Российские регионы: экономический кризис и проблемы модернизации
Migration is an important and rapidly growing phenomenon in the modern world. Many countries are facing problems with integration and adaption of migrants to new living conditions. Subjective well-being (SWB) can be considered as an indicator of how successfully migrants are adapted and integrated into the host society. Levels of migrants’ SWB are often determined by the same factors as for other people—good health, high salary, employment and youth make them happier. Nonetheless, migrants’ decision to migrate is often led by economic motives, which leads them to overvalue economic characteristics of countries and regions of destination and undervalue non-economic factors. This paper aims to estimate the effects of the economic prosperity (measured by gross regional product) and social capital of Russian regions (measured by general social trust and relative size of the community of the migrant’s compatriots) on the life satisfaction of migrants. In addition, we analyze possible effect of the inclusion of the migrants’ country of origin into Eurasian Customs Union. To answer the proposed questions we employed data of the Russian Longitudinal Monitoring Survey—Higher School of Economics (RLMS-HSE) and statistics provided by Russian Federal State Statistics Service. The main method of analysis is a cross-classified multilevel linear regression modeling. The results show that the economic performance of a region has no effect on the life satisfaction of a migrant. It appears that social factors play a greater role—the effects of general social trust and the relative size of the community of a migrant’s compatriots in a region are positive and statistically significant. We found that inclusion of the country of migrants’ origin into the Eurasian Customs Union positively and significantly affects the life satisfaction of migrants. We associate this effect with a decrease in the economic and psychological costs of migration.
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.
This paper explores age-specific migration flows between regions of Russia. Using age-disaggregated data of the Russian Census 2010, we cluster interregional migration flows based on prevailing age-groups of migrants, analyse diversity and similarity in the choice of age-specific migration destinations and describe general socio-economic characteristics of these flows. It is for the first time that the relationship between migration and migrants’ age and life-cycle events is analysed in the Russian context. Similar to migrants in other countries, migrants in Russia choose the place of residence depending on their age. Migration flows which differ by dominating age group of migrants quite often have opposite destinations, because motivations of migration also differ. Migration follows various stages of the life-cycle: people are born in one region, study in another region, go to work in a different region, and resettle to another place after retirement. Migration modeling turns to be complicated if the impact of age factor is ignored. Therefore, the age of migrants should be considered when analyzing, modeling and interpreting interregional migration in Russia.
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 article attempts to identify major factors of the nationalization of the vote in contemporary Russia using the two level approach: the between- and within-region. The former compares regions as units of analysis while the latter additionally takes into account voting in municipalities to obtain levels of voting homogeneity within the regions. The study uses data from the last 2012–2016 national-regional electoral cycle investigating both federal and regional election results. Following Ishiyama (2002) for the between-region level of analysis the Regional Party Vote Inequality index has been utilized. The Party Nationalization Score proposed by Jones and Mainwaring (2003) has been applied to the measurement of voting territorial diversity at the within-region level. The results show that regional political factors may be still considered as major drivers of the nationalization of the vote as it did in the 1990s. The difference is that in politically recentralized Russia non-competitive regions headed by politically strong governors provides between-region inequality rather than contributing to nationalization. At the same time, the similarity continues in the ability of governors’ “political machines” to contribute homogeneity of the vote, but only within their regions.