Search Advanced

Data Science in Finance and Economics

2022, Volume 2, Issue 4: 371-390. doi: 10.3934/DSFE.2022019
Previous Article Next Article
Research article

How does the digital economy affect industrial eco-efficiency? Empirical evidence from China

  • School of Statistics, Lanzhou University of Finance and Economics, Lanzhou, China
  • Received: 02 October 2022 Revised: 23 October 2022 Accepted: 25 October 2022 Published: 31 October 2022

  • JEL Codes: O11, Q57

  • Industry is a sector with large energy consumption and pollutant emissions. Improving industrial eco-efficiency is crucial to energy conservation and pollution reduction. The digital economy has developed rapidly in recent years. However, there is a lack of research on the specific relationship between the digital economy and industrial eco-efficiency. This study measured the industrial eco-efficiency of 30 provinces in China from 2010 to 2020, through a super-efficiency slack-based measure (SBM) considering desirable outputs. By constructing a two-way fixed effect model and a panel quantile model, this study explored the effects of the digital economy on industrial eco-efficiency on a national scale. Furthermore, this study conducted grouping regression and investigated the heterogeneous impacts of the digital economy on industrial eco-efficiency. Finally, this study built a spatial Durbin model to explore the spatial effects of digital economy on industrial eco-efficiency. According to the empirical results, this study yielded the following conclusions. First, the digital economy has a significantly positive effect on industrial eco-efficiency at the national scale, with diminishing marginal returns. Second, the effects of the digital economy on industrial eco-efficiency are significantly heterogeneous on a regional scale. For eastern regions, the effects of the digital economy on industrial eco-efficiency are significantly positive, while they are negative for western regions. Third, the spillover effect of the digital economy on industrial eco-efficiency is not significant in China, indicating that there is digital isolation.

    Citation: Lu Liu, Ming Liu. How does the digital economy affect industrial eco-efficiency? Empirical evidence from China[J]. Data Science in Finance and Economics, 2022, 2(4): 371-390. doi: 10.3934/DSFE.2022019

    Related Papers:

  • Industry is a sector with large energy consumption and pollutant emissions. Improving industrial eco-efficiency is crucial to energy conservation and pollution reduction. The digital economy has developed rapidly in recent years. However, there is a lack of research on the specific relationship between the digital economy and industrial eco-efficiency. This study measured the industrial eco-efficiency of 30 provinces in China from 2010 to 2020, through a super-efficiency slack-based measure (SBM) considering desirable outputs. By constructing a two-way fixed effect model and a panel quantile model, this study explored the effects of the digital economy on industrial eco-efficiency on a national scale. Furthermore, this study conducted grouping regression and investigated the heterogeneous impacts of the digital economy on industrial eco-efficiency. Finally, this study built a spatial Durbin model to explore the spatial effects of digital economy on industrial eco-efficiency. According to the empirical results, this study yielded the following conclusions. First, the digital economy has a significantly positive effect on industrial eco-efficiency at the national scale, with diminishing marginal returns. Second, the effects of the digital economy on industrial eco-efficiency are significantly heterogeneous on a regional scale. For eastern regions, the effects of the digital economy on industrial eco-efficiency are significantly positive, while they are negative for western regions. Third, the spillover effect of the digital economy on industrial eco-efficiency is not significant in China, indicating that there is digital isolation.


    加载中


    [1] Anselin L, Gallo JL, Jayet H (2008) Spatial panel econometrics. In: The Econometrics of Panel Data: Fundamentals and Recent Developments in Theory and Practice, edited by Mátyás L and Sevestre P, Berlin, Heidelberg: Springer, 625–660. http://doi.org/10.1007/978-3-540-75892-1_19
    [2] Carlsson B (2004) The Digital Economy: what is new and what is not? Struct Chang Econ Dyn 15: 245–264. http://doi.org/10.1016/j.strueco.2004.02.001 doi: 10.1016/j.strueco.2004.02.001
    [3] Chen L, Cheng W, Ciuriak D, et al. (2019) The digital economy for economic development: Free flow of data and supporting policies. Policy Brief 4. SSRN Electron J https://ssrn.com/abstract=3413717
    [4] Chen P (2022) Is the digital economy driving clean energy development? -New evidence from 276 cities in China. J Clean Prod 372: 133783. http://doi.org/10.1016/j.jclepro.2022.133783 doi: 10.1016/j.jclepro.2022.133783
    [5] Cui J, Wang W, Chen Z, et al. (2022) How digitalization and financial development impact eco-efficiency? Evidence from China. Environ Sci Pollut Res, 1–15. http://doi.org/10.1007/s11356-022-22366-5 doi: 10.1007/s11356-022-22366-5
    [6] Dabbous A, Tarhini A (2021) Does sharing economy promote sustainable economic development and energy efficiency? Evidence from OECD countries. J Innov Knowl 6: 58–68. http://doi.org/10.1016/j.jik.2020.11.001 doi: 10.1016/j.jik.2020.11.001
    [7] Du J, Liang L, Zhu J (2010) A slacks-based measure of super-efficiency in data envelopment analysis: a comment. Eur J Oper Res 204: 694–697. http://doi.org/10.1016/j.ejor.2009.12.007 doi: 10.1016/j.ejor.2009.12.007
    [8] ElMassah S, Mohieldin M (2020) Digital transformation and localizing the sustainable development goals (SDGs). Ecol Econ 169: 106490. http://doi.org/10.1016/j.ecolecon.2019.106490 doi: 10.1016/j.ecolecon.2019.106490
    [9] Fujii H, Managi S (2013) Determinants of eco-efficiency in the Chinese industrial sector. J Environ Sci 25: S20–S26. http://doi.org/10.1016/s1001-0742(14)60619-7 doi: 10.1016/s1001-0742(14)60619-7
    [10] Han Y, Zhang F, Huang L, et al. (2021) Does industrial upgrading promote eco-efficiency? A panel space estimation based on Chinese evidence. Energy Policy 154: 112286. http://doi.org/10.1016/j.enpol.2021.112286 doi: 10.1016/j.enpol.2021.112286
    [11] Hickel J (2020) The sustainable development index: Measuring the ecological efficiency of human development in the anthropocene. Ecol Econ 167: 106331. http://doi.org/10.1016/j.ecolecon.2019.05.011 doi: 10.1016/j.ecolecon.2019.05.011
    [12] Kim B, Barua A, Whinston AB (2002) Virtual field experiments for a digital economy: a new research methodology for exploring an information economy. Decis Support Syst 32: 215–231. http://doi.org/10.1016/S0167-9236(01)00094-X doi: 10.1016/S0167-9236(01)00094-X
    [13] Koenker R, Bassett Jr G (1978) Regression quantiles. Econometrica 46: 33–50. http://doi.org/10.2307/1913643 doi: 10.2307/1913643
    [14] Krugman P (1991) Increasing returns and economic geography. J Polit Econ 99: 83–499. http://doi.org/10.1086/261763 doi: 10.1086/261763
    [15] Lee Lf, Yu J (2016) Identification of spatial Durbin panel models. J Appl Econ 31: 133–162. http://doi.org/10.1002/jae.2450 doi: 10.1002/jae.2450
    [16] LeSage J, Pace RK (2009) Introduction to spatial econometrics, Chapman and Hall/CRC. http://doi.org/10.1201/9781420064254
    [17] Li G (2019) Spatiotemporal Dynamics of Ecological Total-Factor Energy Efficiency and Their Drivers in China at the Prefecture Level. Int J Environ Res Public Health 16: 3480. http://doi.org/10.3390/ijerph16183480 doi: 10.3390/ijerph16183480
    [18] Li Y, Yang X, Ran Q, et al. (2021) Energy structure, digital economy, and carbon emissions: evidence from China. Environ Sci Pollut Res 28: 64606–64629. http://doi.org/10.1007/s11356-021-15304-4 doi: 10.1007/s11356-021-15304-4
    [19] Liu F, Zhang C, Zhang Y, et al. (2022a) A data-driven approach for the measurement and improvement of regional industrial ecological efficiency for carbon peaking and carbon neutralization. Environ Sci Pollut Res, 1–16. http://doi.org/10.1007/s11356-022-22699-1 doi: 10.1007/s11356-022-22699-1
    [20] Liu F, Zhou S, Yang Y, et al. (2022b) Research on Industrial Ecological Efficiency Evaluation and Improvement Countermeasures Based on Data-Driven Evaluations from 30 Provinces and Cities in China. Sustainability 14: 8665. http://doi.org/10.3390/su14148665 doi: 10.3390/su14148665
    [21] Luo K, Liu Y, Chen P-F, et al. (2022) Assessing the impact of digital economy on green development efficiency in the Yangtze River Economic Belt. Energy Econ 112: 106127. http://doi.org/10.1016/j.eneco.2022.106127 doi: 10.1016/j.eneco.2022.106127
    [22] Mardani A, Zavadskas EK, Streimikiene D, et al. (2017) A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency. Renew Sust Energ Rev 70: 1298–1322. http://doi.org/10.1016/j.rser.2016.12.030 doi: 10.1016/j.rser.2016.12.030
    [23] Mawson VJ, Hughes BR (2019) The development of modelling tools to improve energy efficiency in manufacturing processes and systems. J Manuf Syst 51: 95–105. http://doi.org/10.1016/j.jmsy.2019.04.008 doi: 10.1016/j.jmsy.2019.04.008
    [24] Moulton BR (2000) GDP and the Digital Economy: Keeping up with the Changes. In: Understanding the Digital Economy, edited by Erik B and Brian K, MIT Press, 34–48. Available from: http://196.43.179.6:8080/xmlui/bitstream/handle/123456789/429/Understanding-%20the-%20digital-%20economy%20-%20data-tools-%20and-%20research.pdf?sequence=1#page=41
    [25] Ng IC (2014) New business and economic models in the connected digital economy. J Revenue Pricing Manage 13: 149–155. http://doi.org/10.1057/rpm.2013.27 doi: 10.1057/rpm.2013.27
    [26] Panayotou T (1993) Empirical tests and policy analysis of environmental degradation at different stages of economic development. Available from http://www.ilo.org/public/libdoc/ilo/1993/93B09_31_engl.pdf
    [27] Park Y, Meng F, Baloch MA (2018) The effect of ICT, financial development, growth, and trade openness on CO2 emissions: an empirical analysis. Environ Sci Pollut Res 25: 30708–30719. http://doi.org/10.1007/s11356-018-3108-6 doi: 10.1007/s11356-018-3108-6
    [28] Raheem ID, Tiwari AK, Balsalobre-Lorente D (2020) The role of ICT and financial development in CO2 emissions and economic growth. Environ Sci Pollut Res 27: 1912–1922. http://doi.org/10.1007/s11356-019-06590-0 doi: 10.1007/s11356-019-06590-0
    [29] Reith CC, Guidry MJ (2003) Eco-efficiency analysis of an agricultural research complex. J Environ Manage 68: 219–229. http://doi.org/10.1016/S0301-4797(02)00161-5 doi: 10.1016/S0301-4797(02)00161-5
    [30] Ren XY, Yang SL (2013) An Empirical Research on the Relationship between Foreign Direct Investment and Carbon Dioxide Emission Intensity of China. AMR 807–809: 951–957. Available from: https://www.scientific.net/AMR.807-809.951
    [31] Schaltegger S, Sturm A (1990) Ökologische rationalität: ansatzpunkte zur ausgestaltung von ökologieorientierten managementinstrumenten. die Unternehmung 44: 273–290. Available from: https://www.jstor.org/stable/24180467
    [32] Shahnazi R, Dehghan Shabani Z (2019) The effects of spatial spillover information and communications technology on carbon dioxide emissions in Iran. Environ Sci Pollut Res 26: 24198–24212. http://doi.org/10.1007/s11356-019-05636-7 doi: 10.1007/s11356-019-05636-7
    [33] Shao L, Yu X, Feng C (2019) Evaluating the eco-efficiency of China's industrial sectors: A two-stage network data envelopment analysis. J Environ Manage 247: 551–560. http://doi.org/10.1016/j.jenvman.2019.06.099 doi: 10.1016/j.jenvman.2019.06.099
    [34] Sun H, Kporsu AK, Taghizadeh-Hesary F, et al. (2020) Estimating environmental efficiency and convergence: 1980 to 2016. Energy 208: 118224. http://doi.org/10.1016/j.energy.2020.118224 doi: 10.1016/j.energy.2020.118224
    [35] Swamy LN (2020) The Digital Economy: New Business Models and Key Features. Int J Res Eng Sci Manage 3: 118–122. Available from: http://journals.resaim.com/ijresm/article/view/33.
    [36] Tang C, Xue Y, Wu H, et al. (2022) How does telecommunications infrastructure affect eco-efficiency? Evidence from a quasi-natural experiment in China. Technol Soc 69: 101963. http://doi.org/10.1016/j.techsoc.2022.101963 doi: 10.1016/j.techsoc.2022.101963
    [37] Tobler WR (1970) A computer movie simulating urban growth in the Detroit region. Econ Geogr 46 (sup1): 234–240. Available from: https://www.urban-informatics.org/papers/tobler.pdf
    [38] Viet-Ngu H, Alauddin M (2012) Input-Orientated Data Envelopment Analysis Framework for Measuring and Decomposing Economic, Environmental and Ecological Efficiency: An Application to OECD Agriculture. Environ Resour Econ 51: 431–452. http://doi.org/10.1007/s10640-011-9506-6 doi: 10.1007/s10640-011-9506-6
    [39] Xu J, Huang D, He Z, et al. (2020) Research on the Structural Features and Influential Factors of the Spatial Network of China's Regional Ecological Efficiency Spillover. Sustainability 12: 3137. http://doi.org/10.3390/su12083137 doi: 10.3390/su12083137
    [40] Xu Y, Li T (2022) Measuring digital economy in China. Natl Account Rev 4: 251–272. http://doi.org/10.3934/nar.2022015 doi: 10.3934/nar.2022015
    [41] Xue Y, Tang C, Wu H, et al. (2022) The emerging driving force of energy consumption in China: Does digital economy development matter? Energy Policy 165: 112997. http://doi.org/10.1016/j.enpol.2022.112997 doi: 10.1016/j.enpol.2022.112997
    [42] Yi M, Liu Y, Sheng MS, et al. (2022) Effects of digital economy on carbon emission reduction: New evidence from China. Energy Policy 171: 113271. http://doi.org/10.1016/j.enpol.2022.113271 doi: 10.1016/j.enpol.2022.113271
    [43] Yuan B, Ren S, Chen X (2017) Can environmental regulation promote the coordinated development of economy and environment in China's manufacturing industry? –A panel data analysis of 28 sub-sectors. J Clean Prod 149: 11–24. http://doi.org/10.1016/j.jclepro.2017.02.065 doi: 10.1016/j.jclepro.2017.02.065
    [44] Zhang J, Lyu Y, Li Y, et al. (2022a) Digital economy: An innovation driving factor for low-carbon development. Environ Impact Assess Rev 96: 106821. http://doi.org/10.1016/j.eiar.2022.106821 doi: 10.1016/j.eiar.2022.106821
    [45] Zhang L, Mu R, Zhan Y, et al. (2022b) Digital economy, energy efficiency, and carbon emissions: Evidence from provincial panel data in China. Sci Total Environ 852: 158403. http://doi.org/10.1016/j.scitotenv.2022.158403 doi: 10.1016/j.scitotenv.2022.158403
    [46] Zhang N, Kong F, Yu Y (2015) Measuring ecological total-factor energy efficiency incorporating regional heterogeneities in China. Ecol Indic 51: 165–172. http://doi.org/10.1016/j.ecolind.2014.07.041 doi: 10.1016/j.ecolind.2014.07.041
    [47] Zhang RL, Liu XH (2021) Evaluating ecological efficiency of Chinese industrial enterprise. Renew Energy 178: 679–691. http://doi.org/10.1016/j.renene.2021.06.119 doi: 10.1016/j.renene.2021.06.119
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Data Science in Finance and Economics

Metrics

Article views(931) PDF downloads(61) Cited by(0)

Preview PDF
Download XML
Export Citation
Article outline

Figures and Tables

Tables(10)

Other Articles By Authors

Related pages

Tools

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog