Data envelopment analysis with three inputs (labour, capital, renewable energy supply), GDP as desirable output and carbon emissions as undesirable output, across 31 OECD countries; the Malmquist productivity index estimates average efficiency change from 2004 to 2011.
재생에너지의 환경효율성을 OECD 31개국에 대해 정태·동태 양 측면에서 분석했다. 자료포락분석(DEA)으로 노동·자본·재생에너지 공급을 투입으로, GDP를 바람직한 산출로, 탄소배출을 바람직하지 않은 산출로 두고 효율성을 측정했다. 결과는 OECD 내 지역 간 뚜렷한 차이를 보여 OECD 아메리카가 평균 환경효율성이 가장 높았고 OECD 유럽은 편차가 가장 컸다. 2004~2011년 맘퀴스트 지수로 본 동태적 효율성은 미국발 글로벌 금융위기의 영향을 받았으며, OECD 국가들은 추격(catch-up)과 프론티어 이동(frontier shift) 전략을 함께 사용했다.
Q. What does 'environmental efficiency' mean in this study?
It is a relative frontier measure: how much GDP a country produces from labour, capital and renewable energy supply while generating as little carbon emission as possible. Carbon is modelled as an undesirable output rather than ignored.
Q. Why use DEA rather than a regression?
DEA is non-parametric, so it does not impose a functional form on the production relationship and can handle multiple inputs and outputs — including undesirable ones — at once.
Q. What is the difference between catch-up and frontier shift?
Catch-up is a country moving closer to the existing best-practice frontier; frontier shift is the frontier itself moving outward through technical progress. The Malmquist index decomposes efficiency change into both.
In recent years, renewable energy and environmental efficiency have been interesting issues for both academics and industry actors when discussing sustainable development. Against this background, the present study examines the environmental efficiency of renewable energy from the static and the dynamic perspective in 31 OECD countries, a study conducted to understand the impact of renewable energy across countries. As a non-parametric methodology, data envelopment analysis is used to measure environmental efficiency through multiple inputs and outputs. Labor, capital, and renewable energy supply are the three inputs, while GDP is the desirable output and carbon emissions are the undesirable output. To measure the dynamic environmental efficiency of renewable energy, the Malmquist productivity index is applied to estimate the average efficiency change from 2004 to 2011. The results demonstrate geographical differences in environmental efficiency across the OECD. Countries in OECD America have the highest average environmental efficiency and those in OECD Europe have the largest standard deviation. We also find that dynamic efficiency is influenced by the global financial crisis triggered in the United States. Further, we show that OECD countries implement both catch-up and frontier shift strategies to improve environmental efficiency.