국내 도로화물운송업의 리바운드 효과 추정 및 정책적 시사점
Rebound Effects and Policy Implications in Korean Road Freight Transport Industry
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본 연구에서는 2005~2014년 영업용 화물자동차 운전자들의 분기별 화물운송실적 자료를 이용하여 국내 도로화물운송업의 업종 및 품목별 리바운드 효과를 추정하였다. 구체적으로 추정모형은 크게 종속변수를 차량운행거리와 화물운송거리로 구분하여 설정하였고, 설명변수는 가격변수 외에도 시간변수, 운전자 특성변수, 차량 특성변수, 운송 특성변수 등을 포함하였다. 모든 추정모형들은 이분산성을 고려한 일반최소자승법을 적용하여 분석되었다. 실증분석결과, 모든 추정모형들과 대부분의 추정계수들은 통계적으로 유의하게 나타났으며, 화물운송거리를 기준으로 한 국내 전체 도로화물운송업의 리바운드 효과의 크기는 28.9%로 분석되어 유사 해외 연구결과에 비해 상대적으로 크게 분석되었다. 업종별로는 개별화물이 51.3%로 가장 크고, 용달화물(29.5%), 일반화물(16.9%)의 순으로 분석되었고, 품목별로는 개별 및 용달화물에 속하는 기타화물이 43.3%로 가장 크고, 이어서 대부분 일반화물에 속하는 유류(41.2%), 시멘트(33.1%), 컨테이너(24.3%), 철강(23.0%)의 순으로 분석되었다. 본 연구에서 도출된 국내 도로화물운송업의 리바운드 효과 추정결과는 향후 도로화물부문 에너지 효율화 정책수립을 위한 정책수단 선정과 에너지 및 온실가스 절감효과에 대한 사전 평가에 있어 정량적인 기초자료로 활용될 수 있다고 판단된다.
Abstract
The objective of this study is to estimate the scale of rebound effects in the Korean commercial road freight transport industry, using 2005-2014 road freight transportation survey data of individual truck drivers. For this purpose, various models are constructed where vehicle kilometers traveled (VKT) and freight kilometers traveled (FKT) are used as dependent variables and explanatory variables. These variables include time, driver characteristics, vehicle characteristics, transportation characteristics, and prices. All models are estimated by using a heteroscedasticity augmented pooled GLS model. Empirical results indicate all model and estimated coefficients are statistically significantly different from zero at the 1 percent level, based on the Wald test and p-values. Using FKT dependent variables, the scale of rebound effects is calculated as 28.9 percent in the whole commercial road freight transport industry and this value is higher than rebound effects in foreign countries. Concretely, the medium-sized cargo truck sector (51.3 percent) ranks the highest in rebound effects, followed by the small-sized pick-up truck sector (29.5 percent), and general cargo sector (16.9 percent). In addition, the rebound effect of other goods (43.3 percent) ranks the highest, followed by oil products (41.2 percent), cement products (33.1 percent), container goods (24.3 percent), and steel products (23.0 percent) at the lower end. These results provide quantitative data which can be applied in selecting policy instruments to establish energy efficiency policies of the road freight transportation industry and assessing preliminary policy effects.
참고문헌 (32)
- 2014 국가물류비 조사 및 산정, "권혁구", 한국교통연구원, ~ (2016)
- 김대욱, "에너지 소비효율 개선과 리바운드 효과:수송부문을 중심으로", 자원환경경제연구, 21(2), pp.321~340 (2012), 한국환경경제학회
- 에너지 총조사보고서, "산업자원부", ~
- 국가 에너지절약 및 효율향상 추진체계 개선방안 연구: 산업부분의 에너지효율 평가, "이성근", 에너지경제연구원, ~ (2007)
- 이재훈, "교통부문의 에너지 절감방안", KOTI World -Brief, 1(8), pp.5~6 (2009)
- 화물자동차운송시장 실태조사를 활용한시장평가지표 개발방향, "정승주", 한국교통연구원, 7~ (2007)
- "한국석유공사 석유정보망"[URL]
- Ajanovic, A., "The role of efficiency improvements vs. price effects for modelling passenger car transport demand and energy demand-lessons from European countries", Energy Policy, 41, pp.36~46 (2012)
- Berkhout, P. H. G., "Defining the Rebound Effect", Energy Policy, 28, pp.425~432 (2000)
- Birol, F., "Prices, technology development and the rebound effect", Energy Policy, 28, pp.437~469 (2000)
- Borger, B., "The determinants of fuel use in the trucking industry-volume, fleet characteristics and the rebound effect", Transport Policy, 24, pp.284~295 (2012)
- Evans, A., "The rebound effect in the aviation sector", Energy Economics, 36, pp.158~165 (2013)
- Frondel, M., "Heterogeneity in the rebound effect: further evidence for Germany", Energy Economics, 34, pp.461~467 (2012)
- Greene, D. L., "Vehicle use and fuel-economy: how big is the rebound effect?", Energy Journal, 13, pp.117~143 (1992)
- Greene, D. L., "Fuel economy rebound effect for U.S. household vehicles", Energy Journal, 20, pp.1~31 (1999)
- Grepperud, S., "A general equilibrium assessment of rebound effects", Energy Economics, 26, pp.261~282 (2004)
- Halvorsen, R., "The Interpretation of Dummy Variables in Semilogarithmic Equations", The American Economic Review, 70(3), pp.474~475 (1980)
- Howells, M., "Incorporating macroeconomic feedback into an energy systems model using an IO approach : Evaluating the rebound effect in the Korean electricity system", Energy Policy, 38, pp.2700~2728 (2010)
- Hymel, K., "Induced demand and rebound effects in road transport", Transportation Research Part B, 44, pp.1220~1241 (2010)
- Jin, Sang-Hyeon, "The effectiveness of energy efficiency improvement in a developing country : Rebound effect of residential electricity use in South Korea", Energy Policy, 35, pp.5622~5629 (2007)
- Khazzoom, D. J., "Economic Implications of mandated efficiency in standards for household appliances", Energy Journal, 1, pp.21~39 (1980)
- Khazzoom, D. J., "Energy saving resulting from the adoption of more efficient appliances", Energy Journal, 8, pp.85~89 (1987)
- Lin, B., "Reform of refined oil product pricing mechanism and energy rebound effect for passenger transportation in China", Energy Policy, 57, pp.329~337 (2013)
- The rebound effect for passenger vehicles, "Linn, J.", Resource for the Future, ~, pp.RFF DP 13-19 (2013)
- Matos, F., "The rebound effect on road freight transport: empirical evidence from Portugal", Energy Policy, 39, pp.2833~2842 (2011)
- Puller, S. L., "Household adjustment to gasoline price change: an analysis using 9 years of US survey data", Energy Economics, 21, pp.37~52 (1999)
- Schimek, P., "Gasoline and travel demand models using time series and cross-section data from the United States", Transportation Research Record, 1558, pp.83~89 (1996)
- Small, K., "Fuel efficiency and motor vehicle travel: the declining rebound effect", Energy Journal, 28, pp.25~51 (2007)
- Su, Q., "Induced motor vehicle travel from improved fuel efficiency and road expansion", Energy Policy, 39, pp.7257~7264 (2011)
- Su, Q., "A quantile regression analysis of the rebound effect: evidence from the 2009 national household transportation survey in the United States", Energy Policy, 45, pp.368~377 (2012)
- Wang, H., "Direct rebound effect for passenger transport: empirical evidence from Hong Kong", Applied Energy, 92, pp.162~167 (2012)
- Wang, H., "An empirical study of direct rebound effect for passenger transport in urban China", Energy Economics, 34, pp.452~460 (2012)