Assessing the EU ETS with a bottom-up, multi-sector model. (21st April 2018)

• Record Type: Journal Article
• Authors: Pintos, Pablo; Linares, Pedro
• Is Part Of: Climate policy. Volume 18:Number 4(2018)
• Page Start: 413
• Page End: 424
• Publication Date: 2018-04-21
• Subjects: abatement costs -- company behaviour -- emissions pricing -- EU Emissions Trading Scheme -- industrial emissions; Q31 -- Q37 -- Q48 -- Q56 -- Q58; 363.7
• DOI: 10.1080/14693062.2017.1294045
• Languages: English
• ISSNs: 1469-3062

Abstract

ABSTRACT: The European Emissions Trading System (EU ETS) is the central pillar of the EU response against climate change. This trading mechanism is considered, from the theoretical point of view, as the most cost-effective method to reduce GHG. However, previous studies show that the agents who participate in these markets may behave in a way that may lead to inefficient CO2 prices, creating doubts about the static and dynamic efficiency of the system. This article analyses these possible anomalies by first trying to model the ETS in a more realistic way, addressing some of the limitations of previous models, and second, by comparing the results with real market transactions. For this, a bottom-up, multi-sector model has been built, which represents the EU ETS in an integrated, cross-sectoral way, paying particular attention to the interactions among the most emissions intensive industries. The results show the benefits of this modelling approach and how it better reflects real market conditions. Some preliminary conclusions regarding the behaviour of the agents in the ETS market are also presented. POLICY RELEVANCE Low allowance prices in the EU ETS have put into question the dynamic efficiency of the EU ETS system, prompting various ideas for structural reform. However, determining the right reform also requires estimating correctly how agents will respond to it. This article proposes a tool to realistically simulate the EU ETS under the assumption of rational agents, and compare it to real market outcomes, in order to understand better the behaviour of agents in this carbon market, and therefore how to design better policies.