The size distribution of ‘cities’ delineated with a network theory‐based method and mobile phone GPS data

• Author: Yuki Akiyama,Ritsu Sakuramachi,Ryosuke Shibasaki,Naoya Fujiwara,Shota Fujishima
• DOI: http://doi.org/10.1111/ijet.12254
• Date: 01 March 2020
• Published date: 01 March 2020

Int J Econ Theory. 2020;16:38–50.wileyonlinelibrary.com/journal/ijet38

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© 2020 IAET

Received: 14 February 2019

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Accepted: 7 January 2020

DOI: 10.1111/ijet.12254

ORIGINAL ARTICLE

The size distribution of ‘cities’delineated with

a network theory‐based method and mobile

phone GPS data

Shota Fujishima

1

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Naoya Fujiwara

2,3

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Yuki Akiyama

4

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Ryosuke Shibasaki

4

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Ritsu Sakuramachi

5

1

Graduate School of Economics,

Hitotsubashi University, Tokyo, Japan

2

Graduate School of Information

Sciences, Tohoku University, Sendai,

Japan

3

Institute of Industrial Science, The

University of Tokyo, Tokyo, Japan

4

Center for Spatial Information Science,

The University of Tokyo, Tokyo, Japan

5

ZENRIN DataCom Co., Ltd., Minato‐ku,

Japan

Correspondence

Shota Fujishima, Graduate School of

Economics, Hitotsubashi University, 2‐1

Naka, Kunitachi, 186‐8601 Tokyo, Japan.

Email: s.fujishima@r.hit-u.ac.jp

Funding information

Kikawada Foundation, Japan Society for

the Promotion of Science (JSPS)

Abstract

We delineate “cities”independent of administrative

boundaries in Japan by using a network theory‐based

method and GPS‐based human mobility data. We divide

the country into approximately 1 × 1 km

2

cells and

detect the partition of cells that is optimal from the

perspective of information theory. The resulting groups

of cells are specified as cities. We find that the

combination of two lognormal distributions better fits

the city‐size distribution than a distribution with a

Pareto upper tail. Moreover, we show that a jump

diffusion process is the stochastic process of the city

population underlying such a distribution.

KEYWORDS

city‐size distribution, community detection, GPS data, jump diffusion

process, mixture of distributions, power law

JEL CLASSIFICATION

C46; C55; R12

1

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INTRODUCTION

Economic activities are often geographically localized. However, the spatial extent of such

geographically localized economic activities is generally not guaranteed to coincide with pre‐

existing administrative units such as cities and counties. We therefore need to decide their

spatial extent without resorting to pre‐existing administrative boundaries to obtain an accurate

picture of the local economy. This is also important for effective public policies because

intergovernmental cooperation is desirable when economic activities are spread over multiple