Impacts of energy taxation in the enlarged European Union, evaluation with GEM-E3 Europe

The objective of this study is twofold: first to analyze how the implementation of the EU energy tax policies will affect the EU and its Member States and secondly to analyze how energy tax policies can contribute to climate policy objectives in the enlarged EU.

Development and Application of a Methodology to Identify Projects of Energy Community Interest

Projects of Energy Community Interest” (PECIs) is a label attached to those projects which have the highest positive impact in the largest possible number of Contracting Parties. The assessment of one hundred projects submitted as candidates, and final selection of 35 PECIs was achieved in a collaborative process undertaken by the same Task Force that contributed to the preparation of the Energy Strategy. Chaired by the European Commission, the Task Force was facilitated by the Energy Community Secretariat and benefited from technical assistance of a Consultant sponsored from the Energy Community budget.

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).

Analyzing interrelated stochastic trend and seasonality on the example of energy trading data

The correct modelling of long- and short-term seasonality is a very interesting issue. The choice between the deterministic and stochastic modelling of trend and seasonality and their implications are as relevant as the case of deterministic and stochastic trends itself. The study considers the special case when the stochastic trend and seasonality do not evolve independently and the usual differencing filters do not apply. The results are applied to the day-ahead (spot) trading data of some main European energy exchanges (power and natural gas).