Формирование и развитие инновационной экономики: материалы международной научно-практической конференции
The paper studies a problem of optimal insurer’s choice of a risk-sharing policy in a dynamic risk model, so-called Cramer-Lundberg process, over infinite time interval. Additional constraints are imposed on residual risks of insureds: on mean value or with probability one. An optimal control problem of minimizing a functional of the form of variation coefficient is solved. We show that: in the first case the optimum is achieved at stop loss insurance policies, in the second case the optimal insurance is a combination of stop loss and deductible policies. It is proved that the obtained results can be easily applied to problems with other optimization criteria: maximization of long-run utility and minimization of probability of a deviation from mean trajectory.
The chapter studies a dynamic risk model defined on infinite time interval, where both insurance and per-claim reinsurance policies are chosen by the insurer in order to minimize a functional of the form of variation coefficient under constraints imposed with probability one on insured's and reinsurer's risks. We show that the optimum is achieved at constant policies, the optimal reinsurance is a partial stop loss reinsurance and the optimal insurance is a combination of stop loss and deductible policies. The results are illustrated by a numerical example involving uniformly distributed claim sizes.
Bank stabilization measures adopted by the Russian authorities since 2008 have benefited core state-owned financial institutions to a greater extent than other market participants. Public sector keeps swelling at the expense of domestic private sector. According to the author’s methodology, by January 2010 state-controlled banks possessed over 50 percent of all bank assets, thus putting Russia in the same league with China and India. Development banking and policy lending expand. A feature distinguishing Russia is gradual substitution of direct state control by indirect state ownership in the shape of corporate pyramids headed by state-owned enterprises and state-owned banks. We construct a dataset of bank-level statistical data for the period between 2001 and 2010 and find that quasi-private banks (indirectly state-owned banks) were the fastest growing subgroup. Nationalization and rehabilitation of failed banks was carried out by state-controlled banks and entities rather than by federal executive authorities directly. We suggest that the response of the Russian authorities to bank instability was consistent with long-term trends in the banking system evolution. Anti-crisis measures of 2008-9 re-aligned the sector with the traditional model of banking that rests upon dominant state-owned banks, directed lending, protectionism, administrative interference and elements of price controls. Increased government ownership of banks and control over lending activity are unlikely to be fully dismantled after the crisis is over. This scenario can nevertheless accommodate a tactical retreat of the state from non-core assets in the financial sector, leaving control over 3 largest institutions intact.
This paper uses the banking industry case to show that the boundaries of public property in Russia are blurred. A messy state withdrawal in 1990s left publicly funded assets beyond direct reach of official state bodies. While we identify no less than 50 state-owned banks in a broad sense, the federal government and regional authorities directly control just 4 and 12 institutions, respectively. 31 banks are indirectly state-owned, and their combined share of state-owned banks’ total assets grew from 11% to over a quarter between 2001 and 2010. The state continues to bear financial responsibility for indirectly owned banks, while it does not benefit properly from their activity through dividends nor capitalization nor policy lending. Such banks tend to act as quasi private institutions with weak corporate governance. Influential insiders (top-managers, current and former civil servants) and cronies extract their rent from control over financial flows and occasional appropriation of parts of bank equity.
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.