Το έργο με τίτλο Renewable energy sources policies in a Bayesian DSGE model από τον/τους δημιουργό/ούς Argentiero Amedeo, Bollino Carlo Andrea, Micheli Silvia, Zopounidis Konstantinos διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
A. Argentiero, C.A. Bollino, S. Micheli and C. Zopounidis, "Renewable energy sources policies in a Bayesian DSGE model," Renew. Energy, vol. 120, pp. 60-68, May 2018. doi: 10.1016/j.renene.2017.12.057
https://doi.org/10.1016/j.renene.2017.12.057
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.