Форсайт – сценарий правильного Будущего
The issue of capital city relocation is a topic of debate for more than forty countries around the world. In this first book to discuss the issue, Vadim Rossman offers an in-depth analysis of the subject, highlighting the global trends and the key factors that motivate different countries to consider such projects, analyzing the outcomes and drawing lessons from recent capital city transfers worldwide for governments and policy-makers.
Modern urban performance depends not only on the city's endorsement of hard infrastructure (physical capital), but also on the availability and quality of knowledge communication and social infrastructure (intellectual capital and social capital). This is one of the clear reasons why the concept of Smart Cities recently attracted a great amount of attention, both from academia and city planners. One of the challenges of the Smart City concept is how to raise human capital among people, such as making them culturally sensitive, mobile and to improve other social characteristics. This challenge is especially valid for industrial cities that are facing economic turbulence and a demand for revitalizing their public spaces and economic specialties. The aim of this study is to examine the correlation between the amount of international students in Russian universities with the positive changes that occur in a Russian student’s human capital, and their neighbourhood areas, especially in public spaces. We aim to support the hypothesis that a network of “internationalized” universities serves as a revitalization measure for a city, facilitating the development of its surrounding areas, and reducing political and social risks within a society. Research methods for gathering data are: deductive trend search, which uses a literature review from leading academic journals and the empirical study based on the created questionnaire. This questionnaire forms a dataset which consists of a number of master courses held in English from one of the leading Russian universities based in Moscow. In this paper, we explain the research design and the results of a long-term project which we expect to complete in Russia in 2016.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
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.