
Ikusi/ Ireki
Izenburua
EU ETS CO2 emissions constraints and business performance: a quantile regression approachEgilea
Departamentua
Business Data AnayticsBeste erakundeak
https://ror.org/012a91z28Bertsioa
PreprintaDokumentu-mota
ArtikuluaHizkuntza
IngelesaEskubideak
© 2014 The Authors. Published by Taylor & FrancisSarbidea
Sarbide irekiaArgitaratzailearen bertsioa
https://doi.org/10.1080/13504851.2013.844316Non argitaratua
Applied Economic Letters Vol. 21, issue 2Lehenengo orria
129Azken orria
134Argitaratzailea
Taylor & FrancisGako-hitzak
Environmental economicsCarbon finance
Quantile regresion
EU ETS
Gaia (UNESCO Tesauroa)
Ingurumen-ekonomiaLaburpena
The European Union Emissions Trading Scheme (EU ETS) is the first and largest international scheme for the trading of greenhouse gas emission allowances (European Union Allowances (EUA)). Considering ... [+]
The European Union Emissions Trading Scheme (EU ETS) is the first and largest international scheme for the trading of greenhouse gas emission allowances (European Union Allowances (EUA)). Considering that the global economic crisis is hurting corporate profits, analysing the implications of CO2 emissions constraints for company business performance (BP) is a crucial task for both policymakers and companies. In this context, we analyse the relationship between surplus of allowances (SA) and BP in Spanish firms during the period 2005 to 2010. Using quantile regression techniques that provide a more complete picture of the relationship between the analysed variables, we draw two conclusions. First, an increase in company activity effectiveness led to a decrease in SA, indicating that activity effectiveness was not linked to good environmental performance, in terms of wasting the minimum number of allowances. Second, a decrease in SA, i.e., buying more or selling less EUAs is linked to an increase in company profitability. This provides evidence that the price of EUA was not sufficiently high to create a cost advantage for firms reducing their emissions. Based on our results, two policy measures are proposed. [-]


















