Subsidy allocation strategies for power industry's clean transition under Bayesian Nash equilibrium

Government subsidies are widely acknowledged as a potent instrument for motivating the power industry toward a clean transition. However, existing literature fails to address interactions between government and firms' strategic behaviors under incomplete information. This study proposes a novel game-theoretic model that considers power firms' heterogeneous transition potentials and multiple policy targets to optimize subsidy allocation strategies. The result demonstrates the existence of a Bayesian Nash equilibrium solution and determines the threshold of transition potential above which firms would transition. Furthermore, an equal-splitting strategy is the only optimal subsidy allocation strategy for maximizing the transitioning firm number. Moreover, the uncertainty of participation and the existence of emission penalties will increase the optimal subsidy size targeting carbon emissions reduction. Interestingly, our comparative analysis suggests that the government should refrain from consistently expanding the industry and the subsidy budget to promote transition and reduce carbon emissions, as such actions increase the volatility of policy implementation and decrease the relative subsidy levels for power firms.