Optimal R&D Investment Strategy of Pollution Abatement and Incentive Mechanism Design under Asymmetric Information

The study examines optimal pollution control R&D investment strategy of firms under asymmetric information and further analyzes the impact of government incentive mechanism on it. We use stochastic optimal control theory to get the exact solution of R&D investment strategy and incentive mechanism. Our analysis reveals that if there is no supervisor, firms choose not to cooperate, but the government can take appropriate incentive compensation to make firms reach Nash equilibrium. If there are supervisors, the optimal strategy of the enterprise is to choose cooperation, and there will be Pareto optimum among the firms. Furthermore, the R&D investment level decreases with increasing environmental uncertainty.

Automated summary

The study examines the optimal pollution control R&D investment strategy of firms under asymmetric information and the impact of government incentive mechanisms on it. Findings show that without supervisors, firms may choose not to cooperate, but government incentives can help reach Nash equilibrium; with supervisors, firms tend to choose cooperation, potentially achieving a Pareto optimum.