Государственно-общественное регулирование сферы ЖКХ: опыт Иркутской области
The problem of conflicts between the financial industry professionals’ business interests and the SROs' regulatory activities is studied in this paper. With the help of the elaborated methods the intensity of the US SROs conflicts of interest is revealed since 1991 till 2010 on the basis of the industry professionals’ individual preferences with regard to financial market efficiency. We determined that the professionals gained the maximal accumulated portfolio value provided systematic deviation of the market from normality (efficiency). The professionals’ goals of utility maximization did not match the SROs’ goals of the due market regulation in accordance with the regulator and international organizations requirements. These methods and results could be used in decision making about the allocation of financial market regulatory powers between regulator and SRO.
The article examines the problems of delegation of public powers of authority to self-regulated organizations: public powers of authority which may be delegated, spheres of state administration, where delegation of powers is not allowed, validity of control over realization of delegated powers in all cases of such delegation and responsibility of the state for the acts of private persons who exercise public powers of authority.
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.