agriLOVE: agriculture, land-use and technical change in an evolutionary, agent-based model with M. Coronese, F. Lamperti and A. Roventini
This paper presents a novel agent-based model of land use and technological change in the agricultural sector under environmental boundaries, finite available resources and changing land productivity. In particular, we model a spatially explicit economy populated by boundedly-rational farmers 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, farmers 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 on land 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 showcase the properties of model in different applications considering deforestation and land abandonment; soil degradation; and climate impacts.
Rain does not fall on one roof alone. Farmers' management strategies to cope with precipitation variability among rainfed marginal systems with A. Mantino, G. Ragaglini, C. Fadda, M.E. Pè and A. Nuvolari
Available upon request
In a changing climate, the awareness of precipitation variability is key to food security of smallholder farmers in rainfed marginal systems. In agricultural areas dependent on rainfall phenomena, households able to interpret correctly short-term precipitation deviations and extremes do retain an advantage in terms of resilience. Despite the communitarian nature of these rural societies, we know little about how collective processes influence rainfall risk perception and households’ awareness. In our study we join data from agronomic surveys, daily rainfall estimates and socioeconomic surveys to explore links between the growth of households’ rainfall awareness and social learning dynamics. We build a repeated cross-section dataset, interviewing 280 smallholder households in the Ethiopian highlands in the spring of 2013 and 2019, while computing the mean, the standard deviation and the maximum of three rainfall parameters during the crop growing seasons. By analysing the growth of the household’s precipitation risk perception and the growth rate of the three rainfall parameters, we identify a measure of farmer’s awareness to short-term rainfall variability, which shows high heterogeneity among neighbouring households. Regressions reveal the role of collective learning, which withstand controls for farmers’ age, gender and income. Instrumenting the idir, an informal institution present in Ethiopian societies, we investigate further the collective formation of rainfall awareness. Our findings suggest that collective mechanisms of learning should be considered in mitigation and risk reduction programs. Our work adds to the growing body of literature screening socioeconomic determinants of risk perception in natural hazards environment; it contributes to the debate on reducing households’ climate vulnerability, advising the consideration of social learning mechanisms in rural policy development.
Is green the new black? An ABM approach on transition toward sustainable agriculture with M. Coronese, F. Lamperti and A. Roventini
Since the last decades economic and population growth increasingly pressured the Earth system. Land management is essential to ensure sustainability of future food security, but it needs to cope with rising global environmental risks and constraints. In this work we extend the agriLOVE agent-based model of an agricultural sector to investigate interactions between different agricultural regimes in an economy exposed to explicit environmental boundaries. In particular, we study the ability of the system to favor a transition to a sustainable regime when prolonged cultivation with conventional techniques yields a slowdown in productivity dynamics, due to soil degradation. We investigate transition dynamics under several behavioral, environmental and policy scenarios. Our results point to strong path-dependece and show how the agricultural sector has a very limited capacity to ease transition towards a sustainable regime if not supported by appropriate policies. Intuitively, the transition is negatively affected by the velocity and timing of the phenomenon of soil-erosion. The presence of incomplete information has an ambiguous role: being endowed with more information paradoxically lower transition likelihood, although it speeds up the velocity of the transition itself. We further show the existence of trade-offs between distinct spatial configuration, particularly between different degrees of sustainable farms clusterization. Finally, we demonstrate how subsidies to sustainable farming are relevant to avoid lock-ins of conventional farming, but they are only marginally effective in fostering transition. Taxes on conventional farming can help the diffusion of sustainable practices, but conditional on being severe and targeted at R&D activities.