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Economic Analysis: Theory and Practice
 

The Zipf's law: A cross-country analysis

Vol. 17, Iss. 7, JULY 2018

PDF  Article PDF Version

Received: 14 March 2018

Received in revised form: 25 April 2018

Accepted: 14 May 2018

Available online: 27 July 2018

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: R13

Pages: 1337–1351

https://doi.org/10.24891/ea.17.7.1337

Manaeva I.V. Belgorod National Research University, Belgorod, Russian Federation
in.manaeva@yandex.ru

https://orcid.org/0000-0002-4517-7032

Kanishcheva A.V. Belgorod National Research University, Belgorod, Russian Federation
black_shadow13@mail.ru

https://orcid.org/0000-0003-2960-3844

Importance The article addresses the modern settlement system in cities of the world, being a topical problem of spatial economy. It presents empirical studies of the Zipf's law in foreign and domestic literature. To assess the conformity of the modern settlement system with the rank-size distribution, we chose the following countries: Belarus, Brazil, Great Britain, Egypt, Norway, Poland, Russia, Turkey, USA, France, Japan.
Objectives The aim is to analyze the feasibility of the Zipf's law at the cross-country level.
Methods We apply the least square method to analyze the feasibility of the Zipf's law for the sample of countries.
Results The closest to the ideal Zipf's curve are settlement systems in cities of developing countries (Turkey, Poland, Brazil) and developed countries (USA, Japan). The gap between the main 'primate city' and subsequent rank cities is very significant.
Conclusions Traditionally, the sample of 'primate city' countries is a capital. Large centers will continue to grow at a faster pace and attract more and more migrants. This trend is negative, as overpopulation of large cities will be accompanied by a change in the ethnic and social composition of residents, as well as by suburbanization, which can lead to social and economic stagnation.

Keywords: Zipf's law, rank-size distribution, population size, cross-country level

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