Title of Paper:Contracting and renegotiating with a loss-averse private firm in BOT road projects

Hits:

Date of Publication:2018-06-01

Journal:TRANSPORTATION RESEARCH PART B-METHODOLOGICAL

Included Journals:SCIE、EI、SSCI

Volume:112

Page Number:40-72

ISSN No.:0191-2615

Key Words:BOT road; Renegotiation; Loss aversion; Contract design

Abstract:In BOT road project, the government offers a firm an ex ante contract, which specifies toll price and concession period based on the forecasted demand. When the demand states are observed in the operation period, the government may request renegotiation to adapt the initial contract to the realized demand state. By considering the loss aversion behavior of the private firm, this paper shows that renegotiation takes place only if the private firm's extent of loss aversion is sufficiently small. However, in what direction the government adjusts toll price and concession period depends on the combined effects of initial price, demand level, and demand uncertainty in each demand state. This paper has further investigated the optimal initial contract. We find that if one demand state realizes with a sufficiently large probability, then the optimal initial contract is renegotiation-proof in this demand state while inducing renegotiation in other demand states; if all demand states realize with almost equal probabilities, whether the optimal initial contract prevents or induces renegotiations in all demand states depends on the private firm's extent of loss aversion. This paper makes two major contributions to the literature. First, we apply loss aversion to the context of renegotiation in BOT road projects and show that renegotiation is costly. Second, we consider the optimal_initial contract in anticipation of ex post renegotiation and show that the government should trade off between ex ante social welfare and ex post psychological loss. To obtain more insights and to strengthen our model results, we have reexamined the optimal renegotiation and initial contracts under some relaxed assumptions. (C) 2018 Elsevier Ltd. All rights reserved.