*Names in bold indicate Presenter
A new wave of privatization is pending over Russia: that of welfare sectors (especially, healthcare and human services). Like in «Obamacare», Medicare, and Medicaid, Russian government funding is greatest for the most needy (elderly and low-income groups) and already constitutes an equivalent of 18% of all individual spending in the economy. This is an extremely high level exceeding that of the USSR period. Free riders, over-utilization of services, high pressure on emergency rooms and irresponsive attitude to healthcare consumption abound.
The nonprofit sector being as large as in the US (quantitatively) could play a better role in making public spending more efficient by delivering more services. Also public support coming to the sector from a whole variety of almost unrelated sources constitutes the same proportion of all nonprofit revenues as in the US (in contracts and grants), whereas there is little analysis of how these government support impacted the sector’s development.
Academic aspect relates to estimating the real scope of the Russian nonprofit sector and systematizing its possible roles in welfare service delivery. This is the first Russian nonprofit sector profile summary, which the author did upon demand of the Russian Department of Economic Development having access to 12 different federal, regional and international sources of data.
As in the US, in Russia high profile politics of government funding of nonprofits has tended to overshadow the ongoing transformation and diversification of the ways government financially supports nonprofits (Smith, 2002; Salamon, 2002). Thus, the author had to elaborate a cross-disciplinary approach using econometrics, economics, public policy and political science - to collect a puzzle of 12 pieces into a coherent picture.
First, the author used regressions with determined factors to account for states-specific effects to show how different sources of finance influenced nonprofit activities. Generally grants have a positive, yet insignificant effect, whereas contracts have a clear crowding-out effect. The same, however, happens to grants as their size increases.
Second, given that information comes from different federal sources in different forms (naturally reflecting different departmental needs), the author accounts for department-specific factors and makes an important assumption of unvoluntarily «doctored» accountability. The author worked with data presented by the Federal Department of Health, Federal Department of Economic Development, Federal Department of Labour, Federal Department of Justice, the National Agency of Statistics, used some of the data presented by USAID.
Third, the author uses case-analysis to show how nonprofits were efficient healthcare providers, but also good decision-makers.
Fourth, some American research on crowding-out effects and regulatory functions of the government was used to control for specific factors and to create replacing variables where data is scarce or not available.