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Do economic performance and innovation have a relationship? Evidence from Operational Groups in the Italian agri-food sector

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  • Mazzulla, Francesco
  • Raggi, Meri

Abstract

This study aims to investigate the potential mutual interdependence between an environment that fosters and encourages innovation and the economic performance of agricultural businesses operating in the sector. Specifically, it seeks to determine whether the economic performance of farms in regions with established Operational Groups (OGs) is better than that of farms located in regions where OGs have not yet been implemented, using the European Innovation Partnership for Agricultural Productivity and Sustainability (EIP-AGRI). We combine data on OGs collected from the Innovarurale website, with financial information from the ORBIS database for the period 2013-2022, to assess farm performance. Our estimation strategy employs three staggered difference-in-differences models and an event-study to validate the parallel trends assumption. The results show a positive association between the presence of OGs in a region and an improved economic performance. Our findings suggest that the diffusion of innovation tends to be related to the characteristics of the local economic environment, which should be a critical factor in future policy discussions.

Suggested Citation

  • Mazzulla, Francesco & Raggi, Meri, 2025. "Do economic performance and innovation have a relationship? Evidence from Operational Groups in the Italian agri-food sector," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 14(3).
    • Handle: RePEc:ags:aieabj:393883
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    File URL: https://ageconsearch.umn.edu/record/393883/files/W00123_51-60_05-16801-Mazzulla.pdf
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    References listed on IDEAS

    as
    1. Vladimír Baláž & Tomáš Jeck & Miroslav Balog, 2023. "Firm performance over innovation cycle: evidence from a small European economy," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-23, December.
    2. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    3. Kirill Borusyak & Xavier Jaravel & Jann Spiess, 2024. "Revisiting Event-Study Designs: Robust and Efficient Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(6), pages 3253-3285.
    4. Adele Finco & Deborah Bentivoglio & Giorgia Bucci, 2018. "Lessons of Innovation in the Agrifood Sector: Drivers of Innovativeness Performances," Economia agro-alimentare, FrancoAngeli Editore, vol. 20(2), pages 181-192.
    5. Beatriz Corchuelo Martínez-Azúa & Pedro Eugenio López-Salazar & Celia Sama-Berrocal, 2020. "Determining Factors of Innovative Performance: Case Studies in Extremaduran Agri-Food Companies," Sustainability, MDPI, vol. 12(21), pages 1-24, November.
    6. Matteo Lucchese & Mario Pianta, 2011. "Cycles and innovation," Working Papers 1103, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2011.
    7. Andrea Arzeni & Francesca Giarè & Mara Lai & Maria Valentina Lasorella & Rossella Ugati & Anna Vagnozzi, 2023. "Interactive Approach for Innovation: The Experience of the Italian EIP AGRI Operational Groups," Sustainability, MDPI, vol. 15(19), pages 1-24, September.
    8. Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille, 2020. "Difference-in-Differences Estimators of Intertemporal Treatment Effects," Papers 2007.04267, arXiv.org, revised Dec 2024.
    9. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
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