population – Regional Science Inquiry

Evgenia ANASTASIOU

Postdoctoral Researcher, University of Thessaly

evanastasiou@uth.gr

Abstract

The last decade economic developments affected to a large extend the demographic structure of Greece. The period 2001-2011 is characterized by a net slowdown of the intense urbanization trend, while in the context of crisis there have been identified counter-urban trends, revealing new attractiveness zones in the rural areas. These indications of mobility do not concern entirely the countryside as the newcomers settle only in specific rural spatial units. At the same time these areas have specific features that facilitate the establishment of a new population, such as population dynamics, tourism development, agricultural activity, services and structures, reduction of geographical isolation, low cost of living and habitation. The future of internal migration in Greece heavily depends on existing trends as well as future economic, social and political developments. Though, the lack of official data for the period after 2011 constrains our understanding for the development of internal migration and particularly counter-urban trends in Greece. The present paper raises the issue of the prospects of the establishment of the Greek population in the countryside, taking into account the pull factors of rural areas. Through Foresight and Strategic Thinking Methods, a longer-term framework is being developed to reflect the potential strategic choices of the internal migrants. This approach is based on a mainly qualitative analysis, scenario planning, in order to present the prerequisites for the further development of such a type of mobility.

Keywords: foresight, scenario planning, internal migration, population, countryside

JEL classification: J1, J6, J11, R23

Inna MANAEVA

World Economy Chair –Belgorod State National Research University, Russia, http://www.bsu.edu.ru

In.manaeva@yandex.ru

Svetlana RASTVORTSEVA

World Economy Chair –Belgorod State National Research University, Russia, http://www.bsu.edu.ru

Srartvortseva@gmail.ru

Abstract

The paper is concerned with the topical issues of regional economics – urban inequality in the Russian Federation. Empirical investigations of Zipf’s law were studied in the foreign and Russian literature. Application of this law for assessment of urban inequality using the method of least squares was substantiated. Assessment of urban inequality within the boundaries of the RF federal districts by the indices of population, volume of own production of goods and services is carried out in the paper. The authors used the data of the Federal State Statistics Service for 2014, the investigation included the settlements with the status of a town and with the population over 100 thousand people. Zipf’s law displays over the entire territory of Russia. By the population index in the federal districts, Zipf’s factor varies within the range from – 0.7 (Northwestern Federal District) to – 0.9 (North Caucasian Federal District). As a result of the performed analysis of the Russia’s cities by the population index, Zipf’s factor is within the range from –0.3 (Northwestern Federal District) to –1.2 (Central Federal District). Analysis of the volume of production of goods and services determined the range of Zipf’s factor from –0.26 (North Caucasian Federal District) to – 0.7 (Central and Volga Federal Districts). By the index of population and volume of production of goods and services the following “primate cities” are determined: Moscow and Saint Petersburg, Yekaterinburg (population), which allows to draw a conclusion on their dominance in urban system and high differentiation of cities by these indices. The obtained empirical estimators prove that Russia has no intermediate group of cities macroregional centers. The results of the investigation can be used for creation of methodological tools to develop the mechanisms of smoothing of interregional inequality, program of economic and social development of cities.

Keywords: city, spatial inequality, Zipf’s law, population, population density

JEL classification: R12

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