天氣指數型保險之綜效 以台南虱目魚為例

Abstract

本研究利用1985-2015年台灣台南的虱目魚產量資料以及氣溫資料，針對虱目魚設計天氣指數型保險並檢測其有效性。我們發現HDD(Heating Degree Days)與虱目魚產量有顯著的相關性，可以做為衡量虱目魚低溫風險的指數。因此我們使用Campbell & Diebold的氣溫預測模型預測未來一年的HDD指數分配，發現此模型能有效地描述台南氣溫與氣溫波動度的季節性。由於產量的分配並非常態，因此我們用分量迴歸設計保單，並計算保單的賠付門檻值、賠付型態以及價格。最後我們設計三個情境，考量政府的保費補貼、天然災害救助金以及保險公司收取的附加保費於漁民的財富中，並以二階隨機優越法則比較不同決策，以檢測保單的避險效果。我們發現若保險公司有收取附加保費下，政府必須進行保費補貼漁民才會選擇購買保險。此外由於虱目魚產量不僅只受低溫寒害的影響，導致天氣指數型保險在避險效果上不及天然災害救助。然而，我們發現若將天氣指數型保險與天然災害救助結合，作為一個新的避險工具與天然災害救助比較時，則漁民能有更好避險效果，政府也能減少支出，且保險公司藉由開辦保險業務而有獲利的來源，這即為天氣指數型保險所產生的綜效。

We propose to design a weather index-based insurance(WIBI) for milkfish in Tainan, Taiwan and evaluate its risk-reducing potential by using yield and temperature data from 1985 to 2015. We find Heating Degree Days(HDD) as an appropriate proxy for the frost risk of milkfish. Thus, we use the temperature forecasting model from Campbell & Diebold to forecast one-year ahead HDD density. We comfirm that the model performs well on modeling seasonality of temperature and volatility in Tainan. Because of non normal yield distribution, we propose to use quantile regrssion on contract design and calculate strike level, payout and premium of WIBI. We also design 3 scenarios and consider premium subsidy, natural disaster relief fund, and premium loading into farmers’ wealth function and evaluate risk reduction by Second Stochastic Dominance Approach(SSD). On conditional that premium loading is added, we find that WIBI is effective only when government subsidizes. Furthermore, due to the variety of weahter risk factors, WIBI is less effective than natural disaster relief fund. In addition, we find that with WIBI and natural disaster relief fund combined, it provides more risk reduction for farmer, less fisical burden for government and more profit for insurance companies. Thus, we conclude that WIBI creates synergy for the players in the market.