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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/8845A0CD-A5F8-4606-86A4-07CEB3C37893 | ||
| Year | 2018 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | 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 | ||
| Appears in Collections |
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.
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