To reduce energy consumption and to maintain rapid economic growth: Analysis of the condition in China based on expended IPAT model
By M. Song, Shuhong Wang, Huayi Yu, Jie Wu. 2011
118 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/258983d6e1153c579270b68557ef56f51bc246cc
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Citations in the corpus
- The optimal CO2 emissions reduction path in Jiangsu province: An expanded IPAT approach (2013, methodology): “According to an analysis of China’s energy consumption using the expanded IPAT model, it has been concluded that developing renewable energy and enhancing energy efficiency are crucial to economic growth and reduction of energy consumption [21].”
- On the nexus of financial development, economic growth, and energy consumption in China: New perspective from a GMM panel VAR approach (2018, background): “Second, “growth hypothesis” is supported when there exists only a unidirectional causality running from energy consumption to economic growth (e.g., Lee and Chang, 2008; Al-mulali and Sab, 2012; Ahmad et al., 2017; Tsani, 2010; Song et al., 2011; Lin and Wesseh Jr, 2014; Aqeel and Butt, 2001).”
- Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis (2012, background): “Since for China simultaneously maintaining rapid economic growth, reducing energy consumption and controlling CO2 emissions is compulsory for promoting its low-carbon development (Song et al., 2011), Eq.”
- Comparison of Forecasting Energy Consumption in Shandong, China Using the ARIMA Model, GM Model, and ARIMA-GM Model (2017, methodology): “The acronym stems from the univariate Box–Jenkins autoregressive integrated moving average (ARIMA) [7] analysis, which has been widely used for modeling and forecasting in many fields, such as medical, environmental, financial, and engineering applications [17,33–36].”