Population Dynamics and Spatial Dependence: Evidence from Brazilian Cities

Diego Firmino Costa Da Silva,Raul Da Mota Silveira Neto

doi:10.52324/001c.11127

Abstract

This paper focuses on Brazil’s population dynamics between 1970 and 2010. The first objective is to explore the behavior of Brazil’s population distribution, revisiting the traditional rank-size rule and Markov chain approaches. To increase the accuracy of the information on the dynamics and evolution of the population distribution, spatial dependence is introduced through spatial Markov chains. The distribution shape may indicate that divergence in population size of minimum comparable areas (MCAs) is decreasing. The Zipf’s law estimation indicates that the population distribution is, every decade, moving away from Pareto law. The Markov chain approach indicates, as main evidence, the high persistence of MCAs to remain in their own class size from one decade to another over the entire period, and that different spatial contexts have different effects on regional transitions.

Highlights

Between 1970 and 2010, Brazil’s population became increasingly more concentrated in its cities
How did cities of different sizes grow during the period 1970 to 2010? Second, how are the movements within the distribution affected by spatial dependence? we investigated the evolution of city size distribution and how this is affected by the location of the cities relative to their neighbors
This suggests that to capture the transition dynamics of the size distribution, it is necessary to consider the spatial dependence among minimum comparable areas (MCAs), that is, the initial location of the MCAs matters

Summary

INTRODUCTION

Between 1970 and 2010, Brazil’s population became increasingly more concentrated in its cities. Our three main results indicate that (i) Brazil’s population distribution is, as the decades progress, moving away from Pareto law; (ii) there is low inter-class mobility and a high likelihood for cities to remain in their own class size from one decade to another, and; (iii) different spatial contexts have different effects on regional transition.

DATA AND INITIAL EVIDENCE

ZIPF’S LAW

CITY SIZE DISTRIBUTION AND THE MARKOV TRANSITION DYNAMIC

SPATIAL MARKOV DYNAMICS

Findings

CONCLUSIONS