Green Investment with Capacity Choice Under Subsidy Retraction Risk

Investments in renewable energy (RE) projects have received considerable support from governments to accelerate the energy transition. However, government support also creates uncertainty for investors, as it can be changed or withdrawn at any time. This dissertation studies the investment decision of a firm planning to develop a RE project, determining the optimal investment timing and the optimal capacity to be installed. To address this problem, we develop a real options model with a feed-in tariff (FIT) subsidy, in which the subsidy withdrawal time is modeled as an exponentially distributed random variable. The investment problem is solved analytically and the results are illustrated through a numerical example and a comparative statics analysis. The results show that subsidies do not necessarily accelerate investment. Instead, a critical level of subsidy is needed to accelerate investment. Subsidies below this level delay investment compared to the unsubsidized case. Although high levels of subsidy reduce the optimal installed capacity, low levels of subsidy increase capacity. The impact of subsidy withdrawal risk also depends on the level of financial support. For sufficiently high subsidy levels, an increase in the probability of withdrawal raises the optimal investment threshold, while installed capacity has a non-monotonic behavior. Both remain below the unsubsidized case. For lower subsidy levels, both the optimal investment threshold and installed capacity have non-uniform behaviors as the risk of subsidy withdrawal increases. This study provides important contributions for investors and policy makers, demonstrating that the effectiveness of support policies depends not only on the level of subsidy, but also on its credibility and predictability.