Econometric modelling for estimating direct flood damage to firms: a micro-scale approach using post-event records in Italy

Managing flood risk is crucial for achieving global sustainability. Flood damage to firms' assets, in particular, imposes significant financial stress, necessitating efforts to minimize future consequences. However, current tools and knowledge for estimating flood damage to firms are inadequate, primarily due to a lack of high-quality damage data and the diversity of firm characteristics, complicating generalization. This study aims to improve understanding of micro-scale flood damage to firms in Italy through the analysis of empirical data, focusing specifically on direct damage. The dataset comprises 812 observed damage records collected after five flood events. Damage is categorized into building structure, stock, and equipment. The analysis reveals relationships between damage, economic sector, and water depth. Results indicate that damage increases at a rate less than proportional to the firm surface area and with water depth significantly explaining only stock damage. The quantification of damages across different sectors shows that healthcare facilities register the highest average damage to building structures, the commercial sector is most affected in terms of stock damage, and the manufacturing sector exhibits the greatest average damage to equipment. The derived damage model offers better predictive accuracy than foreign models in the Italian context. These findings aid in developing effective, tailored risk mitigation strategies and provide valuable insights for future research and policy aimed at reducing flood impacts on firms in Italy.