RIEBセミナー（科研基盤研究(S)「包括的な金融・財政政策のリスクマネジメント：理論・実証・シミュレーション」共催）
RIEB Seminar (Jointly supported by:Grant-in-Aid for Scientific Research (S))

日時 2016年12月9日（金）午後3時30分から午後5時00分まで
会場 神戸大学経済経営研究所　調査室（兼松記念館1階）
対象 教員、院生、および同等の知識をお持ちの方
使用言語 英語
備考 論文のコピーは共同研究推進室にご用意いたします。

3:30pm～5:00pm

報告者 Youngho CHANG
所属 南洋理工大学人文社会科学院
論題 Energy R&D and Climate Change: An Endogenous Growth and Technology Model
概要 This study aims to examine how R&D in fossil fuels and backstop resources and resulting technology progress influence resource use, economic growth and climate change in the world economy. It constructs an economic growth model with two sectors and multiple resources, incorporating environmental constraints from climate change models such as general circulation models (GCMs). The model is expected to suggest two switching points: R&D and resource switching points. The technology progress appears to lead to the endogenous substitution among different energy resources and affect the speed of carbon dioxide accumulation in the atmosphere. A fossil fuel with the lowest conversion cost is to be used first and over time it is replaced by another fossil fuel with the next lowest conversion cost. R&D in fossil fuels and backstop resources appear to accelerate the substitution among fossil fuels by accumulating the knowledge stock of using fossil fuels and at the same time it eventually helps the economy switch to the backstop resources as zero extraction cost and the accumulation of knowledge stock of backstop resources make the cost of using backstop resources competitive to fossil fuels. With the accumulation of knowledge stock on backstop resources, fossil fuels will be eventually replaced by backstop resources as their costs become lower and competitive to fossil fuels thanking to no or little extraction cost and decreases in conversion costs. The resource switching point comes after the R&D switching point. This study also shows that the level of carbon emissions and the corresponding temperature change, which reflect how technological change and R&D influence climate change. The derived optimal trajectory of carbon tax rate indicates the cost of adapting to climate change.