The stylized model presented in this paper extends the approach developed by Fischer and Newell (2008) by analysing the optimal policy design in a context with more than one externality while taking explicitly into account uncertainty surrounding future emission damage costs. In the presence of massive uncertainties and technology spillovers, well-designed sup-port mechanisms for renewables are found to play a major role, notably as a means for compensating for technology spillovers, yet also for reducing the investors’ risks. How-ever, the design of these support mechanisms needs to be target-aimed and well-focused. Besides uncertainty on the state of the world concerning actual marginal emission damage, we consider the technological progress through R&D as well as learning-by-doing. A portfolio of three policy instruments is then needed to cope with the existing externalities and optimal instrument choice is shown to be dependent on risk aversion of society as a whole as well as of entrepreneurs. To illustrate the role of uncertainty for the practical choice of policy instruments, an em-pirical application is considered. The application is calibrated to recent global data from IEA and thus allows identifying the main drivers for the optimal policy mix. In addition to assumptions on technology costs and uncertainty of emission damage cost, the importance of technology spillover clearly plays a key role. Yet under some plausible parameter settings, direct subsidies to production are found to be of lower importance than very substantial R&D supports.
Externality technology learning uncertainty climate change spillover renewable energy policy