EURO 2024 Copenhagen
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2474. Unveiling Behavioral Heterogeneity: An Agent-Based Model Exploration of Farmer Decision-Making in the Face of Climate Change

Invited abstract in session TB-43: Simulation in sustainability, stream Agent-based Models in Management, Economic and Organisation Sciences.

Tuesday, 10:30-12:00
Room: 99 (building: 306)

Authors (first author is the speaker)

1. Paolo Gazzotti
Department of Electronics, Information and Bioengineering, Politecnico di Milano
2. Sandra Ricart
Department of Electronics, Information and Bioengineering, Politecnico di Milano
3. Andrea Castelletti
Electronics, Information, and Bioengineering, Politecnico di Milano

Abstract

In the face of climate change threats to agriculture, understanding farmers’ decisions on crop selection and irrigation practices becomes crucial, as they tend to be significantly shaped by risk preferences. Farmers, who all recognize shifts like increased drought severity, exhibit diverse reactions influenced by individual risk aversion, satisfaction, uncertainty, and peer comparisons. Agent-based modeling (ABM) stands out as an essential tool for capturing system dynamics and simulating farmers-environment-climate interactions. Despite calls for realistic human behavior integration, the prevailing paradigm still favors rational agents.
Here we present an ABM application in Italy's Adda River basin, modeling farmers' decisions on crops and irrigation methods. To understand the system's response and resilience to changing climates, we implemented diverse behavioral sub-models. The first maximizes profit with classic perfect foresight. The second introduces climate uncertainty and risk aversion variations based on farmers' memory. The third, a comprehensive behavioral model, considers reference points and loss aversion, acknowledging decisions beyond profit. It offers a holistic view of farmers' choices amid uncertainty and risk, calibrated with collected survey data. Preliminary findings uncover significant differences in system dynamics and resilience across the behavioral setups, providing insights into their efficacy and suitability.

Keywords

Status: accepted

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