This paper analyses the spatial patterns of internal migration in Russia using data on net migration gain/loss in 2200 municipal formations (MFs) in Russia for the 2012–2013 period. These MFs are grouped into age categories that correspond with different life-course stages. We define 16 classes of MFs with similar migration balance patterns for multiple age groups and characterize the most typical classes. The results of our analysis show that age-specific migration patterns are determined by the spatial characteristics of MFs—in particular, a municipality’s localization in the centreperiphery system and the advantages of the geographic location (e.g., resort area, natural resources). We find that a city’s population size and administrative status are also important migration factors. In addition, we reveal differences in inter-regional and intra-regional migration and define their structural characteristics. An analysis of age-specific net migration contributes to our understanding of internal migration factors and allows us to assess the impact of migration on a municipality’s age structure. In large cities and regional centres, migration results in younger populations, while in peripheral areas, it speeds up population ageing. In most of the MFs that we analysed, the migration of youth and adults ‘moves’ in opposite directions. This factor accelerates the impact of migration on the population age structure in areas of destination and origin and significantly influences a municipality’s current and prospective demographic parameters as well as the population’s patterns of settlement and spatial concentration or de-concentration both nationally and regionally.
В статье рассматриваются региональная диагностика как метод исследования социально-экономиеского пространства России, качество экономического пространства и его регионаьные различия, методы и инструменты устойивого развития регионов.
In this study, we analyzed the data about the technological diversification of export composition of upper middle-income countries and the impact of the technological composition of exported goods on GDP growth. Using the dynamic panel data analysis techniques for 34 countries between 1995-2015, we confirmed that exports of high technological products will have a significant positive impact on economic growth for upper middle-income countries as well as medium technological products’ exports which have a limited effect. The exports of low-tech products will have a negative effect for economic growth in the long run.
From the raw diamonds of the eighteenth century, it has been turned into today. Yet, even now, the indigenous India, largely hidden away from public vision. This is a picture of the realm of the Gonds, where it can be seen. It has been shaped by the local miners in Panna and is shaped by The miners dig, the miners dig, savoir vivre . They remain dynamic, and success. It is clear that they can bind themselves to the miner's life. This is a protagonist story that has been spelled out. Based on the ethnographic fieldwork in Pannah, Madhya Pradesh State University of Central Asia
We document the geographic concentration patterns of Russian manufacturing using detailed microgeographic data. About 80% of three‐digit industries are significantly agglomerated, and a similar share of three‐digit industry pairs is significantly coagglomerated. Industry pairs with stronger buyer–supplier links—as measured using Russian input–output tables—tend to be slightly more coagglomerated. This result is robust to instrumental variable estimation using either Canadian or US instruments. Using Canadian ad valorem transport costs as a proxy for transport costs in Russia, we further find that industries with higher transport costs are more dispersed, and industry pairs with higher transport costs are less coagglomerated.