Renewable energy sources policies in a Bayesian DSGE model

Environmental policy measures to reduce greenhouse gases emission to mitigate climate change are common practice in many developed countries, encompassing both technology-push measures and demand-pull measures. The effectiveness of such policies continues to need investigation, especially when shortsighted measures lead to suboptimal investments in the absence of a credible government commitment. The aim of this paper is to assess the effectiveness of a comprehensive strategy for renewable energy sources in a dynamic stochastic general equilibrium model estimated for the Euro area using Bayesian estimation techniques, which includes carbon tax and subsidy measures. To this end, we compare the cost-effectiveness of technology-push measures and demand-pull measures. Our findings show that the environmental policy based on technology-push measures may produce better dynamic effects than demand-pull measures based on a subsidy policy of equal monetary amount. In fact, RES price parity is estimated to occur sooner by implementing technology-push measures than demand-pull measures.