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Simple geographies for complex problems? Revisiting long-term urbanization and settlement population mismatches using elasticity indicators and context-based nonparametric analysis

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Abstract

Diverging rates of population growth and urban expansion have been frequently taken as a proxy of land consumption in advanced economies. As a novel contribution to diachronic analysis of compact vs dispersed urbanization, the present study introduces a logical framework that provides global and local estimates of the increasing mismatch in resident population and urban settlements. ‘Stock’ and ‘flow’ indicators quantifying the elasticity to change in population and building growth rates were calculated separately over three time intervals between 1948 and 2018, as representative of a metropolitan cycle from urbanization to counter-urbanization in a Southern European region (Athens, Greece). The relationship between elasticity indicators and the socioeconomic profile of each municipality in the study area was additionally investigated through nonparametric correlations and a multivariate statistical approach. Results indicate that spatial patterns of population growth and urban expansion diverged since the mid-1970s, reflecting an accelerated development toward discontinuous and dispersed settlements. A less intense population land mismatch was observed in municipalities with compact morphologies, prevalence of non-residential settlements, and above-average accessibility to primary urban functions. The work concludes with a discussion on the use of the proposed indicators to inform strategies of sustainable land management in sprawling metropolitan regions.

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  1. Department of Methods and Models for Economics, Territory and Finance (MEMOTEF), Faculty of Economics, Sapienza University of Rome, Via del Castro Laurenziano, 9, 00136, Rome, Italy

    Luca Salvati

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Salvati, L. Simple geographies for complex problems? Revisiting long-term urbanization and settlement population mismatches using elasticity indicators and context-based nonparametric analysis. Ann Reg Sci 72, 513–533 (2024). https://doi.org/10.1007/s00168-023-01209-2

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