Greenhouse Gas Emissions Forecasts in Countries of the European Union by Means of a Multifactor Algorithm

Abstract

A novel multifactor algorithm is developed with the aim of estimating GHG emissions in the EU countries and forecasting different future scenarios. This is created starting from (1) GDP, (2) population and (3) renewable energy share (RES). The determination coefficient (R2) of the multiple regression adopted reaches a value of 0.96; thus, only 4% of the GHG variation cannot be explained by the combination of the three variables. Germany is removed from the model after analysing the statistical outliers, as it presents an unusual behaviour within the European context. Also, France, Italy and Ireland are removed in the forecast analysis since they are characterised by corrected weighting values above the threshold value of the algorithm (0.156). The results show that GHG emissions decrease 14% in a low-growth-rate scenario, increase 24% in an average-growth scenario and increase 104% in a high-growth-rate scenario. Countries that improve the most are the ones that are currently underdeveloped in RES and are expected to decrease their population in the future (Croatia, Latvia, Cyprus and Greece). Other countries currently well positioned but with expected population growth (Sweden, Luxemburg and Denmark) or with expected intense GDP growth (Estonia and Malta) may lack decarbonisation levers. Therefore, policy makers should introduce additional subsidy schemes and tax exemptions in both developed and less developed countries to meet EU decarbonisation targets. © 2023 by the authors.