Schriftenreihe/Nr.:
54th Congress of the European Regional Science Association: "Regional development & globalisation: Best practices", 26-29 August 2014, St. Petersburg, Russia
Zusammenfassung:
For long time, the applicability of economic theories of cities, urbanisation and urban development as well to Russian cities was hampered by the lack of data beyond population figures. Since 1990, some contributions of Richard Rowland with regard to urban development in Russia referred to certain classes of cities (metropolitan cities, rapidly growing cities, declining cities or secret cities). However, with the exception of secret cities (ZATO), these classifications are derived from purely size characteristics, and are rather descriptive. Also Mykhnenko and Turok (2008) analyse only population figures of 150 East European cities, among them 56 Russian cities. Kauffmann (2010) analyses growth rates of population of about 3000 Russian cities and urban settlements between 1993 and 2004 with regard to the predictions of a certain class of New Economic Geography models. But, since 2004, data for cities with more than 100000 inhabitants (and for some smaller cities with regional capital function, as well) are published by ROSSTAT annually in "Regiony Rossii vol. 3". Applying data from this source, a cluster analysis has been undertaken, where indicators with regard to demography, labour market and geography of 156 cities are included into the variable set. The outcome are 15 clusters that may be well interpreted by principal components. The aim of this cluster analysis is to provide impulses for drawing on theories which may explain Russian urban development. Among principal components 2 most important are natural resources and labor endowment (Eigen Values are 6.2 and 3.2 respectfully). Smaller input in urban dynamics is provided by population change characteristics (Eigen Value is 1.8), the place of the city in urban system hierarchy (1.1) and by the poverty trap situation (0.9). Agglomeration economy has only a weak influence on Russian cities dynamics (Eigen Value is 0.8), it can be identified in cities with more than 1 mln population, in cities of Moscow Metropolitan Region and in principal cities of the Centre and the South of European Russia.