以綜合隨機效用模型衡量遊憩之經濟價值

Measuring the Economic Benefits from Recreation by Using the Mixed Logit Model

間斷反應模型（discrete response models）被廣泛應用在資源管理，交通研究，商品選擇，以及休閒研究等許多領域。其中，綜合隨機效用模型（the mixed logit model）饒富趣味，因為它相當有彈性（flexible）。它可以逼近所有基於效用極大化（random utility maximizing）之間斷反應模型，它也可以刻化消費者之隨機異質性偏好（random heterogeneous preference），此為其他模型所無之優點。休閒研究的最終目的，通常是對遊憩地點之增減，或環境品質之改變，的經濟價值之衡量。以綜合隨機效用模型估計休閒需求時，對於經濟福利效果的計算，乃新興之學術主題。目前有兩種方式：第一個方式將隨機項視為偏好差異；第二個方式將隨機項視為衡量之誤差。僅有的少數文獻以實證顯示，第一個方式所得之效益值總是顯著大於第二個方式所得之效益值。本研究以不同之實證資料，在較多個遊憩地點，及較多種機率分配組合下，發現對隨機項之解釋，有時候顯著影響以綜合隨機效用模型所得到之經濟價值。本研究亦首度發現，第一個方式所得之效益值並非總是大於第二個方式所得之效益值。此外，本研究亦以實證舉例，當使用綜合隨機效用模型估計休閒需求，而且旅遊成本（travel cost）的參數是可變參數時，第一個方式所得到之經濟價值會產生嚴重誤差。第一個方式之變形，則無此缺陷。這些貢獻，幫助人們對綜合隨機效用模型之瞭解。特別是如何使用此模型來衡量遊憩之經濟價值。因此，本研究有助於此模型在休閒研究，自然資源管理，以及其它領域之應用。

Discrete response models have been applied to many fields such as resource management, transportation studies, commodity brand studies, and recreation studies. The mixed logit model (MXL) is interesting because it is flexible, in a sense that it is a generalization of all discrete response models based on random utility maximization. The MXL can capture the random heterogeneous preference of the consumers, which is its unique strength among discrete response models.Typically, the ultimate goal of recreation studies is to obtain economic benefits related to changing site attributes or availability. The literature states that the welfare effects obtained by using the MXL are significantly affected by the interpretation of its random terms. One interpretation denotes the randomness as capturing taste differences among the consumers, another denotes the random terms as capturing measurement errors. The literature finds that the welfare effects the welfare effects based on the first interpretation are all substantially larger than those the welfare effects based on the second interpretation. This study uses a different data set. With more sites and under more distributions of the random parameters, I find that the interpretation of its random terms sometimes significantly affects the welfare effects. However, the welfare effects based on the first interpretation is not always larger than the welfare effects based on the second interpretation.This study also uses empirical data to illustrate that, when the travel cost is a random parameter, the welfare effects based on the first interpretation is significantly biased. A third formula based on the same interpretation is appropriate. These findings help understanding the welfare measurement when using the MXL. Therefore, it helps the application of the MXL in the study of natural recreational resource management as well as in other fields.