IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i18p11204-d908498.html
   My bibliography  Save this article

How Does Digitalization Affect Haze Pollution? The Mediating Role of Energy Consumption

Author

Listed:
  • Jing Wang

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Yubing Xu

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

Abstract

In the context of digital technology innovation, an in-depth investigation into the impact of digitalization on haze pollution is of great significance for scientifically understanding environmental effects of digitalization and building a livable civic environment. From the perspective of energy consumption intensity and structure, this paper theoretically analyzes the direct and indirect effects of digitalization on haze pollution. On this basis, the impact of digitalization on haze pollution for 81 countries over the period 2010–2019 is empirically investigated by using the system GMM and mediating effects model. Empirical results show that digitalization can effectively suppress haze pollution, and there is significant heterogeneity in this inhibiting effect. In addition, digitalization can indirectly restrain haze pollution by reducing energy consumption intensity and optimizing energy consumption structure. The findings of this paper can provide enlightenment for countries to promote digitalization, combat haze pollution, and thus enhance the health of community residents.

Suggested Citation

  • Jing Wang & Yubing Xu, 2022. "How Does Digitalization Affect Haze Pollution? The Mediating Role of Energy Consumption," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11204-:d:908498
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/18/11204/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/18/11204/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meltem Kutlar Joss & Marloes Eeftens & Emily Gintowt & Ron Kappeler & Nino Künzli, 2017. "Time to harmonize national ambient air quality standards," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(4), pages 453-462, May.
    2. William A Pizer & Steven Sexton, 2019. "The Distributional Impacts of Energy Taxes," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 13(1), pages 104-123.
    3. Xiangrong Ma & Jianping Ge & Wei Wang, 2017. "The relationship between urbanization, income growth and carbon dioxide emissions and the policy implications for China: a cointegrated vector error correction (VEC) analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 1017-1033, June.
    4. Dorsey-Palmateer, Reid & Niu, Ben, 2020. "The effect of carbon taxation on cross-border competition and energy efficiency investments," Energy Economics, Elsevier, vol. 85(C).
    5. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Karthik Murali & Michael K. Lim & Nicholas C. Petruzzi, 2019. "The Effects of Ecolabels and Environmental Regulation on Green Product Development," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 519-535, July.
    7. Jordehi, A. Rezaee, 2016. "Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1127-1138.
    8. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    9. Du, Kerui & Yu, Ying & Li, Jing, 2020. "Does international trade promote CO2 emission performance? An empirical analysis based on a partially linear functional-coefficient panel data model," Energy Economics, Elsevier, vol. 92(C).
    10. Yajie Liu & Feng Dong, 2020. "Corruption, Economic Development and Haze Pollution: Evidence from 139 Global Countries," Sustainability, MDPI, vol. 12(9), pages 1-22, April.
    11. Ju, Jingrui & Liu, Luning & Feng, Yuqiang, 2018. "Citizen-centered big data analysis-driven governance intelligence framework for smart cities," Telecommunications Policy, Elsevier, vol. 42(10), pages 881-896.
    12. Zhengquan Guo & Xingping Zhang & Yihong Ding & Xiaonan Zhao, 2021. "A Forecasting Analysis on China‘S Energy Use and Carbon Emissions Based on A Dynamic Computable General Equilibrium Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(3), pages 727-739, February.
    13. Murphree, Michael & Anderson, John (Andy), 2018. "Countering Overseas Power in Global Value Chains: Information Asymmetries and Subcontracting in the Plastics Industry," Journal of International Management, Elsevier, vol. 24(2), pages 123-136.
    14. Shahbaz, Muhammad & Nasreen, Samia & Ahmed, Khalid & Hammoudeh, Shawkat, 2017. "Trade openness–carbon emissions nexus: The importance of turning points of trade openness for country panels," Energy Economics, Elsevier, vol. 61(C), pages 221-232.
    15. Faran Ahmed & Muhammad Naeem & Muhammad Iqbal, 2017. "ICT and renewable energy: a way forward to the next generation telecom base stations," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 43-56, January.
    16. Sadorsky, Perry, 2009. "Renewable energy consumption and income in emerging economies," Energy Policy, Elsevier, vol. 37(10), pages 4021-4028, October.
    17. Christoph Bohringer and Andreas Loschel, 2006. "Promoting Renewable Energy in Europe: A Hybrid Computable General Equilibrium Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 135-150.
    18. Stephen R. Bond, 2002. "Dynamic panel data models: a guide to micro data methods and practice," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 141-162, August.
    19. Chris K. Y. Lo & Christopher S. Tang & Yi Zhou & Andy C. L. Yeung & Di Fan, 2018. "Environmental Incidents and the Market Value of Firms: An Empirical Investigation in the Chinese Context," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 422-439, July.
    20. Xu, Yan & Masui, Toshihiko, 2009. "Local air pollutant emission reduction and ancillary carbon benefits of SO2 control policies: Application of AIM/CGE model to China," European Journal of Operational Research, Elsevier, vol. 198(1), pages 315-325, October.
    21. Apergis, Nicholas & Ben Jebli, Mehdi & Ben Youssef, Slim, 2018. "Does renewable energy consumption and health expenditures decrease carbon dioxide emissions? Evidence for sub-Saharan Africa countries," Renewable Energy, Elsevier, vol. 127(C), pages 1011-1016.
    22. Laddha, Yash & Tiwari, Aviral & Kasperowicz, Rafał & Bilan, Yuriy & Streimikiene, Dalia, 2022. "Impact of Information Communication Technology on labor productivity: A panel and cross-sectional analysis," Technology in Society, Elsevier, vol. 68(C).
    23. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    24. Yi, Ming & Wang, Yiqian & Sheng, Mingyue & Sharp, Basil & Zhang, Yao, 2020. "Effects of heterogeneous technological progress on haze pollution: Evidence from China," Ecological Economics, Elsevier, vol. 169(C).
    25. Elitsa R Banalieva & Charles Dhanaraj, 2019. "Internalization theory for the digital economy," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 50(8), pages 1372-1387, October.
    26. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    27. Lange, Steffen & Pohl, Johanna & Santarius, Tilman, 2020. "Digitalization and energy consumption. Does ICT reduce energy demand?," Ecological Economics, Elsevier, vol. 176(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shunbin Zhong & Huafu Shen & Ziheng Niu & Yang Yu & Lin Pan & Yaojun Fan & Atif Jahanger, 2022. "Moving towards Environmental Sustainability: Can Digital Economy Reduce Environmental Degradation in China?," IJERPH, MDPI, vol. 19(23), pages 1-23, November.
    2. Shuangcheng Luo & Yangli Yuan, 2023. "The Path to Low Carbon: The Impact of Network Infrastructure Construction on Energy Conservation and Emission Reduction," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    3. Yu Ma & Pan Tao, 2023. "A Perspective on Management Myopia: The Impact of Digital Transformation on Carbon Emission Intensity," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mitsuru Sunada, 2008. "Network effects with quality change: an empirical analysis of the Japanese mobile telecommunications market, 1995-2001," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(8), pages 657-674.
    2. Omri, Anis & Nguyen, Duc Khuong, 2014. "On the determinants of renewable energy consumption: International evidence," Energy, Elsevier, vol. 72(C), pages 554-560.
    3. repec:ipg:wpaper:2014-535 is not listed on IDEAS
    4. Gao, Da & Li, Ge & Yu, Jiyu, 2022. "Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities," Energy, Elsevier, vol. 247(C).
    5. Díez-Esteban, José María & Farinha, Jorge Bento & García-Gómez, Conrado Diego, 2016. "The role of institutional investors in propagating the 2007 financial crisis in Southern Europe," Research in International Business and Finance, Elsevier, vol. 38(C), pages 439-454.
    6. Eicher, Theo S. & Schreiber, Till, 2010. "Structural policies and growth: Time series evidence from a natural experiment," Journal of Development Economics, Elsevier, vol. 91(1), pages 169-179, January.
    7. Manthos D. Delis & Sotirios Kokas & Steven Ongena, 2016. "Foreign Ownership and Market Power in Banking: Evidence from a World Sample," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 449-483, March.
    8. Jessica M. Mc Lay & Roy Lay-Yee & Barry J. Milne & Peter Davis, 2015. "Regression-Style Models for Parameter Estimation in Dynamic Microsimulation: An Empirical Performance Assessment," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 83-127.
    9. Huy Quang Doan, 2019. "Trade, Institutional Quality and Income: Empirical Evidence for Sub-Saharan Africa," Economies, MDPI, vol. 7(2), pages 1-23, May.
    10. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    11. Jose Garcia-Louzao & Linas Tarasonis, 2023. "Productivity-enhancing reallocation during the Great Recession: evidence from Lithuania," Oxford Economic Papers, Oxford University Press, vol. 75(3), pages 729-749.
    12. Maynou, L. & McGuire, A. & Serra-Sastre, V., 2019. "Exploring the Impact of New Medical Technology on Workforce Planning," Working Papers 19/07, Department of Economics, City University London.
    13. Yang, Yong, 2012. "Agglomeration density and tourism development in China: An empirical research based on dynamic panel data model," Tourism Management, Elsevier, vol. 33(6), pages 1347-1359.
    14. Kampelmann, Stephan & Rycx, François, 2012. "The impact of educational mismatch on firm productivity: Evidence from linked panel data," Economics of Education Review, Elsevier, vol. 31(6), pages 918-931.
    15. Bertrand, Olivier & Zuniga, Pluvia, 2006. "R&D and M&A: Are cross-border M&A different? An investigation on OECD countries," International Journal of Industrial Organization, Elsevier, vol. 24(2), pages 401-423, March.
    16. Fernando Mayoral & Carlos Garcimartín, 2013. "The impact of population on the reduction of steady-state disparities across Spanish regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(1), pages 49-69, February.
    17. Falavigna, Greta & Ippoliti, Roberto, 2023. "SMEs’ behavior under financial constraints: An empirical investigation on the legal environment and the substitution effect with tax arrears," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    18. Guerino Ardizzi & Massimiliano Cologgi, 2022. "Business models and pricing strategies in the market for ATM withdrawals," Temi di discussione (Economic working papers) 23, Bank of Italy, Economic Research and International Relations Area.
    19. Martin Andersson & Hans Lööf, 2009. "Learning‐by‐Exporting Revisited: The Role of Intensity and Persistence," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(4), pages 893-916, December.
    20. Piccoli, Luca & Tiezzi, Silvia, 2021. "Rational addiction and time-consistency: An empirical test," Journal of Health Economics, Elsevier, vol. 80(C).
    21. Jungmin Lee, 2008. "Outlier Aversion in Subjective Evaluation," Journal of Sports Economics, , vol. 9(2), pages 141-159, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11204-:d:908498. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.