Structural Vector Autoregressive Approach to Evaluate the Impact of Electricity Generation Mix on Economic Growth and CO2 Emissions in Iran
2020 · Energies
저자
Bahareh Oryani, Yoon‐Mo Koo, Shahabaldin Rezania
연구주제
Energy, Environment, Economic Growth · Climate Change Policy and Economics
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
에너지/자원 > 온실가스 처리에너지 외
배정 근거: AI 키워드가 잡은 NTIS 과제의 분류(정책 연계 맵과 같은 방법).
AI 연구 키워드·방법
이산화탄소 배출 electricity generation mix energy growth nexus renewable electricity generation
structural vector autoregression
키워드 (OpenAlex)
renewable electricity generation electricity mix economic growth CO2 emissions energy mix fossil fuels environmental policy sustainable development
초록
This research attempts to evaluate the impact of renewable electricity generation mix on economic growth and CO2 emissions in Iran from 1980 to 2016. In this regard, by using EViews 10, the Structural Vector Autoregressive model (SVAR) is estimated by imposing the Blanchard and Quah long-run restrictions. The yearly data on real Gross Domestic Production (GDP), the share of electricity generation from renewable sources, and carbon dioxide emissions (CO2) caused by liquid, solid, and gaseous fuels were used. The positive impact of one standard deviation shock of increasing the share of renewable electricity on economic growth was confirmed by using Impulse Response Function (IRF). Contrary to the expectation, the share of renewable electricity in the energy mix is not at a desirable level to lower CO2 emissions, which partly could be explained by the dominant role of fossil fuel in Iran (…
이 논문을 지원한 국가R&D 과제 (NTIS 성과)
| 연도 | 과제 | 부처 | 사업 | 수행기관 | NTIS 분류(1순위) |
|---|---|---|---|---|---|
| 2020 | 수송부문 신기술의 지속가능성을 평가하기 위한 통합모형 구축 연구 | 과학기술정보통신부 | 개인기초연구(과기정통부)(R&D) | 서울대학교 | 환경 > 환경예측/감시/평가에너지 외 |
인접 그래프
노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동
이 문서와 연결된 페이지
교수 1
연구주제 1
Energy, Environment, Economic Growth