Comparing Different kind of Vine Copulas Functions to Compute Weather-Based Crop Insurance Premium and Determine Step Function Indemnity for Rainfed Barley in Ahar County

Traditional agriculture insurance suffers an asymmetric information challenges that lead to enormous costs. In addition, since agricultural sector, particularly rainfed production, is more dependent on natural factors and is more impressible of weather situation, politicians must adopt new risk management methods. Weather-based crop insurance schemes are one of these methods that were applied by developing countries and had satisfactory results. In this study, it was attemped to design weather-based crop insurance for Ahar rainfed barley with utilization of the newest approach in computing of dependency structure, i.e., vine copulas functions. The information of yield and weather variables was collected between 1995-2014 from Iranian Agricultural Organization and Metrological Organization, respectively. According to Vuong and Clarke tests, R-vine model was selected to explain joint distribution function of yield and weather variables, then expected loss, premium and step function indemnity were calculated. The calculated premium amount in 80 percent coverage level was 270348 Rials that is less and more reasonable than traditional project premium. The indemnity designing results showed for each certain unit reduction in cumulative rainfall, yield reduction is not linear and constant; hence, the utilization of step function in indemnity paying can provide reliable results.