Abstract
This paper explores the direct impact of new technology on the energy intensity in China. The autoregressive distributed lag (ARDL) bounds test approach to cointegration is utilised over the extended period of 1985–2013. The variables found cointegrated and confirm the long-run association among all the underlying vectors. Furthermore, the results of long- and short-run analysis reveal that new technology spurs energy intensity in China. A 1% increase in technological innovation boosts energy intensity by 0.4% and 0.03% in the long and short run, respectively. The findings suggest that the establishment of smart grids and solar energy parks followed by the reforms in energy sector is yet to achieve plausible efficiency in China. The existing investment and innovation policy reforms are insufficient to assist the energy sector to cope up with the country’s exceptional economic growth trend. Unlike other studies, this paper accommodates structural break in the series. During sensitivity analysis, the model is found stable. Hence, the findings possess important policy implications for China and open up new discussion in the field.
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References
Chen TJ (2016) The development of China’s solar photovoltaic industry: why industrial policy failed. Camb J Econ 40:755–774
De Vita G, Abbott A (2002) Are saving and investment cointegrated? An ARDL bounds testing approach. Econ Lett 77(2):293–299
Dogan E, Inglesi-Lotz R (2017) Analyzing the effects of real income and biomass energy consumption on carbon dioxide (CO2) emissions: empirical evidence from the panel of biomass-consuming countries. Energy 138:721–727
Dogan E, Turkekul B (2016) CO2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the EKC hypothesis for the USA. Environ Sci Pollut Res 23(2):1203–1213
EIA (2015) Energy Information Administration - EIA - Official Energy Statistics from the U.S. Government
Fisher-Vanden K, Jefferson GH, Jingkui M, Jianyi X (2006) Technology development and energy productivity in China. Energy Econ 28(5):690–705
Greening LA, Greene DL, Difiglio C (2000) Energy efficiency and consumption—the rebound effect—a survey. Energy Policy 28(6–7):389–401
Herrerias MJ, Cuadros A, Luo D (2016) Foreign versus indigenous innovation and energy intensity: further research across Chinese regions. Appl Energy 162:1374–1384
Herring H, Roy R (2007) Technological innovation, energy efficient design and the rebound effect. Technovation 27(4):194–203
Hochstetler K, Kostka G (2015) Wind and solar power in Brazil and China: interests, state–business relations, and policy outcomes. Glob Environ Pol 15(3):74–94
Inglesi-Lotz R, Dogan E (2018) The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa’s big 10 electricity generators. Renew Energy 123:36–43
Jaffe AB, Newell RG, Stavins RN (2003) Technological change and the environment. Handb Environ Econ 1:461–516
Karfakis C, Moschos D (1989) Testing for long run purchasing power parity: a time series analysis for the greek drachma. Econ Lett 30(3):245–248
Karplus VJ (2007) Innovation in China’s energy sector. Center for Environmental Science and Policy, Stanford
Kontonikas A (2010) A new test of the inflation–real marginal cost relationship: ARDL bounds approach. Econ Lett 108(2):122–125
Liu Y, Zhou Y, Wu W (2015) Assessing the impact of population, income and technology on energy consumption and industrial pollutant emissions in China. Appl Energy 155(1):904–917
Meireles M, Soares I, Afonso O (2012) Dirty versus ecological technology in an endogenous growth model. Appl Econ Lett 19(8):729–733
Moutinho V, Madaleno M, Inglesi-Lotz R, Dogan E (2018) Factors affecting CO2 emissions in top countries on renewable energies: a LMDI decomposition application. Renew Sust Energ Rev 90:605–622
Ozturk I, Acaravci A (2013) The long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in Turkey. Energy Econ 36:262–267
Pesaran MH, Smith RJ, Shin Y (2001) Bounds Testing Approaches to the Analysis of Level Relationships. J Appl Econ 16:289–326
Popp DC (2001) The effect of new technology on energy consumption. Resour Energy Econ 23(3):215–239
WDI (2015) World Development Indicators 2015. Washington, DC: World Bank
WIPO 2014 Available at: http://www.wipo.int/export/sites/www/ipstats/en/docs/infographics_pct_2014.pdf
Wu N (2011) China energy issues: energy intensity, coal liquefaction, and carbon pricing (Doctoral dissertation, Massachusetts Institute of Technology)
Yao X, Zhou H, Zhang A, Li A (2015) Regional energy efficiency, carbone mission performance and technology gaps in China: a meta frontier non-radial directional distance function analysis. Energy Policy 84:142–154
Zachariadis T (2007) Exploring the relationship between energy use and economic growth with bivariate models: new evidence from G-7 countries. Energy Econ 29(6):1233–1253
Zhang YJ, Peng HR, Liu Z, Tan W (2015a) Direct energy rebound effect for road passenger transport in China: a dynamic panel quantile regression approach. Energy Policy 87:303–313
Zhang YJ, Wang AD, Tan W (2015b) The impact of China’s carbon allowance allocation rules on the product prices and emission reduction behaviors of ETS-covered enterprises. Energy Policy 86:176–185
Zivot E, Andrews D(1992) Further Evidence On The Great Grash, The Oil-Price Shock, And The Unit-Root Hypothesis. J Bus Econ Stat 10(3):251–270
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Ahmed, K., Ozturk, I. What new technology means for the energy demand in China? A sustainable development perspective. Environ Sci Pollut Res 25, 29766–29771 (2018). https://doi.org/10.1007/s11356-018-2957-3
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DOI: https://doi.org/10.1007/s11356-018-2957-3