Международные организации: некоторые проблемы устойчивости и развития
Stimulation of innovation is a priority and a key factor for sustainable economic growth for the leading world economics during the last decade. Innovation became a dominant factor of social and economic evolvement that demands cutting of the period of innovation cycle; strengthening the impact of science on social and economic sphere; significance enhancement of non-economic factors; enlargement of public and corporative expenditures on research, technological and innovation development; globalization and integration of trans-national innovation processes. Global financial and economic crisis and its consequences brought to a head the necessity to speed up innovation at the level of companies, economic segments and national economics as a whole. In this respect development of integration processes and creation of common innovation strategies for grouping of states such as the EU and CIS, as well as for independent governments and companies becomes the crucial approach to enhance their competitiveness in the world economic area. The decision on development of Intergovernmental Target Programme for Innovation Cooperation of Commonwealth Independent States until 2020 was made by the Heads of the CIS Governments on November 14, 2008. The paper sets to analyze the document’s main goals and objectives, its content, the process of its development and possible implementation paths.
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.