Evaluation of environmental energy efficiency and its influencing factors: a prefecture-level analysis of Japanese manufacturing industries

被引:0
作者
Shimizu M. [1 ]
Tiku O. [2 ]
机构
[1] Faculty of Global and Regional Studies, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami-gun, Okinawa
[2] Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji-shi, Tokyo
基金
日本学术振兴会;
关键词
Cleaner production; Data envelopment analysis; Environmental energy efficiency; Manufacturing industry; Pooled mean group;
D O I
10.1186/s40008-023-00297-9
中图分类号
学科分类号
摘要
This study evaluates the progress of efficient energy use and the control of carbon dioxide (CO2) emissions in Japan between 1990 and 2012. A new indicator of energy performance is presented called environmental energy efficiency (EEE). The EEE of manufacturing industries was measured by each prefecture in Japan. We estimated the influencing factors of EEE for each industry by applying the pooled mean group (PMG) method. Our findings are as follows: First, the Japanese manufacturing industry has not been in line with the EEE improvement goals since the adoption of the Kyoto Protocol. However, the progress of each industry was relatively consistent by region. Second, EEE tends to improve and then deteriorate or monotonically increase as economic development progresses. Third, EEE is raised by expanding industry share. Finally, EEE, which focuses on energy reduction, is likely to increase with the progress of energy-saving technology. © 2023, The Author(s).
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  • [21] Mandal S.K., Do undesirable output and environmental regulation matter in energy efficiency analysis? evidence from Indian cement industry, Energ Policy, 38, 10, pp. 6076-6083, (2010)
  • [22] Mardani A., Zavadskas E.K., Streimikiene D., Jusoh A., Khoshnoudi M., A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency, Renew Sustain Energ Rev, 70, pp. 1298-1322, (2017)
  • [23] Martinez-Zarzoso I., Bengochea-Morancho A., Pooled mean group estimation of an environmental Kuznets curve for CO<sub>2</sub>, Econ Lett, 82, 1, pp. 121-126, (2004)
  • [24] Pedroni P., Critical values for cointegration tests in heterogeneous panels with multiple regressors, Oxford Bull Econ & Stats, 61, s1, pp. 653-670, (1999)
  • [25] Pedroni P., Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis, Econ Theory, 20, 3, pp. 597-625, (2004)
  • [26] Pesaran M.H., General diagnostic tests for cross section dependence in panels Cambridge Working Papers Economics, (2004)
  • [27] Pesaran M.H., A simple panel unit root test in the presence of cross-section dependence, J Appl Econ, 22, 2, pp. 265-312, (2007)
  • [28] Pesaran M.H., Smith R., Estimating long-run relationships from dynamic heterogeneous panels, J Econ, 68, 1, pp. 79-113, (1995)
  • [29] Pesaran M.H., Shin Y., Smith R.P., Pooled mean group estimation of dynamic heterogeneous panels, J Am Stat Assoc, 94, 446, pp. 621-634, (1999)
  • [30] Rakshit I., Mandal S.K., A global level analysis of environmental energy efficiency: an application of data envelopment analysis, Energy Effic, 13, 5, pp. 889-909, (2020)