Relation of economic and environmental indicators to the European Union Emission Trading System: a spatial analysis

Abstract

The main goal of this contribution is to evaluate the development of CO2 emissions and selected economic indicators of EU28 countries in the period from 2005 to 2015, and to capture geographical pattern and spatial distribution of countries emitting pollution. This will be performed within the context of the EU Emissions Trading System (ETS), which has represented a major scheme in Europe to cope with CO2 emissions since 2005. The actual situation in the field of the EU ETS is described and key scientific studies focusing on the EU ETS are presented. Based on a broad set of indicators we examine and evaluate possible geographical pattern in the development of selected indicators within the EU and provide detailed spatial analysis of economic and environmental data of EU28 countries, with the use of (geo)visual analysis of spatial data and spatial statistics (grouping analysis). The preliminary results of the (geo)visual analysis show that CO2 emissions within EU countries were decreasing in the selected period 2005–2015, with some exceptions (e.g. Iceland and Latvia). As the development of CO2 emissions in all EU countries is not similar, the other economic and environmental indicators were included (e.g. GDP, Investments) into the analysis in order to reveal a common (geographical) pattern and explain the current situation. Based on grouping/cluster analysis, it is possible to form territorial groups of EU states with similar development, which are almost perfectly in the line with current EU member states strategies of CO2 emissions trade. The current auction markets are well in tune with geographical and economic characteristics of particular EU countries. Results of grouping analysis of all indicators in 2015 using six K-nearest neighbours underline current separate auction markets for Germany, the United Kingdom and Poland.It indicates that the system of emission auctions has logical background and the markets represent natural platforms for emission trading, corresponding to both economic and spatial characteristics of particular countries/polluters. Presented approach thus brings valuable information for policymakers both on the national and international level for the next phases of EU ETS scheme planning.

Spatial Patterns in Fiscal Impacts of Environmental Taxation in the EU

“…As Jurušs and Brizga (2017) pointed out, politicians rarely take environmental considerations into account, but mostly follow the fiscal aims of the tax and socio-economic arguments trying to balance outside pressure (arising from the European Union environmental policy and acts) and the interests of domestic social partners (business and trade unions). Dealing with EU ETS revenues, some countries are probably better traders and can earn more money from the auctions since the auction prices depend on current demand on the exchange (Pászto and Zimmermannová 2019). According to the significant increase in the price of emission allowances in the period 2018-2020 (from approx.…”

“…The number of neighbors for our purposes was set to be six, and the algorithm searched for them in terms of Euclidean distances (i.e., straight lines between country center points). The choice of this method was based on previous experience and use by the authors (Pászto and Zimmermannová 2019), and also due to the fact that it was necessary to determine the target number of groups (based on non-spatial cluster analysis in the first part). It is important to mention that the cluster analysis takes into account both a spatial component (XY coordinates) and the input indicators' value.…”

“…They analyzed the spatial pattern of emissions changes using clustering analysis of emissions changes at the EU and country-level in the period 2005-2012. Pászto and Zimmermannová (2019) evaluated the development of CO 2 emissions and selected economic indicators of EU-28 countries in the period from 2005 to 2015, capturing the geographical patterns and spatial distribution of countries emitting pollution. Skovgaard et al (2019) explored patterns of adoption (both implemented policies and those scheduled to be) through cluster analysis to investigate factors that could explain policies' decisions to adopt carbon pricing.…”

Assessing the Green Growth Trajectory through Resource and Impact Decoupling Indices: The Case of Poland

“…Third, the EU membership in 2004 [60]. Fourth, the launch of the EU emission trading scheme in 2005 [61]. All the above reflect various elements of Poland's commitment towards sustainable development.…”