국가그룹별 환경원단위 효율의 비교
Comparison of Environmental Intensity Efficiency by Country Group
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본 연구의 목적은 확률변경거리모형을 사용하여 CO2와 PM2.5배출량의 환경원단위효율(EIE)을 측정하고 5개 소득 그룹별 원단위 효율을 비교해 보고자 함이다. 원단위효율은 환경규제의 영향을 받는 약처분과 받지 않는 강처분으로 구분하고 원단위비효율오차의 분포는 절단정규분포와 반정규분포로 구분하여 추정하였다. 실증결과에 의하면 CO2와 PM2.5배출량의 약처분추정식에서 동일하게 K의 증가는 CO2를 감소시키는 방향으로 작용하고 있다. 그러나 화석에너지는 CO2배출량을 증가시키는 방향으로 작용한다. 또한 원단위효율의 증가추이에서 PM2.5원단위보다 CO2원단위 효율의 향상속도가 빠르다. PM2.5배출량의 증가가 CO2배출량 증가속도보다 빠르게 진행되고 있다. CO2원단위효율은 고소득그룹, OECD, 저소득그룹이 높았고 PM2.5원단위 효율은 고소득그룹, 상위중간소득그룹, OECD 순서로 높았다. 이처럼 두 원단위 효율은 속한 각 국가의 소득수준에 따른 경제발전단계와 배출량의 차이를 반영한다.
Abstract
The purpose of this study is to measure the Environmental Intensity Efficiency (EIE) of CO2 and PM2.5 emissions using the Stochastic Frontier Distance Function model and to compare the intensity efficiencies across five income groups. The intesnsity efficiency is divided into strong and weak disposability based on the impact of environmental regulations, and the distribution of inefficiency errors in intesnsity efficiency is estimated using the truncated normal and half-normal distributions. Empirical results indicate that an increase in K consistently acts to reduce CO2 emissions in the weak disposability estimation equations for both CO2 and PM2.5 emissions. However, fossil energy tends to increase CO2 emissions. Additionally, in the trend of increasing intesnsity efficiency, the improvement speed of CO2 intesnsity efficiency is faster than that of PM2.5 intesnsity efficiency. The increase in PM2.5 emissions is proceeding faster than the increase in CO2 emissions. The CO2 intesnsity efficiency was highest in the high-income group, OECD, and low-income group, while the PM2.5 intesnsity efficiency was highest in the high-income group, upper-middle-income group, and OECD, in that order. These results reflect the differences in economic development stages and emissions based on the income levels of the respective countries.
참고문헌 (27)
- Aigner, D., "Formulation and estimation of stochastic frontier production function models", Journal of Econometrics, 6(1), pp.21~37 (1977)
- Bai, X., "Environmental efficiency of apple production in China : A translog stochastic frontier analysis", Agricultural and Resource Economics Review, 48(2), pp.199~220 (2019)
- Battese, G. E., "Frontier production function, technical efficiency and panel data : With application to paddy farmers in India", Journal of Productivity Analysis, 3, pp.153~169 (1992)
- Battese, G. E., "A model for technical inefficiency effects in a stochastic frontier production function for panel data", Empirical Economics, 20(2), pp.325~332 (1995)
- Bibi, Z., "Technical and environmental efciency of agriculture sector in South Asia : A stochastic frontier analysis approach", Environment, Development and Sustainability, 23, pp.9260~9279 (2021)
- Chambers, R. G., "Estimating multi-output technologies", American Journal of Agricultural Economics, 71(4), pp.880~995 (1989)
- Cuesta, R. A., "Environmental efficiency measurement with translog distance functions : A parametric approach", Ecological Economics, 68, pp.2232~2242 (2009)
- Duman, Y. S., "Environmental technical efficiency in EU member and candidate countries : A parametric hyperbolic distance function approach", Energy, 147, pp.297~307 (2018)
- Eder, A., "Environmental efficiency measurement when producers control pollutants under heterogeneous conditions : A generalization of the materials balance approach", Journal of Productivity Analysis, 57, pp.157~176 (2022)
- Gong, J. -Y., "Measurement of environmental pollution index and analysis of influencing factors using the stochastic frontier cost function", Environmental Policy, 24(3), pp.207~231 (2016)
- Harrala, R., "Global CO2 efficiency : Country-wise estimates using a stochastic cost frontier", Energy Policy, 45, pp.762~770 (2012)
- Hsiao, W., "Energy efficiency of the Baltic sea countries : An application of stochastic frontier analysis", Energies, 104, pp.1~11 (2019)
- Jondrow, J., "On the estimation of technical inefficiency in the stochastic frontier production function model", Journal of Econometrics, 19, pp.233~238 (1982)
- Kang, M. -J., "Energy intensity effciency and the effect of changes in GDP and CO2 emission", Energy Efficiency, 15(8), pp.1~20 (2022)
- Kang, S. -M., "Development and international comparison of alternative energy efficiency models using the stochastic frontier translog function", Environmental Policy, 25(3), pp.221~256 (2017)
- Kang, S. -M., "Comparison of environmental intensity efficiency by income group using pollution models", Environmental Policy, 30(4), pp.1~27 (2023)
- Kim, K. -H., "Estimation of greenhouse gas emission efficiency of Korean firms using the stochastic frontier model", Journal of Climate Change Research, 10(2), pp.117~128 (2019)
- Kim, K. -W., "Evaluation of environmental performance of 29 provinces in China : Focusing on integrated pollution intensity", Environmental Policy Studies, 10(1), pp.71~91 (2011)
- Lansink, A. O., "CO2 and energy efficiency of different heating technologies in the Dutch glasshouse Industry", Environmental and Resource Economics, 24, pp.395~407 (2003)
- Reinhard, S., "Econometric estimation of technical and environmental efficiency : An application to Dutch dairy farms", American Journal of Agriculture Economics, 81, pp.44~60 (1999)
- Reinhard, S., "Environmental efficiency with multiple environmentally detremental variables: Estimated with SFA and DEA", European Journal of Operation Research, 121, pp.287~303 (2000)
- Reinhard, S., "Analysis of environmental efficiency variation", American Journal of Agriculture Economics, 84(4) (2002)
- Rifkin, J., "3차 산업혁명" (2012), 민음사
- Rifkin, J., "글로벌 그린 뉴딜" (2020), 민음사
- Rødseth, K. L., "Environmental efficiency measurement and the materials balance condition reconsidered", European Journal of Operational Research, 250(1), pp.342~346 (2016)
- Zhou, P., "Measuring economy-wide energy efficiency performance:A parametric frontier approach", Applied Energy, 90(1), pp.196~200 (2012)
- Zhou, Y., "Technical and environmental efficiency of hog production in China : A stochastic frontier production function analysis", Journal of Integrative Agriculture, 14(6), pp.1069~1080 (2015)
