This book represents the 8th volume of results obtained from the monitoring of the status of civil society in Russia that is conducted by the Centre for Studies of Civil Society and the Nonprofit Sector (the National Research University “Higher School of Economics”) in conjunction with the leading sociological centres of Russia. The empirical base of this publication is formed from the data of All-Russian survey of population aged 18 years and older, that was based on representative sample and carried out in 83 regions of Russia in 2259 localities within the framework of expert services on the strategy of socio-economic development of Russia till 2020. The data provided characterizes engagement of Russians in volunteering, charitable donations and other social and political practices. The data describes determinants of Russians connected with responsibility for actions taken in their neighborhoods and localities and the country at large and their sense of the opportunity to exert their influence over it. This book will be of use to social and political scientists, economists, teachers and students of the social sciences and anyone, interested in the development of civil society in Russia.
Article is devoted to Old Belief history in the years of World War I. It is analyzed first of all features of the broadest charity of Old Believers in 1914-1917.
Тhe article considers accounts Valuation and Budget rules - documents, regulating the budget process, or the process of compiling, approving, implementing and controlling of implementation of the state scheduling of income and expenses in Russia of the end of 19th - beginning of 20th century. The named documents are to be a foundation of present budget law in Russia, that supposes their detailed research.
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.