Vol. 15 No. 2 (2026)
Full Research Articles

Inequality and concentration in farmland production and size: A regional analysis for the European Union from 2010 to 2020

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  • Simone Boccaletti,
  • Paolo Maranzano,
  • Miguel Viegas
Simone Boccaletti
Department of Economics, Management and Statistics, University of Milano-Bicocca, Milano, Italy
Paolo Maranzano
Osservatorio O-Fire, University of Milano-Bicocca, Milano, Italy
Miguel Viegas
Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), University of Aveiro, Portugal
DOI: https://doi.org/10.36253/bae-17797

Published 2025-10-29

Keywords

  • agricultural market concentration,
  • Farmland inequality,
  • Gini index,
  • Spatial autocorrelation,
  • European Union regions

How to Cite

Boccaletti, S., Maranzano, P., & Viegas, M. (2025). Inequality and concentration in farmland production and size: A regional analysis for the European Union from 2010 to 2020. Bio-Based and Applied Economics, 15(2), 45–62. https://doi.org/10.36253/bae-17797

Copyright (c) 2026 Paolo Maranzano, Simone Boccaletti, Miguel Viegas

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Abstract

This article investigates the phenomenon of market concentration in the European agricultural sector from 2010 to 2020 at the regional level. To this end, we exploit the spatiotemporal dynamics of the Gini concentration index for farmland and production. First, we examine the variability within and between countries to assess whether the industry has suffered from increasing concentration during the study period. The next objective is to identify the empirical relationship between the two indicators and determine whether spatial spill-overs occur in terms of market concentration across regions. Our findings confirm the fragmented picture of the European agricultural sector, which is characterized by a high degree of heterogeneity within and across countries as concerns both land concentration and production concentration. In addition, we confirm the existence of a positive association between the two concentration measures. Lastly, the remarkable spatial autocorrelation we observe supports the hypothesis that adjacent regions tend to register similar levels of concentration, generating clusters of regions with either high or low values.

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