Conference Agenda

The European Union Emissions Trading System (EU ETS) has become the cornerstone of the European Union’s strategy to decarbonize the economy and mitigate climate change. Following these objectives, the aim of this paper is to assess the impact

of the price of carbon, which is linked to the European market of allowances, on carbon

dioxide emissions. To do so, we propose an econometric model that extends the Environmental Kuznets Curve (EKC) model in several directions. First, the price of carbon,

which is the policy variable, is introduced in the model in a nonparametric fashion;

Second, we propose to use an interactive fixed effects approach to control for latent

heterogeneities in both dimensions of panel data; Third, to allow for spatial dependence, we introduced spatially correlated errors. The extended EKC model presents

several challenges from the estimation point of view. To cope with them, using a profile likelihood approach, we propose a Feasible Generalized Least Squares estimator

of the parameters of interest. Furthermore, the policy effects curve is also efficiently

estimated. The asymptotic properties of the estimators are shown and, based on these

outcomes, we empirically evaluate the policy effects. It turns out that our approach

provides results that differ significantly and are more meaningful with respect to those

obtained using standard estimation techniques.

We study the impact of the 2022-2023 energy crisis in Germany. We collect 3 waves of panel data to measure how political attitudes change with increasing energy prices for households. Our difference-in-differences estimation exploits unique features of the German energy sector, which allows for a quasi-experimental design. We show that increases in electricity payments lead to a decline in support for democratic institutions, with effects intensifying over time. The study sheds light on the consequences of economic shocks on political attitudes and has implications for the design of stringent climate policies.

The success of climate policies depends crucially on the dynamics of public support. Using unique longitudinal data from three surveys conducted between 2019 and 2022, we study the variations of public support for carbon pricing in Germany. The period includes two relevant events: the introduction and ramping up of carbon pricing in Germany and the exogenous increase in energy prices following the Russian invasion of Ukraine. Using panel methods, we show that support is very persistent over time and might have increased slightly more recently. However, people who experience high energy costs display a lower support. Regarding revenue use, we detect that social cushioning has become more popular over time. Our findings suggest that it is crucial to gather enough support before implementing climate policies.

The economic and climate effectiveness of the EU Emission Trading Scheme (EU ETS) are central for the achievement of the EU's objective of carbon neutrality by 2050. This paper contributes to the literature evaluating this scheme by examining the relationship between regulated firms' emission behavior and their economic outcomes taking international competition dynamics into account. We construct a dataset covering around 1,200 firms covered by the EU ETS during the entirety of its third phase and estimate a novel indicator of volume-based emission intensities for these firms. We apply an IV approach to a fixed-effects panel model and find that companies that reduced their emission intensity experienced either no change or a small but significant increase in their economic performance. When we explicitly control for the competitive environment they operate in, this result remains robust, suggesting that leakage mitigation measures have been effective for sectors at high risk of carbon leakage and that firms generally were not negatively impacted by the higher carbon prices observed in the EU ETS' third phase.