An empirical study of parametric insurance for drought risk

The rising incidence and impact of natural disasters have thus increased the need for efficient risk transfer solutions. Conventional indemnity insurance contracts tend to inadequately address financial risks associated with natural disasters due to transaction costs, time-consuming claims settlement, and moral hazard. Parametric insurance, which provides compensation based on predefined indices such as weather cycles or earthquake activity, has thus become a promising alternative (Barnett & Mahul, 2007). This research paper examines the application of parametric insurance as a new paradigm to address climate change risks, especially those associated with drought conditions on the Veneto coast of Lake Garda. After a brief analysis of the most relevant theoretical contributions on parametric insurance, a case study is proposed to calibrate a parametric insurance contract to mitigate drought risks. Using historical rainfall records from ARPA Veneto (Regional Agency for Environmental Prevention and Protection of Veneto), this research demonstrates that empirical statistical methods, including non-parametric density estimation and simulation techniques, provide an effective framework for pricing parametric insurance contracts (Figueiredo et al., 2018). The proposed methodology offers a transparent and data-driven approach for supporting climate adaptation strategies while contributing a replicable framework for drought risk transfer in agricultural systems.