Институты регулирования регионального развития
The paper discusses problems of regional economy regulation. It exposes the experience of different countries regional development institutions. Moreover, it displays the efficacy assesment of economic policy applied at the level of macroregions. The tools required to pursue the regional macropolicy and to regulate it in terms of economy are investigated.
Purpose – The purpose of this paper is to introduce findings of comparative analysis and various models based on cultural heritage resources to foster regional development.
Design/methodology/approach – Comparison of operational schemes, market positions and branding of three successful cultural heritage centers in Germany, Great Britain and Russia demonstrates a variety of regional development models based on cultural resources and tourism development, and reveals their advantages and disadvantages.
Findings – The paper evidences the potential of cultural resources and the tourism sector as drivers for regional development, and helps formulate basic recommendations for the Russian situation requiring elaboration of adequate financial and social instruments.
Originality/value – The paper provides a complex analysis of different operational models in three European countries with regard to specific national situations and specificity of heritage operational management.
The paper discusses social aspects of higher education institutions engagement with their regional communities. On the basis of the cases of the Russian Siberian and Southern Federal Universities the author analyzes practices and formats of their interaction with different regional stakeholders as part of the FUs' social function implementation. The FU's capacity to enhance their third mission is assessed. The author suggests a set of indicators to assess universities social activities impact on development of the regions, and puts forward recommendations on building the federal universities capacity for fulfilling their third role. The paper is prepared within the framework of the Ministry of Education and Science project "Organizational and analytical support to the national priority project "Education" on activities aimed at "Development of Federal Universities", carried out by the National Training Foundation.
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.