Trend Projections of Greenhouse Gas Emission Reduction Potentials : A Bootstrap-Based Nonparametric Efficiency Analysis
We use nonparametric methods to compute the environmental inefficiency of 100 countries over the period 1990-2017 on the macro-level. The inefficiency is expressed as the potential reduction of GHG emissions, holding economic output constant. Based on that, we estimate different trend functions and project the trends further until 2050. Confidence intervals to indicate the uncertainty inherent in the longrun projections are obtained by bootstrapping. We compare the efficient emissions remaining after subtracting the potential reductions with the official EU climate targets. It becomes apparent that a sizable contribution could be made by reducing inefficiency. However, even after removing the entire inefficiency, the results also indicate that this alone is probably not sufficient to break the increasing trend of GHG (and especially CO2) emissions. Thus, further policy measures are required for breaking the trend
Year of publication: |
[2022]
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Authors: | Larissa, Fait ; Krüger, Jens J. ; Tarach, Moritz ; Wetzel, Heike |
Publisher: |
[S.l.] : SSRN |
Subject: | Treibhausgas-Emissionen | Greenhouse gas emissions | Klimawandel | Climate change | Luftverschmutzung | Air pollution | Theorie | Theory | Klimaschutz | Climate protection | Nichtparametrisches Verfahren | Nonparametric statistics | Effizienz | Efficiency | Technische Effizienz | Technical efficiency |
Saved in:
freely available
Extent: | 1 Online-Ressource (30 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 12, 2022 erstellt |
Other identifiers: | 10.2139/ssrn.4107819 [DOI] |
Classification: | Q54 - Climate; Natural Disasters ; E23 - Production ; C14 - Semiparametric and Nonparametric Methods ; C53 - Forecasting and Other Model Applications |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013289121