| The limitations of the expected utility theory in predicting risk preference under low probabilities have been discussed by various experimental studies. However, the existing studies have not arrived at a consensus in this area. There are signs of both over-insurance and under-insurance for low-probability loss events. The topic has particularly not been addressed when ambiguity is coupled with low probability estimates. This paper theoretically analyzes the implications of ambiguity aversion for insurance purchasing in loss events involving low probabilities. The topic has been looked into under the light of forest carbon offsets and the need for insurance for unavoidable losses of the sequestrated carbon. The paper offers an experimental design involving three phases, including a replica of a previous study on insurance behaviour, addition of the ambiguity factor, and two methods of measuring ambiguity preference. Wildfire losses are associated with small probabilities and ambiguity, and ambiguity increases the individual's willingness to pay for insurance. Therefore, the government can set a higher price for its mandatory insurance program provided on forestry offset credits. |
