Качество городской среды как фактор устойчивого развития муниципальных образований
The article discusses the concept of the creative city and its application in Russian cities. On the examples of Obvodny Kanal area and New Holland Island in St. Pe- tersburg the possible consequences of the creative spaces development are analyzed: social segregation, elitism and the increasing importance of the cultural consump- tion as a segregational practice.
The article present of a model of sustainable development of the largest companies in the region and in the territory. The model allows evaluating the sustainable character of a company's development through comparison of the planned and real data, and to discover its non-balanced dynamics.
The article discusses the issues of sustainable development. The implementation of the sustainable development concept involves the integration of different levels of government and bringing the approach to the level of business and individual projects.A company may have a different degree of economic stability, the measurement of which can be accomplished through the analysis of the cost structure of the product sold, including the costs of maintaining the environment. Evaluation of the project can be carried out taking into account the levels of initiation and levels of its impact on sustainable development. We propose a method of evaluation that allows taking into account all three aspects: economic, social and environmental.In the process of assessing the sustainability of the project it is advisable to take into account the full life cycle.The article shows how to take into account the parameters that characterize the activity and the product produced by the asset. By themselves, the project or the circumstances of its implementation could result in your loss of stability of the system in which it is located. It is recommended to evaluate the loss of stability in private terms, and as a whole for the project — based on the calculation of the integral indicator.
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.