Using a temporal input-output approach to analyze the ripple effect of China’s energy consumption
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DOI: 10.1016/j.energy.2020.118641
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- Benkraiem, Ramzi & Lahiani, Amine & Miloudi, Anthony & Shahbaz, Muhammad, 2019.
"The asymmetric role of shadow economy in the energy-growth nexus in Bolivia,"
Energy Policy, Elsevier, vol. 125(C), pages 405-417.
- Ramzi Benkraiem & Amine Lahiani & Anthony Miloudi & Shahbaz Muhammad, 2019. "The asymmetric role of shadow economy in the energy-growth nexus in Bolivia," Post-Print hal-01935226, HAL.
- Pao, H.T., 2009. "Forecasting energy consumption in Taiwan using hybrid nonlinear models," Energy, Elsevier, vol. 34(10), pages 1438-1446.
- Kumar, Ujjwal & Jain, V.K., 2010. "Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India," Energy, Elsevier, vol. 35(4), pages 1709-1716.
- Ekonomou, L., 2010. "Greek long-term energy consumption prediction using artificial neural networks," Energy, Elsevier, vol. 35(2), pages 512-517.
- Rajbhandari, Ashish & Zhang, Fan, 2018.
"Does energy efficiency promote economic growth? Evidence from a multicountry and multisectoral panel dataset,"
Energy Economics, Elsevier, vol. 69(C), pages 128-139.
- Rajbhandari,Ashish & Zhang,Fan, 2017. "Does energy efficiency promote economic growth? : evidence from a multi-country and multi-sector panel data set," Policy Research Working Paper Series 8077, The World Bank.
- Owen, Anne & Scott, Kate & Barrett, John, 2018. "Identifying critical supply chains and final products: An input-output approach to exploring the energy-water-food nexus," Applied Energy, Elsevier, vol. 210(C), pages 632-642.
- Long, Yin & Yoshida, Yoshikuni, 2018. "Quantifying city-scale emission responsibility based on input-output analysis – Insight from Tokyo, Japan," Applied Energy, Elsevier, vol. 218(C), pages 349-360.
- Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
- He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
- Zhong, Sheng, 2018. "Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD," Energy Policy, Elsevier, vol. 122(C), pages 655-667.
- Chai, Jian & Du, Mengfan & Liang, Ting & Sun, Xiaojie Christine & Yu, Ji & Zhang, Zhe George, 2019. "Coal consumption in China: How to bend down the curve?," Energy Economics, Elsevier, vol. 80(C), pages 38-47.
- Xiao, Jin & Li, Yuxi & Xie, Ling & Liu, Dunhu & Huang, Jing, 2018. "A hybrid model based on selective ensemble for energy consumption forecasting in China," Energy, Elsevier, vol. 159(C), pages 534-546.
- Xu, Ning & Ding, Song & Gong, Yande & Bai, Ju, 2019. "Forecasting Chinese greenhouse gas emissions from energy consumption using a novel grey rolling model," Energy, Elsevier, vol. 175(C), pages 218-227.
- Utgikar, V.P. & Scott, J.P., 2006. "Energy forecasting: Predictions, reality and analysis of causes of error," Energy Policy, Elsevier, vol. 34(17), pages 3087-3092, November.
- Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2019. "Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model," Renewable Energy, Elsevier, vol. 140(C), pages 70-87.
- Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng, 2016. "Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model," Energy, Elsevier, vol. 100(C), pages 384-390.
- de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
- Liu, Hong & Wang, Chang & Tian, Meiyu & Wen, Fenghua, 2019. "Analysis of regional difference decomposition of changes in energy consumption in China during 1995–2015," Energy, Elsevier, vol. 171(C), pages 1139-1149.
- Chien, Taichen & Hu, Jin-Li, 2007. "Renewable energy and macroeconomic efficiency of OECD and non-OECD economies," Energy Policy, Elsevier, vol. 35(7), pages 3606-3615, July.
- Fatemeh Bazzazan & Peter Batey, 2003. "The Development and Empirical Testing of Extended Input-Output Price Models," Economic Systems Research, Taylor & Francis Journals, vol. 15(1), pages 69-86, March.
- Acheampong, Alex O., 2018. "Economic growth, CO2 emissions and energy consumption: What causes what and where?," Energy Economics, Elsevier, vol. 74(C), pages 677-692.
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- Jia, Zhijie & Lin, Boqiang, 2022. "Is the rebound effect useless? A case study on the technological progress of the power industry," Energy, Elsevier, vol. 248(C).
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Keywords
China’s economy; Energy consumption forecasting; Temporal input-output approach; Ripple effect; Time curve;All these keywords.
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