GDP and employment effects of policies to close the 2020 emissions gap

Terry Barker, Eva Alexandri, Jean-Francois Mercure (), Yuki Ogawa and Hector Pollitt

Climate Policy, 2016, vol. 16, issue 4, 393-414

Abstract: Four policies might close the gap between the global GHG emissions expected for 2020 on the basis of current (2013) policies and the reduced emissions that will be needed if the long-term global temperature increase can be kept below the 2 °C internationally agreed limit. The four policies are (1) specific energy efficiency measures, (2) closure of the least-efficient coal-fired power plants, (3) minimizing methane emissions from upstream oil and gas production, and (4) accelerating the (partial) phase-out of subsidies to fossil-fuel consumption. In this article we test the hypothesis of the International Energy Agency (IEA) that these policies will not result in a loss of gross domestic product (GDP) and we estimate their employment effects using the E3MG global macro-econometric model. Using a set of scenarios we assess each policy individually and then consider the outcomes if all four policies were implemented simultaneously. We find that the policies are insufficient to close the emissions gap, with an overall emission reduction that is 30% less than that found by the IEA. World GDP is 0.5% higher in 2020, with about 6 million net jobs created by 2020 and unemployment reduced. Policy relevance The gap between GHG emissions expected under the Copenhagen and Cancun Agreements and that needed for emissions trajectories to have a reasonable chance of reaching the 2 °C target requires additional policies if it is to be closed. This article uses a global simulation model E3MG to analyse a set of policies proposed by the IEA to close the gap and assesses their macroeconomic effects as well as their feasibility in closing the gap. It complements the IEA assessment by estimating the GDP and employment implications separately by the different policies year by year to 2020, by major industries, and by 21 world regions.

Date: 2016
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Citations: View citations in EconPapers (15)

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DOI: 10.1080/14693062.2014.1003774

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