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Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions

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  • Pretis, Felix

Abstract

Estimates of both the human impact on climate as well as the economic impacts of climate change are crucial to inform policy decisions. Econometric modelling allows us to quantify these impacts and their uncertainties, but models have to be consistent with the underlying physics and the time series properties of the data. Here I show that energy-balance models of climate are equivalent to an econometric cointegrated system and can be estimated in discrete time. This equivalence provides a basis for the use of cointegration methods to estimate climate responses and test their feedback. Further, it is possible to use the estimated parameters to quantify uncertainties in integrated assessment models of the economic impacts of climate change. In an application I estimate a system of temperatures, ocean heat content, and radiative forcing including greenhouse gases, and find statistical support for the cointegrated energy balance model. Accounting for structural breaks from volcanic eruptions highlights large parameter uncertainties and shows that previous empirical estimates of the temperature response to increased CO2 concentrations may be misleadingly low due to model-misspecification.

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  • Pretis, Felix, 2020. "Econometric modelling of climate systems: The equivalence of energy balance models and cointegrated vector autoregressions," Journal of Econometrics, Elsevier, vol. 214(1), pages 256-273.
  • Handle: RePEc:eee:econom:v:214:y:2020:i:1:p:256-273
    DOI: 10.1016/j.jeconom.2019.05.013
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    3. Liang Chen & Juan J. Dolado & Jesús Gonzalo & Andrey Ramos, 2023. "Heterogeneous predictive association of CO2 with global warming," Economica, London School of Economics and Political Science, vol. 90(360), pages 1397-1421, October.
    4. Johansen, Søren & Nielsen, Morten Ørregaard, 2018. "The cointegrated vector autoregressive model with general deterministic terms," Journal of Econometrics, Elsevier, vol. 202(2), pages 214-229.
    5. G. Cornelis van Kooten & Mark E. Eiswerth & Jonathon Izett & Alyssa R. Russell, 2021. "Climate Change and the Social Cost of Carbon: DICE Explained and Expanded," Working Papers 2021-01, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    6. Neil R. Ericsson, 2021. "Dynamic Econometrics in Action: A Biography of David F. Hendry," International Finance Discussion Papers 1311, Board of Governors of the Federal Reserve System (U.S.).
    7. Carrion-i-Silvestre, Josep Lluís & Kim, Dukpa, 2021. "Statistical tests of a simple energy balance equation in a synthetic model of cotrending and cointegration," Journal of Econometrics, Elsevier, vol. 224(1), pages 22-38.
    8. Bruns, Stephan B. & Csereklyei, Zsuzsanna & Stern, David I., 2020. "A multicointegration model of global climate change," Journal of Econometrics, Elsevier, vol. 214(1), pages 175-197.
    9. Xu, Xin & Huang, Shupei & Lucey, Brian M. & An, Haizhong, 2023. "The impacts of climate policy uncertainty on stock markets: Comparison between China and the US," International Review of Financial Analysis, Elsevier, vol. 88(C).
    10. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    11. Chen, Li & Gao, Jiti & Vahid, Farshid, 2022. "Global temperatures and greenhouse gases: A common features approach," Journal of Econometrics, Elsevier, vol. 230(2), pages 240-254.
    12. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    13. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    14. Bento, Antonio M. & Miller, Noah & Mookerjee, Mehreen & Severnini, Edson R., 2020. "A Unifying Approach to Measuring Climate Change Impacts and Adaptation," IZA Discussion Papers 13290, Institute of Labor Economics (IZA).
    15. Marina Friedrich & Luca Margaritella & Stephan Smeekes, 2023. "High-Dimensional Causality for Climatic Attribution," Papers 2302.03996, arXiv.org.
    16. Andrés Fortunato & Helmut Herwartz & Ramón E. López & Eugenio Figueroa B., 2022. "Carbon dioxide atmospheric concentration and hydrometeorological disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 57-74, May.
    17. Hildegart Ahumada & Magdalena Cornejo, 2020. "The effect of Amazon deforestation on global climate variables," Asociación Argentina de Economía Política: Working Papers 4332, Asociación Argentina de Economía Política.
    18. Robert K. Kaufmann & Felix Pretis, 2023. "An empirical estimate for the snow albedo feedback effect," Climatic Change, Springer, vol. 176(8), pages 1-20, August.
    19. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "On Spurious Causality, CO2, and Global Temperature," Papers 2103.10605, arXiv.org.
    20. Tobias Adrian & Nina Boyarchenko & Domenico Giannone & Ananthakrishnan Prasad & Dulani Seneviratne & Yanzhe Xiao, 2022. "800,000 Years of Climate Risk," Staff Reports 1031, Federal Reserve Bank of New York.
    21. David B. Stephenson & Alemtsehai A. Turasie & Donald P. Cummins, 2023. "More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    22. Felix Pretis, 2022. "Does a Carbon Tax Reduce CO2 Emissions? Evidence from British Columbia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 115-144, September.
    23. Manveer Kaur Mangat & Erhard Reschenhofer, 2020. "Frequency-Domain Evidence for Climate Change," Econometrics, MDPI, vol. 8(3), pages 1-15, July.
    24. Pretis, Felix, 2021. "Exogeneity in climate econometrics," Energy Economics, Elsevier, vol. 96(C).
    25. Giselle Montamat & James H. Stock, 2020. "Quasi-experimental estimates of the transient climate response using observational data," Climatic Change, Springer, vol. 160(3), pages 361-371, June.

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    More about this item

    Keywords

    Cointegration; Vector autoregression; Climate; Energy balance; Indicator saturation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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