments to consumption and investment under the SSPs. The losses worsen with warming. Developing countries are disproportionately affected. However, we observe the potential for double dividends from transitioning to sustainable livestock production and renewable energy sources, preventing further warming and physical damages, and enhancing the resilience of food and energy supply chains to climate risks.

Suggested Citation

  • Roshen Fernando, 2024. "Global Economic Impacts of Physical Climate Risks on Agriculture and Energy," CAMA Working Papers 2024-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2024-37
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2024-06/37_2024_fernando.pdf
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    More about this item

    Keywords

    climate change; extreme events; physical climate risks; macroeconomics; CGE; DSGE; machine learning;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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