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The accountability imperative for quantifying the uncertainty of emission forecasts: Evidence from Mexico

Abstract : Governmental climate change mitigation targets are typically developed with the aid of forecasts of greenhouse-gas (GHG) 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 GHG emissions in the country. We use those projections to produce probabilistic forecasts of GHG 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.
Keywords : Climate CO2 emissions
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Submitted on : Sunday, October 24, 2021 - 5:09:59 AM
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Fatemeh Bakhtiari, Gissela Landa, Oswaldo Morales-Nápoles, Daniel Puig. The accountability imperative for quantifying the uncertainty of emission forecasts: Evidence from Mexico. Climate Policy, Taylor & Francis, 2018, 18 (6), pp.742 - 751. ⟨10.1080/14693062.2017.1373623⟩. ⟨hal-03399622⟩

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