Subsidy on transport adaptation investment-modeling decisions under incomplete information and ambiguity

This paper models subsidy policies on transport facility's adaptation to climate change-related disasters under the government's incompleteness and ambiguity of disaster information. We consider a transport facility (an airport or a seaport) that is in a vertical structure with an upstream facility operator and a few downstream carriers. The exact probability of disaster damage level is privately known by the facility operator, while the government has incomplete information and has to form a probability distribution. If the government cannot accurately perceive such probability (misjudgment), ambiguity emerges. This is the first modeling work to integrate the incomplete information and ambiguity in one framework to analyze the transport investment under uncertainty. Modeling results suggest that such incomplete information and ambiguity in many cases allow the facility operator to secure information rent, and make the facility output, adaptation investment and social welfare downwardly distorted (i.e., less than the levels under complete information). The ambiguity can bring two countervailing effects under incomplete information, namely the “pooling effect” and the “agency cost effect,” which jointly determine the downward distortions on market outcomes and the welfare-maximizing subsidy policy. When its degree is low, the ambiguity causes a more dominant “pooling effect” that can help alleviate the distortion, improving social welfare. In presence of ambiguity, the increasing optimism of the government would deteriorate the distortion, likely to damage social welfare. Our analytical results provide support to subsidy on adaptation and policies to promote adaptation effectiveness and carrier competition in downstream market. To alleviate possible distortion, the government also needs to be cautious to reduce ambiguity through more information acquisition, and not be too optimistic on the disaster damage.