An Impact Assessment of GHG Taxation on Emilia-Romagna Dairy Farms through an Agent-Based Model Based on PMP

Abstract

The aim of this work is to assess the structural, production, environmental, and economic impact of an increasing tax on climate change gas emissions related to milk production under the current CAP payment system. The analysis is performed using an Agent-Based Model (ABM) based on Positive Mathematical Programming (PMP). The integration between ABM and PMP makes it possible to simulate farmers’ strategies considering the interaction between them, the territorial specificity, and the heterogeneity of farms in the presence of little information on production costs. It also makes it possible to add a social and cultural perspective to the economic factors. The model is calibrated using FADN data for the Emilia-Romagna region (Italy) from the year 2020. The results show that farmers belonging to different age groups make decisions based on economic profitability, but also on their social and cultural background. To maximise their utility functions, farmers can opt for more efficient agricultural management practices that may result in the exchange of production factors, especially land. The overall impact penalises less efficient farms and agricultural production with higher negative externalities.