Influence of Government Credit Risk on PPP Projects in Operation Stage

Abstract

In PPP projects, insufficient risk management may lead to the breakdown of partnerships and even project failures. Among them, the government credit risk is regarded as unbearable risk and a key risk affecting PPP projects because of its high frequency and impact. Therefore, based on the contractual relationship between both sides, a principal-agent model for the optimal choice of investors and the government under the government default probability is constructed. This paper explored the quantity relationship of the government credit risk and the project utility through analysing the effect of government default probability perceived by both parties on the investor’s optimal effort level and government allocation ratio. The results demonstrate that the government credit risk will decrease the effort level of investors and have a negative impact on the utility of the project. Furthermore, the government’s modification of the contract allocation ratio based on its own credit rating can offset the negative impact of its credit risk on the effectiveness of the project. But this regulatory effect is limited. The findings effectively provide some insights and theoretical basis for solving the negative effects of government credit risk.

Yushe Coal Mining Subsidence Area Highway Project Analysis

“…The change in law and policy contributed to the early termination of the project. A large amount of academic literature state that government credit risk is the main risk faced by social capital (Zhou and Liu, 2021). The government in this project has shown a low level of creditworthiness.…”

Incentive Mechanisms of an Experimental Resource-Sharing Platform Considering Reputation Effects for Megaprojects

“…In 2022, the Chengdu R&D base of the NTIC invested an additional 148.802 million RMB in the construction of the platform. The investment cost of the digital laboratory was 42.05 million RMB, that of the intelligent construction laboratory was 11 million RMB, that of the disaster warning and prevention and control laboratories was 27.611 million RMB, that of the geography and geology laboratories was 61.501 million RMB, and that of the other laboratories was 6.64 million To better assess the changes and influence of various parameters and to better understand the incentive models used in this paper, it combined the actual situation of this project and related literature (Wang et al, 2020b;Zhou & Liu, 2021;Li et al, 2022a;Liu & Zhou, 2022) through numerical simulation of different scenarios to analyze the impact of the degree of sharing (d) and the reputation impact coefficient (k) on the laboratories' optimal effort level (e * ), fixed funding (α), benefits (W) and the platform's benefits (V). To validate the previous related conclusions, the random perturbations caused by external factors are assumed to obey the N(0, 1) standard normal distribution.…”

Analysis of Collaborative Innovation Behavior of Megaproject Participants Under the Reward and Punishment Mechanism

“…Numerical simulation is often used as a supplement to game analysis, which can not only display the results of the model intuitively but also judge the changing trend between variables by drawing function graphics (Zhou & Liu, 2021). In order to more intuitively analyze the impact of the main objective factors such as participation innovation cost, collaborative innovation participation incentive, collaborative income sharing proportion, achievement transformation income sharing proportion and the main behavioral characteristic factors such as risk aversion coefficient, the loss sensitivity coefficient on the evolution results of collaborative innovation behavior in megaprojects, in this section, MATLAB R2018a software for simulation analysis was used.…”