Population Structures in Russia: Optimality and Dependence on Parameters of Global Evolution


  • Yuri Yegorov University of Vienna




urban, rural, population density, prices, transport, transition


The paper is devoted to analytical investigation of the division of geographical space into urban and rural areas with application to Russia. Yegorov (2005, 2006, 2009) has suggested the role of population density on economics. A city has an attractive potential based on scale economies. The optimal city size depends on the balance between its attractive potential and the cost of living that can be approximated by equilibrium land rent and commuting cost. For moderate scale effects optimal population of a city depends negatively on transport costs that are related positively with energy price index.

The optimal agricultural density of population can also be constructed. The larger is a land slot per peasant, the higher will be the output from one unit of his labour force applied to this slot. But at the same time, larger farm size results in increase of energy costs, related to land development, collecting the crop and bringing it to the market.

In the last 10 years we have observed substantial rise of both food and energy prices at the world stock markets. However, the income of farmers did not grow as fast as food price index. This can shift optimal rural population density to lower level, causing migration to cities (and we observe this tendency globally). Any change in those prices results in suboptimality of existing spatial structures.

If changes are slow, the optimal infrastructure can be adjusted by simple migration. If the shocks are high, adaptation may be impossible and shock will persist. This took place in early 1990es in the former USSR, where after transition to world price for oil in domestic markets existing spatial infrastructure became suboptimal and resulted in persistent crisis, leading to deterioration of both industry and agriculture.

Russia is the largest country but this is also its problem. Having large resource endowment per capita, it is problematic to build sufficient infrastructure. Russia has too low population density and rural density declines further due to low fertility and migration to cities. Those factors limited the growth of the USSR, but after the economic reforms of 1990s the existing infrastructure became exposed to permanent shock of high transport costs. Due to large distances it is optimal to return to gasoline and thus transport subsidy. This will work also against disintegration of the country.

Author Biography

Yuri Yegorov, University of Vienna

Faculty of Economics and Business

Dept. of Industry, Energy and Environment

Senior Researcher


Atkinson, Anthony Barnes & Micklewright, John (1992) Economic Transformation in Eastern Europe and the Distribution of Income. - Cambridge Books, Cambridge University Press, number 9780521433297, October.

Kauffman A. (2013) The Russian Urban System in Transition: The View of New Economic Geography. – ERSA 2013, Palermo.

Kauffmann A. (2007) Transport Costs and the Size of Cities: the Case of Russia, University of Potsdam, Discussion paper # 9.

Robert J., Lennert M. (2010) Two scenarios for Europe: "Europe confronted with high energy prices" or "Europe after oil peaking", Futures,


Mascarilla-i-Miro O., Yegorov Y. (2005) Modelling Functional Area and Commuting Flows, Cuadernos de Economia, 2005, vol.28, p.39-56.

Yegorov Y. (1999) Dacha pricing in Russia: General Equilibrium Model of Location, CASE-CEU Working Paper No.18, Warsaw, March 1999, 27 p.

Yegorov Y. (2005) Role of density and field in spatial economics. In: Yee Lawrence (Ed.), Contemporary Issues in Urban and Regional Economics. N.Y.: Nova Science Publishers, 55-78.

Yegorov Y. (2006) Emergence and Evolution of Heterogeneous Spatial

Patterns - ERSA Congress 2006, Volos, Greece


Yegorov Y. (2009) Socio-economic influences of population density, Chinese Business Review, vol.8, No. 7, p. 1-12.




How to Cite

Yegorov, Y. (2016) “Population Structures in Russia: Optimality and Dependence on Parameters of Global Evolution”, REGION, 3(1), pp. 89–106. doi: 10.18335/region.v3i1.74.