Article
Attracting Skilled Labour to the North: Migration Loss and Policy Implications Across Russia’s Diverse Artic Regions
This paper identifies education, skills training and improved social infrastructure as key development issues to address population decline in regions of steady out-migration from the Russian Arctic. Migration flows are mostly stabilized after the sharp and unexpectedly large population decline in the Arctic in the 1990s, during the transition to a market economy. However, the trends set in motion during that collapse, including falling general levels of education, declining size of all but the largest cities, and aging of the populace, are deepening in consequence for some regions, even where government resettlement programs exist. As young professionals continue to leave, resettling com-patriates and hiring shift labour may contribute to the vitality of more resilient regions, for example, Krasnoyarsk and Yamalo-Nenets. However, the European part of the Russian Arctic, despite its critical importance to commerce and to military security, and despite assistance programs and subsidies, is conforming more to the aging, less productive contours of neighbouring Artic states on the periphery of Europe.
This paper analyzes German and Russian ideas of nationhood as conceived by the state through the states’ migration and repatriation policies. Immigration policies at large and repatriation policies in particular are viewed in this paper as symptomatic means of understanding inclusion and exclusion in a nation-state, and evolution of such policies are taken as indicators of changes in idioms of the national self. The main argument of the paper is that German national identity is slowly moving away from an ethno-centric conceptualization of nationhood, while Russia has failed to formulate a conception of the Russian nation-state. The findings of this study merit further reflection the effectiveness of repatriation policies, on the relationship between the state and society, on the transnational essence of migration pathways, and on the “post-Soviet condition” which has set the stage for all of the aforementioned processes and transformations.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.
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.