Государственная политика РФ по развитию крупных городских агломераций и проблемы ее реализации
The article discusses the development of agglomerations as "points of growth" as applied to the modern economy of Russia, analyzes approaches to the management of the process of agglomeration growth. SWOT-analysis was carried out in the formation of agglomerations in the Russian Federation. It is shown that the state encourage the development of agglomerations can be implemented within the overall strategy of spatial and economic development of the country by creating objects of the innovation economy, improve regional cohesion and quality of life, infrastructure development.
The current lack of a unified indicators system to evaluate the innovation activity at the rigional level makes it nessesary to develop methodology for assessing the innovative capacity of the region. It should include appoaches related to the formal and substantive analysis to identify the factors that influence the innovative capacity of the region, as well as expert evaluation to rank the factors identified.
In article the system of indicators of an estimation of use of social and economic potential of region, approaches to its forecasting and maintenance of unity of received estimations are considered.
In Soviet period absence of market prices led to extremely inefficient land use and spatial development of cities. Centralized planning system was not flexible and responsive to changing demand, preoccupied with minimization of construction costs and characterized by very low density of land use. In 20 years after the beginning of market economic reforms and mass privatization of real property the situation in land use and spatial development of Russian cities didn’t change much. Main reasons of this are: unclear, non-specified and often not registered property rights; quasi-monopoly of the state on urban lands; absence of clear distinction between federal, regional and municipal lands; high transaction costs and administrative barriers for developers; still very much administrative approach to planning and land use regulation, absence of real dialog with community development groups and NGOs. In this legal and institutional environment regional and/or local authorities often act in interests of big and influential investors and developers, scarifying interests of community as well as of small private owners and tenants. As a result we can see a further worsening of the urban environment, decreasing of green areas, disappearance of historical character of whole parts of city centers, sprawl developments in suburbia etc.
To measure transaction costs and administrative risks in urban development and construction, a survey of developers, builders and real estate agents was undertaken in St Petersburg and Leningrad region, the results of which are presented in the paper.
Labor productivity is the most important factor in the economic growth of the region. Traditional production functions assess the contribution of labor resources to three-fourths of the total one. But today there are new factors, the inclusion of which in the model is necessary, since they determine the key forces of economic development, identify the direction of regional policy.
Economic growth, according to neoclassical theory and the theory of endogenous growth, is influenced by labor resources: population density, quality of labor, the level of employment, investment in human capital, labor productivity. The role of human capital in the models of endogenous growth is considered at two angles: through the ability to generate knowledge and innovative development and as an independent factor - the accumulation of human capital in the region is the basis of economic growth.
The article analyzes classical and modern approaches to assessing the impact of labor resources on economic growth, shows the role played by production functions in such approaches. The characteristic of the main trends of the economic growth of the Russian regions is given, the analysis of development of labor resources and efficiency of their use is made. Production functions such as the Cobb-Douglas type are constructed for the Russian regions, showing the contribution of labor and capital to economic growth, and the statistical significance of these factors is determined. The study was conducted for 83 regions of Russia for the period from 1995 to 2015.
The study will identify the main trends of the impact of the labor force to economic growth, to form the main conclusions for economic policy in the regions of Russia.
The general region socio-economical developement estimation approach is based on the agregation of diffeerent indices into one number. This approach leads to the loss of information, because highly economically developed regions are mixed with the poorly developed regions which live only due to subsidies. The new complex-valued index is proposed in the article. The usage of the index allows to evaluate the regions' developement from two separated sides: the social developement and economical developement. The simple way of such a complex-valued indices is proposed in the article.
Developments in methodologies, agglomeration, and a range of applied issues have characterized recent advances in regional and urban studies. Volume 5 concentrates on these developments while treating traditional subjects such as housing, the costs and benefits of cities, and policy issues beyond regional inequalities. Contributors make a habit of combining theory and empirics in each chapter, guiding research amid a trend in applied economics towards structural and quasi-experimental approaches. Clearly distinguished from the New Economic Geography covered by Volume 4, these articles feature an international approach that positions recent advances within the discipline of economics and society at large.
Urban infrastructure in Russia was heavily subsidized by the state during the socialist period. The market economy is bringing new participants, which could have a significant impact on collective consumption institutions.
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.