Abstract

AbstractWe provide new insights on the city size distribution of countries around the world. Using more than 10,000 cities delineated via geospatial data and a globally consistent city identification scheme, we investigate distributional shapes in all countries. In terms of population, we find that Zipf's law holds for many, but not all, countries. Contrasting the distribution of population with the distribution of economic activity, measured by nighttime lights, across cities we shed light on the globally variant magnitude of agglomeration economies. Deviations from Zipf's law are to a large extent driven by an undue concentration in the largest cities. They benefit from agglomeration effects which seem to work through area rather than through density. Examining the cross‐country heterogeneity in the city size distribution, our model selection approach suggests that historical factors play an important role, in line with the time of development hypothesis.

Highlights

  • The rapid urbanization process around the world has brought renewed interest to the question of the size distribution of cities

  • We are the first to investigate whether the size distribution of economic activity in countries follows Zipf’s Law. (iii) We investigate the geographical, institutional and historical determinants of the cross-country variation we observe in the city size distribution, and we look at changes over time

  • We examine the particular role played by primary cities, which have been linked to autocratic structures (Ades and Glaeser, 1995), political centralization (Davis and Henderson, 2003) and low levels of development in general (Henderson, 2003)

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Summary

Introduction

The rapid urbanization process around the world has brought renewed interest to the question of the size distribution of cities. Satellite data of nighttime lights have been shown to be an appropriate proxy for local economic activity (Henderson et al, 2012, Donaldson and Storeygard, 2016) and are increasingly used for the study of cities in developing countries where up-to-date population data are lacking (Bluhm and Krause, 2018, Storeygard, 2016, Fetzer et al, 2016). It is an open question whether light per capita is the same for all cities in a country and how light output in cities responds to changes in population. An Online Appendix contains the accompanying material, such as supplementary information on the data set, a simulation exercise, detailed results for each country as well as numerous robustness checks

Related literature
City identification and city size measurement
Estimation approach
Results in terms of population and light
Explaining patterns along the city size distribution in population and light
Determinants of cross-country variation
Changes over time and outlook
Concluding remarks
G Model selection procedure for determinants xxxviii i
Simulation
Threshold choice in practice
Alternative thresholds
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