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2023
- handle: 10670/1.wyl0t3
- hal: hal-04011734
- doi: 10.1111/agec.12764
- WOS: 000940502200001
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info:eu-repo/semantics/altIdentifier/doi/10.1111/agec.12764
info:eu-repo/semantics/OpenAccess
Mots-clés
Economic performance Farmers Income Meta-analysis Short food supply chains Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q13 - Agricultural Markets and Marketing • Cooperatives • Agribusiness Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q14 - Agricultural FinanceSujets proches
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Pierre Chiaverina et al., « Does short food supply chain participation improve farm economic performance? A meta‐analysis », HAL-SHS : économie et finance, ID : 10.1111/agec.12764
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Résumé
Many researchers, policy makers and food activists view Short Food Supply Chains (SFSC) as attractive levers for improving farm income and the sustainability of farming systems. However, the empirical evidence documenting the association between SFSC participation and farm economic performance has been mixed. In this study, through a meta-analysis using a logistic regression, we identify key factors to explain differences between studies that find better economic performance in SFSC and those that do not. Our meta-analysis consists of 48 studies published in English and French from 2000 to 2022 that examine the economic performance of farms engaged in SFSC. Based on far more empirical evidence than previous reviews, we find that the relationship between SFSC participation and farmer income remains ambiguous. More specifically the findings indicate that the reported effect of SFSC on a farm economic performance varies depending on location and the indicator used to capture the economic performance of farms. Studies conducted in Europe are more likely to report higher farmer income as are studies that use profit satisfaction metrics rather than measures of gross or net income. We also emphasize the need to interpret the reported results cautiously because few are based on causal inference methods. Furthermore, the very few studies that account for selection bias often do so with inadequate corrections.