Characterizing the sectoral development of cities

PLoS One. 2021 Jul 14;16(7):e0254601. doi: 10.1371/journal.pone.0254601. eCollection 2021.

Abstract

Previous research has identified a predictive model of how a nation's distribution of gross domestic product (GDP) among agriculture (a), industry (i), and services (s) changes as a country develops. Here we use this national model to analyze the composition of GDP for US Metropolitan Statistical Areas (MSA) over time. To characterize the transfer of GDP shares between the sectors in the course of economic development we explore a simple system of differential equations proposed in the country-level model. Fitting the model to more than 120 MSAs we find that according to the obtained parameters MSAs can be classified into 6 groups (consecutive, high industry, re-industrializing; each of them also with reversed development direction). The consecutive transfer (a → i → s) is common but does not represent all MSAs examined. At the 95% confidence level, 40% of MSAs belong to types exhibiting an increasing share of GDP from agriculture. In California, such MSAs, which we classify as part of an agriculture renaissance, are found in the Central Valley.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • Cities
  • Economic Development*
  • Gross Domestic Product
  • Urban Population

Grants and funding

D. Rybski thanks the Alexander von Humboldt Foundation for financial support under the Feodor Lynen Fellowship. D. Rybski is grateful to the Leibniz Association (project IMPETUS) for financially supporting our research. P. Pradhan acknowledges funding from the German Federal Ministry of Education and Research for the BIOCLIMAPATHS project (grant agreement No 01LS1906A) under the Axis-ERANET call.