Time-Series Similarity and Clustering of Producer Share Dynamics in Agrifood Markets: Evidence from Origin–Destination Price Relationships

Abstract:

Producer share indicators summarize how value is distributed along agrifood supply chains, yet their temporal dynamics remain difficult to compare across products and periods. This paper proposes a reproducible time-series analytics framework to characterize and group producer-share trajectories derived from paired origin–destination price series. We compute producer share time series for a set of agrifood products and quantify similarity using complementary measures capturing co-movement and shape, including Pearson-correlation-based proximity and Euclidean distance on standardized representations. To reduce dimensionality and mitigate noise, we apply principal component analysis and perform unsupervised clustering (k-means) to identify classes of products exhibiting comparable producer-share dynamics. The resulting clusters provide an interpretable typology of market behaviors, highlighting homogeneous groups that may share structural drivers (e.g., commercialization patterns or intermediation margins). We further discuss how cluster membership can support decision-making in crop substitution and market monitoring by revealing products with analogous temporal responses. The proposed pipeline is simple to implement, fully data-driven, and adaptable to other commodity-price settings.

Aplicación:

El artículo A time‑series clustering framework for producer‑share dynamics in agrifood supply chains proporciona una metodología cuantitativa para analizar cómo se distribuye el valor económico a lo largo de la cadena agroalimentaria, un aspecto central para comprender los problemas estructurales que afectan a los productores de la Huerta Valenciana. Mientras que previamente se han estuadiado los patrones estructurales que condicionan la sostenibilidad económica del sistema agrario, a continuación se propone un pipeline analítico reproducible basado en series temporales de precios origen-destino que permite calcular la cuota del productor (producer share) y analizar su evolución en el tiempo.

We would like to acknowledge funding from the Generalitat Valenciana (Spain) through the PROMETEO 2024 CIPROM/2023/32 grant.