Fluctuations in the Relative Dynamics of Development of Russia’s Regional Centers in 2003–2013

Abstract

The paper considers the dynamics of the socioeconomic development of 75 cities, administrative centers of Russian regions. The main objective of the study is to test the authors' methodology, which makes it possible to determine and classify the trajectories of change in the relative position of a city in the investigated set in each year of the period. Unlike the common analysis scheme, when situations at the beginning and end of the period are compared, the authors investigate changes over 11 years on an annual basis, i.e., the trajectory of change in the relative position of an object in the selected set. The study and comparison of the trajectories makes it possible to (a) see inflection points, i.e., the years in which the development of a city was relatively accelerated or decelerated in order to further reveal the factors of the change in trajectory and (b) to suggest a basis for grouping cities by trajectory type. The methodology calculates the city development dynamics index by integrating the nine indicators and constructing a rank vector. In addition, the characteristics of a sampling, such as the minimum and maximum values and variation coefficients, are calculated for each of the nine primary indicators for each year. Cities are grouped by the rank vectors that describe the trajectory of the dynamics. Groups of cities that are steadily growing faster than others, stably lagging behind, and with changing trajectories are identified. Hypotheses explaining the acceleration or deceleration of the development of individual cities are put forward. No significant relationship between acceleration of development and development of official strategies has been established.

Growth Centres in Polarized Macro-Regional Space: An Example From Russia’s Central Black Earth Macro-Region

“…-численность населения [Zhikharevich, Rusetskaya, 2018]; -уровень урбанизации [Rolling back Russia's…, 2018]; -инвестиции в основной капитал [Буфетова, 2009;Zhikharevich, Rusetskaya, 2018]; -ожидаемая продолжительность жизни [Зубаревич, 2009] и др. По данным показателям рассчитывается мера, которая характеризует поляризацию (т. е. то, насколько равномерно распределен данный показатель по изучаемой совокупн ости объектов).…”

“…-коэффициент Джини [Зубаревич, 2009;OECD Regions and Cities…, 2018]; -коэффициент Тейла [Маслихина, 2013; OECD Regions and Cities…, 2018]; -коэффициент вариации [Коломак, 2014; Нефедова, 2009]; -отношение максимального значения показателя к минимальному [Zhikharevich, Rusetskaya, 2018];…”