Published April 27, 2026 | Version v1
Working paper Open

Spatial and Panel Data Analysis of Food Loss and Waste Drivers Across the EU Supply Chain - Discussion paper

  • 1. ROR icon Centro de Investigación y Tecnología Agroalimentaria de Aragón
  • 2. ROR icon Fundacion Agencia Aragonesa para la Investigacion y el Desarrollo

Description

Abstract

Reducing food waste has become a central objective within EU food system policy, particularly under the Farm to Fork Strategy and Sustainable Development Goal 12.3. While policy discussions often concentrate on consumer behaviour, food waste in fact emerges from interactions between technological conditions, structural characteristics of agri-food systems, and demand-side dynamics across multiple supply chain stages. This paper provides an empirical assessment of these drivers across EU Member States, with the aim of supporting evidence-based policy design and improving the representation of food waste in forward-looking modelling exercises. Using harmonised EU food waste data for 27 Member States over the period 2013–2022, we estimate fixed-effects panel regressions separately for four supply chain stages: Primary Production (PP), Processing and Manufacturing (PM), Retail Distribution (RD), and Households (HH). The analysis is preceded by a comprehensive spatial autocorrelation diagnostic. Key findings show that food waste does not exhibit significant spatial clustering at the national level, and that determinants differ substantially across stages. At the household level, income displays an inverted-U relationship with food waste, with an implied turning point near €48,972, while education, household composition and unemployment are robust additional drivers. Upstream stages are governed primarily by production scale and logistics-related variables. Main results are confirmed across multiple robustness checks.

Citation

Ferrer-Pérez, H. & Philippidis, G. (2026). Spatial and Panel Data Analysis of Food Loss and Waste Drivers Across the EU Supply Chain. Discussion paper BrightSpace Horizon Europe project GA Nr. 101060075. https://doi.org/10.5281/zenodo.19814075

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Funding acknowledgement

Funded by the European Union. Grant Agreement No. 101060075. Views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.

UK Research and Innovation Project Code: 10047415 https://gtr.ukri.org/projects?ref=10047415

Legal notice

This document was produced under the terms and conditions of Grant Agreement No. 101060075 for the European Commission. It does not necessary reflect the view of the European Union and in no way anticipates the Commission’s future policy in this area. The European Commission is not liable for any consequence stemming from the reuse of this publication.

© BrightSpace, 2026

The reuse of this document is authorised under a Creative Commons Attribution 4.0 International (CCBY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of elements that are not owned by the BrightSpace consortium, permission may need to be sought directly from the respective right holders.

Project information

BrightSpace Horizon Europe project Grant Agreement No. 101060075 https://cordis.europa.eu/project/id/101060075 CALL: Innovative governance, environmental observations and digital solutions in support of the Green Deal WORK PROGRAMME Topic ID: HORIZON-CL6-2021-GOVERNANCE-01-12 EU agriculture within a safe and just operating space and planetary boundaries

BrightSpace Project coordination: Wageningen Economic Research, The Hague, NL Contact: brightspace.wser@wur.nl | Website: www.brightspace-project.eu

Project duration: 1 November 2022 – 31 October 2027.

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Additional details

Related works

Cites
Dataset: 10.5281/zenodo.17483053 (DOI)

Funding

European Commission
Horizon Europe HORIZON-CL6-2021-GOVERNANCE-01-12 BrightSpace Grant Agreement No. 101060075
UK Research and Innovation
Funder: UKRI Project Code: 10047415

Software

Programming language
Stata