Региональная интеграция на севере Европы
This chapter proposes an unfolding view of the EU as a sort of post-modern neo-medieval empire, in which narratives of othering towards Central and Eastern Europe preserve their salience.
The article analyses the EU activity in assisting developing countries to develop energy sector throughperspective of the functional approach. The author identifies the EU approach by assessing EU compliance with the G8 commitments on assisting developing countries to develop energy sector. The assessment is made on the basis of the analysis of EU implementation of its commitments made in four major spheres of international engagement for energy development, such as ensuring developing countries’ access to modern energy sources, clean energy development, raw natural energy resources, sustainable management and environmental protection. In order to ensure comprehensive and unbiased assessment the author applies the methodology of global governance delivery function approach and compares EU compliance with compliance of other traditional donors such as USA and emerging donors such as Russia. In conclusion some recommendations on how to raise effectiveness in assisting developing countries to develop energy sector are made for the Russian Federation.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.