Федеральные округа России. Региональная экономика
The sector of knowledgeintensive business services (KIBS) not only contributes to its own dynamic and innovative development but also to the development of the external environment through the creation, accumulation, and dissemination of knowledge. Therefore, it is considered one of the key pillars of the knowledgebased economy. This article addresses the problem of its spatial distribution in Russia. The basis of the study is uniquely empirical, obtained through a series of largescale surveys among Russian pro ducers and consumers of KIBS. The collected data provide quantitative evidence for the spatial dimension of the sector. Comparative analysis of the production and consumption of KIBS in Russia’s federal districts makes it possible to classify the latter in terms of the exchange of related services and mapping of the intensity of their interregional supply and demand across federal districts. It is established that companies offering KIBS in Russia are largely concentrated in big cities. The demand for KIBS is more distributed, but not spa tially neutral. This paper may be of interest to researchers focusing on the spatial distribution of elements of the innovationbased economy in Russia. It is also relevant for regional authorities, because it can help them assess the development capacity of their regions.
In the present paper we consider the infl uence of limited time resources on the planning of territories. By specifi c example of one of the districts of Nizhniy Novgorod region it is shown how the limitations of political and economic factors change the trajectory of territorial development.
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.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.
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.