Agricultural Productivity in Latin America and the

Up to 70% of agricultural productivity growth in Latin America and the Caribbean is reduced when environmental costs are taken into account. The increase in production has been driven mainly by the intensive use of inputs rather than by technological or managerial improvements, highlighting the need for policies that integrate sustainability and innovation. (IDB, 2025)

Salazar, L., Tadeo Ruesta, D. V., Alvarez, L., Bernal Hernandez, S. ., & Martel, P. (2025). Agricultural Productivity in Latin America and the Caribbean (1961-2021): Subregional and National Analysis. Balduzzi Fiallos, M. S. (Ed.).

Climate investment required

US$2.1 to US$2.8 trillion is the estimated range of cumulative investment through 2030 in LAC to meet climate commitments, per the report (ECLAC, 2025).

2,1 a 2,8 billones de dólares es el rango de inversión acumulada estimada hasta 2030 en ALC para cumplir compromisos climáticos, según el informe (CEPAL, 2025).

Climate equivalent annual investment required

3.7% to 4.9% of regional GDP is the estimated average annual equivalent of climate investment through 2030 in LAC (ECLAC, 2025).

3,7% a 4,9% del PIB regional es el equivalente anual promedio de la inversión climática estimada hasta 2030 en ALC, según el informe (CEPAL, 2025).

Productive Articulation Initiatives (PAI)

687 IAPs make up the database with information used to classify productive articulation initiatives financing sources in 18 countries (2023–2025), according to the note in the report’s financing chart (ECLAC, 2025).

687 IAP conforman la base con información usada para clasificar fuentes de financiamiento de iniciativas en 18 países (2023–2025), según la nota del gráfico de financiamiento del informe (CEPAL, 2025).

PAI: focused on specialized public infrastructure

0.4% of the 497 productive articulation initiatives (PAI) (same 20 countries; 2023–2025) focus on specialized public infrastructure development (ECLAC, 2025).

0,4% de las 497 iniciativas de articulación productiva (IAP) (en los 20 países listados; 2023–2025) reporta como foco estratégico el desarrollo de infraestructura pública especializada, según el informe (CEPAL, 2025).

PAI Governance

In “almost all” cases, productive articulation initiatives (PAI) (in the same 20 countries) are managed by a decision-making body averaging 11 people, with composition mainly private sector (72.7%), then civil society (15.0%), public sector (10.2%), and academia (1%) (ECLAC, 2025).

En “casi la totalidad” de los casos, las iniciativas de articulación productiva (IAP) (en los 20 países listados) son gestionadas por un órgano de decisión conformado por un promedio de 11 personas; además, ese órgano se compone mayoritariamente por sector privado (72,7%), seguido de sociedad civil (15,0%), sector público (10,2%) y sector académico (1%), según el informe (CEPAL, 2025).

Agricultural policies in Peru 2019-2022

State support for the Peruvian agricultural sector (2019–2022) is analyzed using the OECD methodology (PSE and GSSE), quantifying subsidies, general services, and competitiveness programs, and linking them to the sector's GHG emissions. It assesses its consistency with the NDCs and the National Agricultural Policy 2021–2030, highlighting the need to reorient incentives towards climate-smart and low-carbon agricultural practices.

Banco Interamericano de Desarrollo (BID)

De los Santos, J., Muñoz, G., Tellez-Lara, N., Rondinone, G., & De Salvo, C. P. (2025). Políticas agropecuarias en Perú 2019-2022: análisis y cuantificación de los apoyos y su vinculación con las emisiones de gases de efecto invernadero.

Building towards Sustainable Development Goal

Building towards the goal of zero hunger, the food and agriculture sector must be considered when designing nutritional interventions (Duncan et al., 2022).

Construyendo hacia el objetivo de hambre cero, el sector alimentario y agrícola debe ser considerado al diseñar intervenciones nutricionales (Duncan et al., 2022).

Duncan, E., Ashton, L., Abdulai, A. R., Sawadogo-Lewis, T., King, S. E., Fraser, E. D. G., Vosti, S., Haines, J., Knight, F., & Roberton, T. (2022). Connecting the food and agriculture sector to nutrition interventions for improved health outcomes. Food Security, 14, 657-675. https://doi.org/10.1007/s12571-022-01262-3

Evidence detail

Instituto de Ciencia y Tecnología Agrícolas (ICTA)

ICTA

Predictive models and food security

The study conducts a comprehensive review of the use of predictive models to strengthen food security in Latin America, with an emphasis on Colombia. It analyzes 65 studies published between 2014 and 2024 that apply algorithms such as Random Forests and Neural Networks to anticipate agricultural yields, manage climate risks, and optimize resources. The results show that agricultural, climatic, and technological variables predominate, while socioeconomic and nutritional dimensions are underrepresented. The article highlights the need to integrate multidimensional data to develop more robust models that strengthen the resilience and sustainability of food systems in the region.

Universidad de Santander: Bucaramanga, Santander, Colombia. Universidad El Bosque: Bogotá, Bogota D.C., Colombia. Universidad Tecnológica de Pereira: Pereira, Colombia.

Trejos-Suárez, J., Pardo, L. V. C., Tabares, J. E., Garzón, S., Bryon, A., & Alarcón, Z. (2025). Modelos predictivos para la seguridad alimentaria en América Latina: Una revisión de alcance. Archivos Latinoamericanos de Nutrición, 75(2), 129-142.