This paper presents a dynamic agent-based model of land use and agricultural production under environmental boundaries, finite available resources and endogenous technical change. In particular, we model a spatially explicit smallholder farming system populated by boundedly-rational agents competing and innovating to fulfill an exogenous demand for food, while coping with a changing environment shaped by their production choices. Given the strong technological and environmental uncertainty, agents learn and adaptively employ heuristics which guide their decisions on engaging in innovation and imitation activities, hiring workers, acquiring new farms, deforesting virgin areas and abandoning unproductive lands. Such activities in turn impact farm productivity, food production, food prices and land use. We firstly show that the model can replicate key stylized facts of the agricultural sector. We then extensively explore its properties across several scenarios featuring different institutional and behavioral settings. Finally, we simulate the model across different applications considering deforestation and land abandonment; human-induced soil degradation; and climate impacts. AgriLOVE offers a flexible simulation environment to study the endogenous emergence of different agricultural production regimes from the interaction of spatially dispersed farms subject to resource constraints, spatial influence and climate change.

AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model

Coronese M.
;
Occelli M.;Lamperti F.;Roventini A.
2023-01-01

Abstract

This paper presents a dynamic agent-based model of land use and agricultural production under environmental boundaries, finite available resources and endogenous technical change. In particular, we model a spatially explicit smallholder farming system populated by boundedly-rational agents competing and innovating to fulfill an exogenous demand for food, while coping with a changing environment shaped by their production choices. Given the strong technological and environmental uncertainty, agents learn and adaptively employ heuristics which guide their decisions on engaging in innovation and imitation activities, hiring workers, acquiring new farms, deforesting virgin areas and abandoning unproductive lands. Such activities in turn impact farm productivity, food production, food prices and land use. We firstly show that the model can replicate key stylized facts of the agricultural sector. We then extensively explore its properties across several scenarios featuring different institutional and behavioral settings. Finally, we simulate the model across different applications considering deforestation and land abandonment; human-induced soil degradation; and climate impacts. AgriLOVE offers a flexible simulation environment to study the endogenous emergence of different agricultural production regimes from the interaction of spatially dispersed farms subject to resource constraints, spatial influence and climate change.
2023
File in questo prodotto:
File Dimensione Formato  
SSRN-id3944282.pdf

accesso aperto

Tipologia: Documento in Pre-print/Submitted manuscript
Licenza: Dominio pubblico
Dimensione 2.35 MB
Formato Adobe PDF
2.35 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/554651
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
social impact