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Xun Zhou

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kuosmanen, Timo & Zhou, Xun & Eskelinen, Juha & Malo, Pekka, 2021. "Design Flaw of the Synthetic Control Method," MPRA Paper 106328, University Library of Munich, Germany.

    Cited by:

    1. Pekka Malo & Juha Eskelinen & Xun Zhou & Timo Kuosmanen, 2024. "Computing Synthetic Controls Using Bilevel Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1113-1136, August.
    2. Dmitry Arkhangelsky & Guido Imbens, 2023. "Causal Models for Longitudinal and Panel Data: A Survey," Papers 2311.15458, arXiv.org, revised Jun 2024.

  2. Malo, Pekka & Eskelinen, Juha & Zhou, Xun & Kuosmanen, Timo, 2020. "Computing Synthetic Controls Using Bilevel Optimization," MPRA Paper 104085, University Library of Munich, Germany.

    Cited by:

    1. Lucke, Bernd, 2022. "Growth Effects of European Monetary Union: A Synthetic Control Approach," MPRA Paper 120662, University Library of Munich, Germany, revised 27 Mar 2024.
    2. Jaume Vives-i-Bastida, 2022. "Predictor Selection for Synthetic Controls," Papers 2203.11576, arXiv.org, revised Dec 2022.
    3. Coelho dos Santos, Marcelo Bittencourt & Klotzle, Marcelo Cabus & Baptista Palazzi, Rafael, 2024. "The effect of oil discovery in Brazil: A synthetic control approach," Resources Policy, Elsevier, vol. 92(C).
    4. Lucke, Bernd & Rehfeldt, Erik, 2022. "How does expropriation affect FDI? A synthetic control analysis of oil and gas sector nationalizations in South America," MPRA Paper 115374, University Library of Munich, Germany.
    5. Kuosmanen, Timo & Zhou, Xun & Eskelinen, Juha & Malo, Pekka, 2021. "Design Flaw of the Synthetic Control Method," MPRA Paper 106328, University Library of Munich, Germany.
    6. Lucke, Bernd, 2022. "Growth Effects of European Monetary Union: A Synthetic Control Approach," MPRA Paper 115373, University Library of Munich, Germany.

Articles

  1. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).

    Cited by:

    1. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    2. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.

  2. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.

    Cited by:

    1. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.
    2. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).
    3. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.

  3. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.

    Cited by:

    1. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Mototsugu Fukushige & Yingxin Shi, 2022. "Quantile regression approach for measuring production inefficiency with empirical application to the primary production sector for the Xinjiang Production and Construction Corps in China," Asia-Pacific Journal of Regional Science, Springer, vol. 6(2), pages 777-805, June.
    3. K. Hervé Dakpo & Yann Desjeux & Laure Latruffe, 2023. "Cost of abating excess nitrogen on wheat plots in France: An assessment with multi‐technology modelling," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 800-815, September.
    4. Hu, Shuo & Wang, Ailun & Lin, Boqiang, 2024. "Marginal abatement cost of CO2: A convex quantile non-radial directional distance function regression method considering noise and inefficiency," Energy, Elsevier, vol. 297(C).
    5. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.
    6. Rødseth, Kenneth Løvold, 2023. "Shadow pricing of electricity generation using stochastic and deterministic materials balance models," Applied Energy, Elsevier, vol. 341(C).
    7. Zhiqiang Liao & Sheng Dai & Eunji Lim & Timo Kuosmanen, 2024. "Overfitting Reduction in Convex Regression," Papers 2404.09528, arXiv.org, revised Oct 2024.
    8. Sheng Dai & Timo Kuosmanen & Zhiqiang Liao, 2024. "Economic growth of cities: Does resource allocation matter?," Papers 2410.04918, arXiv.org.
    9. Wang, Hengkang & Shen, Jie & Gao, Ji & Wang, Wei & Zhu, Lei & Gu, Yongzheng & Wang, Tiankun, 2024. "Cost estimation of Non-CO2 greenhouse gas emissions reduction- A bottom-up analysis of coal-bed methane extraction and utilization in Shanxi, China," Energy, Elsevier, vol. 309(C).
    10. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Non-crossing convex quantile regression," Economics Letters, Elsevier, vol. 233(C).
    11. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.
    12. Sun, Yuhuan & Li, Hui & Zhu, Bingcheng, 2024. "Factor market distortion, total factor energy efficiency and energy shadow price: A case of Chinese manufacturing industry," Energy, Elsevier, vol. 307(C).
    13. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    14. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    15. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    16. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
    17. Tang, Wenzhi & Du, Shaofu & Hu, Li & Wang, Bill & Zhu, Yangguang, 2022. "The effects of leadership in Clean Development Mechanism low-carbon operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    18. Liao, Zhiqiang & Dai, Sheng & Kuosmanen, Timo, 2024. "Convex support vector regression," European Journal of Operational Research, Elsevier, vol. 313(3), pages 858-870.
    19. Rødseth, Kenneth Løvold, 2023. "Noise pollution of container handling: External and abatement costs and environmental efficiency," Transport Policy, Elsevier, vol. 134(C), pages 82-93.
    20. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2023. "Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period," Energy Economics, Elsevier, vol. 118(C).
    21. Rasmus Bøgh Holmen & Timo Kuosmanen & Jaan Masso & Per Botolf Maurseth & Kenneth Løvold Rødseth, 2024. "Optimal Intertemporal Broadband Investments To Promote Regional Economic Development," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 149, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    22. Jradi, Samah & Parmeter, Christopher F. & Ruggiero, John, 2021. "Quantile estimation of stochastic frontiers with the normal-exponential specification," European Journal of Operational Research, Elsevier, vol. 295(2), pages 475-483.
    23. Timo Kuosmanen & Yong Tan & Sheng Dai, 2023. "Performance analysis of English hospitals during the first and second waves of the coronavirus pandemic," Health Care Management Science, Springer, vol. 26(3), pages 447-460, September.
    24. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).

  4. Zhou, Xun & Kuosmanen, Timo, 2020. "What drives decarbonization of new passenger cars?," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1043-1057.

    Cited by:

    1. Muhammad Tayyab Sohail & Sana Ullah & Muhammad Tariq Majeed, 2024. "Transportation taxes and CO2 emissions nexus in BCIST economies: Implication for environmental sustainability," Energy & Environment, , vol. 35(5), pages 2829-2845, August.
    2. Yuan, Qianqian & Baležentis, Tomas & Shen, Zhiyang & Streimikiene, Dalia, 2021. "Economic and environmental performance of the belt and road countries under convex and nonconvex production technologies," Journal of Asian Economics, Elsevier, vol. 75(C).
    3. Mónica Meireles & Margarita Robaina & Daniel Magueta, 2021. "The Effectiveness of Environmental Taxes in Reducing CO 2 Emissions in Passenger Vehicles: The Case of Mediterranean Countries," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
    4. Wang, Hui & Li, Rupeng & Zhang, Ning & Zhou, Peng & Wang, Qiang, 2020. "Assessing the role of technology in global manufacturing energy intensity change: A production-theoretical decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    5. Wolff, Michael & Becker, Tristan & Walther, Grit, 2023. "Long-term design and analysis of renewable fuel supply chains – An integrated approach considering seasonal resource availability," European Journal of Operational Research, Elsevier, vol. 304(2), pages 745-762.
    6. Xu, Jin-Hua & Guo, Jian-Feng & Peng, Binbin & Nie, Hongguang & Kemp, Rene, 2020. "Energy growth sources and future energy-saving potentials in passenger transportation sector in China," Energy, Elsevier, vol. 206(C).
    7. Wu, F. & Zhou, P. & Zhou, D.Q., 2020. "Modeling carbon emission performance under a new joint production technology with energy input," Energy Economics, Elsevier, vol. 92(C).

  5. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).

    Cited by:

    1. Yunfei An & Xunpeng Shi & Qunwei Wang & Jian Yu & Dequn Zhou & Xiaoyong Zhou, 2023. "China's manufacturing firms' willingness to pay for carbon abatement: A cost perspective," Business Strategy and the Environment, Wiley Blackwell, vol. 32(8), pages 5477-5486, December.
    2. Bei Gao & Zuoren Sun, 2023. "Marginal CO 2 and SO 2 Abatement Costs and Determinants of Coal-Fired Power Plants in China: Considering a Two-Stage Production System with Different Emission Reduction Approaches," Energies, MDPI, vol. 16(8), pages 1-26, April.
    3. Xian, Yujiao & Hu, Zhihui & Wang, Ke, 2023. "The least-cost abatement measure of carbon emissions for China's glass manufacturing industry based on the marginal abatement costs," Energy, Elsevier, vol. 284(C).
    4. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.
    5. Jingyan Fu & Artie W. Ng, 2021. "Scaling up Renewable Energy Assets: Issuing Green Bond via Structured Public-Private Collaboration for Managing Risk in an Emerging Economy," Energies, MDPI, vol. 14(11), pages 1-16, May.
    6. Kuosmanen, Natalia & Kuosmanen, Timo & Maczulskij, Terhi & Zhou, Xun, 2024. "Least-cost Decarbonization Pathways for Electricity Generation in Finland: A Convex Quantile Regression Approach," ETLA Working Papers 114, The Research Institute of the Finnish Economy.
    7. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    8. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    9. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    10. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    11. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
    12. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2023. "Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period," Energy Economics, Elsevier, vol. 118(C).
    13. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).

  6. Kuosmanen, Timo & Zhou, Xun & Dai, Sheng, 2020. "How much climate policy has cost for OECD countries?," World Development, Elsevier, vol. 125(C).

    Cited by:

    1. Sheng-Wei Lin & Wen-Min Lu, 2024. "A chance-constrained network DEA approach based on enhanced Russell-based directional distance measure to evaluate public sector performance: a case study of OECD countries," Annals of Operations Research, Springer, vol. 342(3), pages 1837-1864, November.
    2. Bei Gao & Zuoren Sun, 2023. "Marginal CO 2 and SO 2 Abatement Costs and Determinants of Coal-Fired Power Plants in China: Considering a Two-Stage Production System with Different Emission Reduction Approaches," Energies, MDPI, vol. 16(8), pages 1-26, April.
    3. Xian, Yujiao & Hu, Zhihui & Wang, Ke, 2023. "The least-cost abatement measure of carbon emissions for China's glass manufacturing industry based on the marginal abatement costs," Energy, Elsevier, vol. 284(C).
    4. Sheng Dai & Natalia Kuosmanen & Timo Kuosmanen & Juuso Liesio, 2023. "Optimal resource allocation: Convex quantile regression approach," Papers 2311.06590, arXiv.org.
    5. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
    6. Chu, Long & Grafton, R. Quentin & Nguyen, Hai, 2022. "A global analysis of the break-even prices to reduce atmospheric carbon dioxide via forest plantation and avoided deforestation," Forest Policy and Economics, Elsevier, vol. 135(C).
    7. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2021. "Lurking in the Shadows: The Impact of Emissions Target Setting on Carbon Pricing and Environmental Efficiency," QBS Working Paper Series 2021/05, Queen's University Belfast, Queen's Business School.
    8. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    9. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.
    10. Núñez, Angie Paola Bernal & Gutiérrez-Montes, Isabel & Hernández-Núñez, Héctor Eduardo & Suárez, David Ricardo Gutiérrez & García, Gustavo Adolfo Gutiérrez & Suárez, Juan Carlos & Casanoves, Fernando , 2023. "Diverse farmer livelihoods increase resilience to climate variability in southern Colombia," Land Use Policy, Elsevier, vol. 131(C).
    11. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    12. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    13. Liao, Zhiqiang & Dai, Sheng & Kuosmanen, Timo, 2024. "Convex support vector regression," European Journal of Operational Research, Elsevier, vol. 313(3), pages 858-870.
    14. Quinn, Barry & Gallagher, Ronan & Kuosmanen, Timo, 2023. "Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period," Energy Economics, Elsevier, vol. 118(C).
    15. Wen, Xiaojie & Yao, Shunbo & Sauer, Johannes, 2022. "Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach," Ecological Economics, Elsevier, vol. 201(C).

  7. Zhou, D.Q. & Wu, F. & Zhou, X. & Zhou, P., 2016. "Output-specific energy efficiency assessment: A data envelopment analysis approach," Applied Energy, Elsevier, vol. 177(C), pages 117-126.

    Cited by:

    1. Fei, Rilong & Lin, Boqiang, 2017. "The integrated efficiency of inputs–outputs and energy – CO2 emissions performance of China's agricultural sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 668-676.
    2. Toshiyuki Sueyoshi & Mika Goto, 2020. "Performance Assessment of Japanese Electric Power Industry: DEA Measurement with Future Impreciseness," Energies, MDPI, vol. 13(2), pages 1-24, January.
    3. Gong, Shixin & Shao, Cheng & Zhu, Li, 2019. "Multi-level and multi-granularity energy efficiency diagnosis scheme for ethylene production process," Energy, Elsevier, vol. 170(C), pages 1151-1169.
    4. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Allocation of emission permits for China’s power plants: A systemic Pareto optimal method," Applied Energy, Elsevier, vol. 204(C), pages 607-619.
    5. Majid Azadi & Balal Karimi & William Ho & Reza Farzipoor Saen, 2022. "Assessing green performance of power plants by multiple hybrid returns to scale technologies," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1177-1211, December.
    6. Nadimi, Reza & Tokimatsu, Koji, 2019. "Potential energy saving via overall efficiency relying on quality of life," Applied Energy, Elsevier, vol. 233, pages 283-299.
    7. Zuoren Sun & Chao An & Huachen Sun, 2018. "Regional Differences in Energy and Environmental Performance: An Empirical Study of 283 Cities in China," Sustainability, MDPI, vol. 10(7), pages 1-28, July.
    8. Jiang, Lei & Zhou, Haifeng & He, Shixiong, 2021. "Does energy efficiency increase at the expense of output performance: Evidence from manufacturing firms in Jiangsu province, China," Energy, Elsevier, vol. 220(C).
    9. Patrick Gasser & Marco Cinelli & Anna Labijak & Matteo Spada & Peter Burgherr & Miłosz Kadziński & Božidar Stojadinović, 2020. "Quantifying Electricity Supply Resilience of Countries with Robust Efficiency Analysis," Energies, MDPI, vol. 13(7), pages 1-35, March.
    10. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Miao, Zhuang, 2018. "Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change," Energy Economics, Elsevier, vol. 72(C), pages 166-176.
    11. Sorana Vătavu & Oana-Ramona Lobonț & Iulia Para & Andrei Pelin, 2018. "Addressing oil price changes through business profitability in oil and gas industry in the United Kingdom," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-22, June.
    12. Benedetti, Miriam & Bonfa', Francesca & Bertini, Ilaria & Introna, Vito & Ubertini, Stefano, 2018. "Explorative study on Compressed Air Systems’ energy efficiency in production and use: First steps towards the creation of a benchmarking system for large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 227(C), pages 436-448.
    13. Lizhan Cao & Zhongying Qi & Junxia Ren, 2017. "China’s Industrial Total-Factor Energy Productivity Growth at Sub-Industry Level: A Two-Step Stochastic Metafrontier Malmquist Index Approach," Sustainability, MDPI, vol. 9(8), pages 1-22, August.
    14. Wen, Quan & Hong, Jingke & Liu, Guiwen & Xu, Pengpeng & Tang, Miaohan & Li, Zhongfu, 2020. "Regional efficiency disparities in China’s construction sector: A combination of multiregional input–output and data envelopment analyses," Applied Energy, Elsevier, vol. 257(C).

  8. Zhou, X. & Fan, L.W. & Zhou, P., 2015. "Marginal CO2 abatement costs: Findings from alternative shadow price estimates for Shanghai industrial sectors," Energy Policy, Elsevier, vol. 77(C), pages 109-117.

    Cited by:

    1. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    2. Jie Zhang & Lu Zhang, 2016. "Impacts on CO 2 Emission Allowance Prices in China: A Quantile Regression Analysis of the Shanghai Emission Trading Scheme," Sustainability, MDPI, vol. 8(11), pages 1-12, November.
    3. He, Weijun & Yang, Yi & Wang, Zhaohua & Zhu, Joe, 2018. "Estimation and allocation of cost savings from collaborative CO2 abatement in China," Energy Economics, Elsevier, vol. 72(C), pages 62-74.
    4. Marc Baudry & Anouk Faure, 2021. "Technological Progress and Carbon Price Formation: an Analysis of EU-ETS Plants," Working Papers 2021.10, FAERE - French Association of Environmental and Resource Economists.
    5. Hu, Guangxiao & Ma, Xiaoming & Ji, Junping, 2019. "Scenarios and policies for sustainable urban energy development based on LEAP model – A case study of a postindustrial city: Shenzhen China," Applied Energy, Elsevier, vol. 238(C), pages 876-886.
    6. A. Bellver-Domingo & F. Hernández-Sancho, 2018. "Environmental Benefit of Improving Wastewater Quality: A Shadow Prices Approach for Sensitive Areas," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 1-15, April.
    7. Wei, Yigang & Liang, Xin & Xu, Liang & Kou, Gang & Chevallier, Julien, 2023. "Trading, storage, or penalty? Uncovering firms' decision-making behavior in the Shanghai emissions trading scheme: Insights from agent-based modeling," Energy Economics, Elsevier, vol. 117(C).
    8. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
    9. Zhenkai Yang & Mei-Chih Wang & Tsangyao Chang & Wing-Keung Wong & Fangjhy Li, 2022. "Which Factors Determine CO 2 Emissions in China? Trade Openness, Financial Development, Coal Consumption, Economic Growth or Urbanization: Quantile Granger Causality Test," Energies, MDPI, vol. 15(7), pages 1-18, March.
    10. Lee, Chia-Yen & Wang, Ke, 2019. "Nash marginal abatement cost estimation of air pollutant emissions using the stochastic semi-nonparametric frontier," European Journal of Operational Research, Elsevier, vol. 273(1), pages 390-400.
    11. Ling-Yun He & Jia-Jia Ou, 2017. "Pollution Emissions, Environmental Policy, and Marginal Abatement Costs," IJERPH, MDPI, vol. 14(12), pages 1-16, December.
    12. Du, Limin & Hanley, Aoife & Wei, Chu, 2015. "Estimating the marginal abatement cost curve of CO2 emissions in China: Provincial panel data analysis," Kiel Working Papers 1985, Kiel Institute for the World Economy (IfW Kiel).
    13. Zeng, Shihong & Jiang, Xue & Su, Bin & Nan, Xin, 2018. "China's SO2 shadow prices and environmental technical efficiency at the province level," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 86-102.
    14. Wenyin Cheng & Zhusong Yang & Xia Pan & Tomas Baležentis & Xueli Chen, 2020. "Evolution of Carbon Shadow Prices in China’s Industrial Sector during 2003–2017: A By-Production Approach," Sustainability, MDPI, vol. 12(2), pages 1-14, January.
    15. Kejia Yang & Yalin Lei, 2017. "The carbon dioxide marginal abatement cost calculation of Chinese provinces based on stochastic frontier analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(1), pages 505-521, January.
    16. Liangpeng Wu & Qingyuan Zhu, 2021. "Impacts of the carbon emission trading system on China’s carbon emission peak: a new data-driven approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2487-2515, July.
    17. Ji, D.J. & Zhou, P., 2020. "Marginal abatement cost, air pollution and economic growth: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 86(C).
    18. Ye Duan & Nan Li & Hailin Mu & Shusen Gui, 2017. "Research on CO 2 Emission Reduction Mechanism of China’s Iron and Steel Industry under Various Emission Reduction Policies," Energies, MDPI, vol. 10(12), pages 1-24, December.
    19. Bowen Xiao & Dongxiao Niu & Han Wu & Haichao Wang, 2017. "Marginal Abatement Cost of CO 2 in China Based on Directional Distance Function: An Industry Perspective," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    20. Lee, Chia-Yen & Zhou, Peng, 2015. "Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990–2010," Energy Economics, Elsevier, vol. 51(C), pages 493-502.
    21. Dong-Xiao Yang & Lei Yang & Xiao-Ling Chen & Chan Wang & Pu-Yan Nie, 2023. "Research on credit pricing mechanism in dual-credit policy: is the government in charge or is the market in charge?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1561-1581, February.
    22. Dong-Hyun Oh & JongWuk Ahn & Sinwoo Lee & Hyundo Choi, 2021. "Measuring technical inefficiency and CO2 shadow price of Korean fossil-fuel generation companies using deterministic and stochastic approaches," Energy & Environment, , vol. 32(3), pages 403-423, May.
    23. Wang, Jian & Lv, Kangjuan & Bian, Yiwen & Cheng, Yu, 2017. "Energy efficiency and marginal carbon dioxide emission abatement cost in urban China," Energy Policy, Elsevier, vol. 105(C), pages 246-255.
    24. Silva, Felipe & Fulginiti, Lilyan E. & Perrin, Richard K., 2016. "Did technical change in agricultural production decrease the emission of pollutants on the Amazon Forest during 1990-2009?," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230092, Southern Agricultural Economics Association.
    25. Surender Kumar & Rakesh Kumar Jain, 2018. "Shadow Price of CO 2 Emissions in Indian Thermal Power Sector," Working Papers id:12791, eSocialSciences.
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    42. Arjan Trinks & Erik Hille, 2023. "Carbon costs and industrial firm performance: Evidence from international microdata," CPB Discussion Paper 445, CPB Netherlands Bureau for Economic Policy Analysis.
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    48. Silva, Felipe & Fulginiti, Lilyan E. & Perrin, Richard K., 2016. "Did technical change in agricultural production decrease the emission of pollutants on the Amazon Forest during 1990-2009?," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230092, Southern Agricultural Economics Association.
    49. Surender Kumar & Rakesh Kumar Jain, 2018. "Shadow Price of CO 2 Emissions in Indian Thermal Power Sector," Working Papers id:12791, eSocialSciences.
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