[1] Ju KY, SuB, Zhou DQ et al. Does energy-price regulation benefit China’s economy and environment? Evidence from energy-price distortions[J]. Energy Policy, 105, 108-119(2017).

[2] 冷艳丽, 杜思正. 能源价格扭曲与雾霾污染: 中国的经验证据[J]. 产业经济研究, 2016,80(1):71-79. [Leng YL, Du SZ. Energy price distortion and haze pollution: The evidence from China[J]. Industrial Economics Research, 2016,80(1):71-79.] [Leng Y L, Du S Z. Energy price distortion and haze pollution: The evidence from China[J]. Industrial Economics Research, 2016, 80(1): 71-79.]

[3] Wang XL, Bai MQ, Xie CP. Investigating CO₂ mitigation potentials and the impact of oil price distortion in China’s transport sector[J]. Energy Policy, 130, 320-327(2019).

[4] Lai PH, Du MZ, WangB et al. Assessment and decomposition of total factor energy efficiency: An evidence based on energy shadow price in China[J]. Sustainability(2016). https://www.ncbi.nlm.nih.gov/pubmed/28008371

[5] Zhang XP, Xu QN, ZhangF et al. Exploring shadow prices of carbon emissions at provincial levels in China[J]. Ecological Indicators, 46, 407-414(2014).

[6] TamakiT, Shin KJ, NakamuraH et al. Shadow prices and production inefficiency of mineral resources[J]. Economic Analysis and Policy, 57, 111-121(2018).

[7] 陈欣, 刘延. 中国二氧化碳影子价格估算及与交易价格差异分析: 基于二次型方向性距离产出函数[J]. 生态经济, 2018,34(6):14-20. [ChenX, LiuY. Estimation of China’s carbon dioxide shadow price and analysis of the difference in transaction price: Output function based on quadratic directional distance[J]. Ecological Economy, 2018,34(6):14-20.] [Chen X, Liu Y. Estimation of China’s carbon dioxide shadow price and analysis of the difference in transaction price: Output function based on quadratic directional distance[J]. Ecological Economy, 2018, 34(6): 14-20.]

[8] Zhao QZ, Yan QY, Zhang LJ et al. Dynamic and spatial character analysis of regional marginal abatement costs of CO₂ emissions from energy consumption: A provincial aspect[J]. Polish Journal of Environmental Studies, 28, 2501-2511(2019).

[9] WangK, Che LN, Ma CB et al. The shadow price of CO₂ emissions in China’s iron and steel industry[J]. Science of the Total Environment, 598, 272-281(2017).

[10] Singbo AG, Lansink AO, EmvalomatisG. Estimating shadow prices and efficiency analysis of productive inputs and pesticide use of vegetable production[J]. European Journal of Operational Research, 245, 265-272(2015).

[11] ChoiY, ZhangN, ZhouP. Efficiency and abatement costs of energy-related CO₂ emissions in China: A slacks-based efficiency measure[J]. Applied Energy, 98, 198-208(2012).

[12] Yan QY, Wang YX, TomasB et al. Energy-related CO₂ emission in China’s provincial thermal electricity generation: Driving factors and possibilities for abatement[J]. Energy, 11, 1096-1118(2018).

[13] Sheng PF, YangJ, Shackman JD. Energy’s shadow price and energy efficiency in China: A non-parametric input distance function analysis[J]. Energies, 8, 1975-1989(2015).

[14] 吴凡, 刘雪娇, 谢文秀. 要素配置优化与中国区域能源影子价格[J]. 现代财经(天津财经大学学报), 2017,37(3):93-101. [WuF, Liu XJ, Xie WX. Factor configuration optimization and regional energy shadow price in China[J]. Modern Finance and Economics-Journal of Tianjin University of Finance and Economics, 2017,37(3):93-101.] [Wu F, Liu X J, Xie W X. Factor configuration optimization and regional energy shadow price in China[J]. Modern Finance and Economics-Journal of Tianjin University of Finance and Economics, 2017, 37(3): 93-101.]

[15] FukuyamaH, Weber WL. A directional slacks: Based measure of technical inefficiency[J]. Socio-Economic Planning Sciences, 43, 274-287(2009).

[16] ZhangN, Kong FB, Yu YN. Measuring ecological total-factor energy efficiency incorporating regional heterogeneities in China[J]. Ecological Indicators, 51, 165-172(2015).

[17] Yu YT, Huang JH, ZhangN. Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective[J]. Ecological Modelling, 402, 1-17(2019).

[18] Battese GE, Rao DS P, O’Donnell CJ. A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies[J]. Journal of Productivity Analysis, 21, 91-103(2004).

[19] 方琳, 吴凤平, 王新华, 等. 基于共同前沿SBM模型的农业用水效率测度及改善潜力[J]. 长江流域资源与环境, 2018,27(10):2293-2304. [FangL, Wu FP, Wang XH, et al. Analysis of agricultural water efficiency measurement and improvement potential based on meta frontier SBM model[J]. Resources and Environment in the Yangtze Basin, 2018,27(10):2293-2304.] [Fang L, Wu F P, Wang X H, et al. Analysis of agricultural water efficiency measurement and improvement potential based on meta frontier SBM model[J]. Resources and Environment in the Yangtze Basin, 2018, 27(10): 2293-2304.]

[20] Long XL, Luo YS, Sun HP et al. Fertilizer using intensity and environmental efficiency for China’s agriculture sector from 1997 to 2014[J]. Natural Hazards, 92, 1573-1591(2018).

[21] 国涓, 刘丰, 王维国. 中国区域环境绩效动态差异及影响因素: 考虑可变规模报酬和技术异质性的研究[J]. 资源科学, 2013,35(12):2444-2456. [GuoJ, LiuF, Wang WG. Dynamic differences and factors affecting regional environmental performance in China: Variable return to scale and technology heterogeneity[J]. Resources Science, 2013,35(12):2444-2456.] [Guo J, Liu F, Wang W G. Dynamic differences and factors affecting regional environmental performance in China: Variable return to scale and technology heterogeneity[J]. Resources Science, 2013, 35(12): 2444-2456.]

[22] Lin BQ, Tan RP. Ecological total-factor energy efficiency of China’s energy intensive industries[J]. Ecological Indicators, 70, 480-497(2016).

[23] Li JL, Lin BQ. Ecological total-factor energy efficiency of China’s heavy and light industries: Which performs better[J]. Renewable & Sustainable Energy Reviews, 72, 83-94(2017).

[24] 聂雷, 郭忠兴, 彭冲. 基于SBM-Undesirable和Meta-frontier模型的城市建设用地利用效率研究[J]. 资源科学, 2017,39(5):836-845.

[25] 陈诗一. 工业二氧化碳的影子价格: 参数化和非参数化方法[J]. 世界经济, 2010,33(8):93-111. [Chen SY. Shadow price of industrial carbon dioxide: Parametric and nonparametric approach[J]. The Journal of World Economy, 2010,33(8):93-111.] [Chen S Y. Shadow price of industrial carbon dioxide: Parametric and nonparametric approach[J]. The Journal of World Economy, 2010, 33(8): 93-111.]

[26] Chiu CR, Liou JL, Wu PI et al. Decomposition of the environmental inefficiency of the meta-frontier with undesirable output[J]. Energy Economics, 34, 1392-1399(2012).

[27] 张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估算: 1952-2000[J]. 经济研究, 2004, (10):35-44. [ZhangJ, Wu GY, Zhang JP. The estimation of China’s provincial capital stock: 1952-2000[J]. Economic Research Journal, 2004, (10):35-44.] [Zhang J, Wu G Y, Zhang J P. The estimation of China’s provincial capital stock: 1952-2000[J]. Economic Research Journal, 2004, (10): 35-44.]

[28] 中华人民共和国国家统计局. 中国统计年鉴[M]. 北京: 中国统计出版社, 2001-2018. [National Bureau of Statistics of the People’s Republic of China. China Statistical Yearbook[M]. Beijing: China Statistics Press, 2001-2018.] [National Bureau of Statistics of the People’s Republic of China. China Statistical Yearbook[M]. Beijing: China Statistics Press, 2001-2018.]

[29] 国家统计局能源统计司, 国家能源局综合司. 中国能源统计年鉴[M]. 北京: 中国统计出版社, 2001-2018. [Department of Energy Statistics, National Bureau of Statistics of the People’s Republic of China, Department of General Affairs National Energy Administration of the People’s Republic of China. China Energy Statistical Yearbook[M]. Beijing: China Statistics Press, 2001-2018.] [Department of Energy Statistics, National Bureau of Statistics of the People’s Republic of China, Department of General Affairs National Energy Administration of the People’s Republic of China. China Energy Statistical Yearbook[M]. Beijing: China Statistics Press, 2001-2018.]

[30] YaoX, Zhou HC, Zhang AZ et al. Regional energy efficiency, carbon emission performance and technology gaps in China: A meta-frontier non-radial directional distance function analysis[J]. Energy Policy, 84, 142-154(2015).