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The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico

Author

Listed:
  • Daniel Puig

    (UNEP - United Nations Environmental Programme - UNESCO)

  • Oswaldo Morales-Nápoles

    (TNO - The Netherlands Organisation for Applied Scientific Research, TU Delft - Delft University of Technology, TU Delft - Delft University of Technology, Department of Civil Engineering and Geosciences [Delft] - TU Delft - Delft University of Technology)

  • Fatemeh Bakhtiari
  • Gissela Landa

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

Governmental climate change mitigation targets are typically developed with the aid of forecasts of greenhouse-gas emissions. The robustness and credibility of such forecasts depends, among other issues, on the extent to which forecasting approaches can reflect prevailing uncertainties. We apply a transparent and replicable method to quantify the uncertainty associated with projections of gross domestic product growth rates for Mexico, a key driver of greenhouse-gas emissions in the country. We use those projections to produce probabilistic forecasts of greenhouse-gas emissions for Mexico. We contrast our probabilistic forecasts with Mexico's governmental deterministic forecasts. We show that, because they fail to reflect such key uncertainty, deterministic forecasts are ill-suited for use in target-setting processes. We argue that (i) guidelines should be agreed upon, to ensure that governmental forecasts meet certain minimum transparency and quality standards, and (ii) governments should be held accountable for the appropriateness of the forecasting approach applied to prepare governmental forecasts, especially when those forecasts are used to derive climate change mitigation targets.

Suggested Citation

  • Daniel Puig & Oswaldo Morales-Nápoles & Fatemeh Bakhtiari & Gissela Landa, 2017. "The accountability imperative for quantifiying the uncertainty of emission forecasts : evidence from Mexico," Working Papers hal-03389325, HAL.
  • Handle: RePEc:hal:wpaper:hal-03389325
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-03389325
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    1. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    2. Hanea, Anca & Morales Napoles, Oswaldo & Ababei, Dan, 2015. "Non-parametric Bayesian networks: Improving theory and reviewing applications," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 265-284.
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    Cited by:

    1. Daniel Puig & Fatemeh Bakhtiari, 2019. "Incorporating uncertainty in national-level climate change-mitigation policy: possible elements for a research agenda," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 9(1), pages 86-89, March.

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