Прогноз научно-технологического развития России: 2030. Энергоэффективность и энергосбережение
In the past decades Foresight has been significantly developed as a tool for long-term forecasting in the field of power generation and energy efficiency. Such research aims at investigation of the most promising innovation strategies in this area, identifying various (including alternative) ways to achieve technological and market goals with the participation of best qualified experts. Such Foresight method as Roadmapping is widespread in the world practice. It helps to shape complex and interrelated views on prospects of innovation development in specific areas of energy efficiency, it links R&D programmes with creation of technologies and products, as well as their subsequent commercialization. The paper provides an overview of the world Foresight experience aimed at creating vision of the future and building innovation strategies related to energy efficiency. Special attention is paid to the Russian research practice, in particular to different types of Foresight projects implemented by the specialists of State University - Higher School of Economics. The authors describe the results of main projects dedicated to shape the future of energy-efficient technologies and to develop of innovation strategies on their application.
The given study is devoted to the issues of searching the ways for adaptation to climate change, mitigation of its impact on the economy and population, as well as to the role of increasing energy efficiency in the economies of some countries of Eastern Europe, Caucasus and Central Asia (EECCA). It also relates to the issues of responding to negative trends and emerging challenges caused by climate change. The Report represents several case studies on the above topics implemented in Moldova, Tadjikistan, Kazakhstan, Azerbaijan and the Russian Federation by the network of regional enviuronmental centres. It also contains consideration of possible methodological approaches and recommendations on addressing the above issues in the EECCA region.
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.