Доверие в нестабильном российском обществе
The paper demonstrates the potential of the stochastic frontier-based methods of performance assessment of non-profit associations. They are commonly used for productivity analysis and could serve as an adequate tool for such assessment, especially when dealing with numerous non-profits pursuing identical and clearly identified objectives. A case in point are homeowners associations (HOA), which are formed within apartment buildings to manage common property. Data was collected by a survey of 82 HOAs in Russias national capital Moscow and a large industrial city of Perm. Different techniques and robust checks are applied, exogenous parameters that influence HOA efficiency are revealed. Among those, physical conditions of the housing stock and ability of tenants to resolve the collective action problem in operating housing infrastructure were shown to be of primary importance. Overall, HOA, despite of their appeal and successful performance in developed nations, are not necessarily a superior option in countries and societies where civic capacity is in short supply, and housing stock suffers from wear and tear.
The article examines differences between two Russian regions – Moscow and Bashkortostan – through the following socio-psychological indicators: perceived social capital, trust, civil identity, life satisfaction, and economic attitudes.
This article is talking about state management and cultural policy, their nature and content in term of the new tendency - development of postindustrial society. It mentioned here, that at the moment cultural policy is the base of regional political activity and that regions can get strong competitive advantage if they are able to implement cultural policy successfully. All these trends can produce elements of new economic development.
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.