The research of companies’ territorial strategies allows to specify the entrepreneurs logic of territories choice for the investment by eliminating from the analysis the offshore capital, to reveal the differences in regional strategies of companies in various branches of the economy, to identify the company preferences in territories for different activities, to assess the attractiveness for foreign investors not only regions, but also different types of settlements (all of these tasks cannot be solved on the basis of statistical data). The paper analyzes the location of regional divisions of different types (production, logistics, sales, research, management) of 50 largest foreign companies operating in Russia (Forbes rating). The author confirms the compliance of this location with the existing theoretical ideas about the companies’ territorial strategies, including the importance of key economic centers, hierarchical and wave diffusion, neighborhood effect. The paper shows the differences in investments’ attracting in different types of cities (including the role of million-plus cities in the location of companies distribution centers and research units, small towns in attracting industrial enterprises, the second-third cities of regions in the development of the retail trade), in the wideness of the geography of companies activities in different industries (including the presence of minimum territorial barriers in the food industry and mono-brand retail trade, especially cars), the importance of proximity to Moscow. The article highlights Russian Federation subjects with the maximum degree of allocation of foreign companies.
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.