| Asian countries such as Thailand are emerging markets. In the Thai case, the insurance industry is mainly dominated by the life and non-life segments. The focus of this study is one type of non-life insurance, namely crop insurance. Thailand has the fifth biggest harvested area of rice of any country in the world, yet its average yields are lower than a number of countries whose crop area is substantially smaller. Climate-related factors play a crucial role in terms of growing rice, and in addition the number of natural disasters appears to have been growing year by year, substantially affecting farmers. This investigation examines a potential approach for risk mitigation in the case of major rice crop insurance to take care of their interests, i.e. the area-yield index, using weather variables. Historical data from 1995-2011 for crop rice spanning six provinces in northeastern Thailand (that is, Loei, Nakhonphanom, Nongbualamphu, Nongkhai, Sakonnakhon and Udonthani) are considered to verify the feasibility of this policy.;The first vital step is the selection of the area to reduce basis risk, with the results showing that on the basis of the relevant variables examined, there are differences between the provinces studied in terms of both area and climate. After that, the investigation of factors affecting rice cropping is conducted. Among variables of interest, rainfall and rainy days are important for rice yield. Subsequently, the functions of the anticipated yields for the relevant provinces are produced using linear regression and spline regression analyses; and based on trigger yields created at coverage levels within the range from 70% to 95% (mainly focusing at 80%, 85%, 90% and 95%) and two protection levels (100% and 150%), a strikingly wide variety of premium rates for the provinces being examined are established.;The findings reveal that using the uniform flat premium currently seems inappropriate. Further investigations could shed light on other parts of Thailand and other Thai cash crops. Finally,,this work can be used as a starting point for specific premium models in future.;Keywords: area-yield index crop insurance, Thai rice, weather-related factors, linear regression analysis, spline regression analysis. |
