Региональная экономика и пространственное развитие в 2 т.: учебник для бакалавриата и магистратуры. — 2-е изд., перераб. и доп.
The paper reviews the problem of Russian regions’ inequality and the current system of intergovernmental fiscal relations, which is used as the main smoothing mechanism of the regional disparities. To use only the minimum level of fiscal capacity as the main calculated indicator of the intergovernmental transfers is not effective, because the real differences between the regions should be considered by taking into account socioeconomic variables (income levels, standard of living). Moreover the problem of a large grant amount to the sub-national government must be solved not only at the federal level. The detection of the reasons revealed that an active regional policy is required. There are also suggestions and recommendations to the federal and regional authorities how to improve the system of intergovernmental fiscal relations in the Russian Federation in the article.
In this paper we study convergence among Russian regions. We find that while there was no convergence in 1990s, the situation changed dramatically in 2000s. While interregional GDP per capita gaps still persist, the differentials in incomes and wages decreased substantially. We show that fiscal redistribution did not play a major role in convergence. We therefore try to understand the phenomenon of recent convergence using panel data on the interregional reallocation of capital and labor. We find that capital market in Russian regions is integrated in a sense that local investment does not depend on local savings. We also show that economic growth and financial development has substantially decreased the barriers to labor mobility. We find that in 1990s many poor Russian regions were in a poverty trap: potential workers wanted to leave those regions but could not afford to finance the move. In 2000s (especially in late 2000s), these barriers were no longer binding. Overall economic development allowed even poorest Russian regions to grow out of the poverty traps. This resulted in convergence in Russian labor market; the interregional gaps in incomes, wages and unemployment rates are now below those in Europe. The results imply that economic growth and development of financial and real estate markets eventually result in interregional convergence.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
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.