IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i6p3242-d767919.html
   My bibliography  Save this article

Does the Government’s Environmental Attention Affect Ambient Pollution? Empirical Research on Chinese Cities

Author

Listed:
  • Shan Huang

    (School of Computer Science and Engineering, Hunan Institute of Technology, Hengyang 421200, China)

  • Yan Ding

    (Business School, Hunan Institute of Technology, Hengyang 421200, China)

  • Pierre Failler

    (Economics and Finance Group, Portsmouth Business School, University of Portsmouth, Portsmouth PO1 3DE, UK)

Abstract

Environmental pollution has attracted growing government attention. We employ a series of panel data regression models to measure and analyze the impact of environmental attention of 284 prefecture-level municipal governments on ambient pollution in China. The results show that: (1) The improvement of government environmental attention can curb ambient pollution. (2) The impact of government environmental attention on ambient pollution is heterogeneous in the difference of regional and local environmental pollution severity. (3) Government environmental attention inhibits ambient pollution through green development and industrial upgrading. The conclusions of this paper provide evidence and implications for environmental regulation in developing countries and cities.

Suggested Citation

  • Shan Huang & Yan Ding & Pierre Failler, 2022. "Does the Government’s Environmental Attention Affect Ambient Pollution? Empirical Research on Chinese Cities," Sustainability, MDPI, vol. 14(6), pages 1-19, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3242-:d:767919
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/6/3242/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/6/3242/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    2. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    3. Huang, Zhehao & Liao, Gaoke & Li, Zhenghui, 2019. "Loaning scale and government subsidy for promoting green innovation," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 148-156.
    4. Shuai Wang & Cunyi Yang & Zhenghui Li, 2021. "Spatio-Temporal Evolution Characteristics and Spatial Interaction Spillover Effects of New-Urbanization and Green Land Utilization Efficiency," Land, MDPI, vol. 10(10), pages 1-26, October.
    5. Zhenghui Li & Fanqi Zou & Yong Tan & Jinhui Zhu, 2021. "Does Financial Excess Support Land Urbanization—An Empirical Study of Cities in China," Land, MDPI, vol. 10(6), pages 1-17, June.
    6. Lee, Chien-Chiang & Chen, Mei-Ping & Lee, Chi-Chuan, 2021. "Investor attention, ETF returns, and country-specific factors," Research in International Business and Finance, Elsevier, vol. 56(C).
    7. Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    8. Chen, Zhao & Kahn, Matthew E. & Liu, Yu & Wang, Zhi, 2018. "The consequences of spatially differentiated water pollution regulation in China," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 468-485.
    9. Zhenghui Li & Zimei Huang & Pierre Failler, 2022. "Dynamic Correlation between Crude Oil Price and Investor Sentiment in China: Heterogeneous and Asymmetric Effect," Energies, MDPI, vol. 15(3), pages 1-22, January.
    10. Wang, B. & Liu, L. & Huang, G.H. & Li, W. & Xie, Y.L., 2018. "Effects of carbon and environmental tax on power mix planning - A case study of Hebei Province, China," Energy, Elsevier, vol. 143(C), pages 645-657.
    11. Cunyi Yang & Tinghui Li & Khaldoon Albitar, 2021. "Does energy efficiency affect ambient PM2.5? The moderating role of energy investment," Papers 2105.11080, arXiv.org.
    12. Yue Liu & Zhenghui Li & Manrui Xu, 2020. "The Influential Factors of Financial Cycle Spillover: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1336-1350, May.
    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. Hu, Hui & Qi, Shaozhou & Chen, Yuanzhi, 2023. "Using green technology for a better tomorrow: How enterprises and government utilize the carbon trading system and incentive policies," China Economic Review, Elsevier, vol. 78(C).
    2. Mengzhi Xu & Jixia Li & Zeyu Ping & Qianming Zhang & Tengfei Liu & Can Zhang & Huachun Wang, 2022. "Can Local Government’s Attention Allocated to Green Innovation Improve the Green Innovation Efficiency?—Evidence from China," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    3. Zongrun Wang & Lili Yang & Xiaohang Ren & Duong Phuong Thao Pham, 2023. "Facilitate or Inhibit: Corporate Environmental Performance and Financing Costs," Evaluation Review, , vol. 47(4), pages 727-759, August.
    4. Jing Sun & Jienan Hu & Hongmei Wang & Yinfeng Shi & Ziru Wei & Tangzhe Cao, 2023. "The Government’s Environmental Attention and the Sustainability of Environmental Protection Expenditure: Evidence from China," Sustainability, MDPI, vol. 15(14), pages 1-12, July.
    5. Xu, Ye & Wen, Shuang & Tao, Chang-Qi, 2023. "Impact of environmental tax on pollution control: A sustainable development perspective," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 89-106.
    6. Danmeng Wang & Ruolan Li & Guoxi Gao & Nueryia Jiakula & Shynggys Toktarbek & Shilin Li & Ping Ma & Yongzhong Feng, 2022. "Impact of Climate Change on Food Security in Kazakhstan," Agriculture, MDPI, vol. 12(8), pages 1-13, July.
    7. Silvia Puiu & Mihaela Tinca Udriștioiu & Liliana Velea, 2022. "Air Pollution Management: A Multivariate Analysis of Citizens’ Perspectives and Their Willingness to Use Greener Forms of Transportation," IJERPH, MDPI, vol. 19(21), pages 1-15, November.

    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. Sa Xu & Cunyi Yang & Zhehao Huang & Pierre Failler, 2022. "Interaction between Digital Economy and Environmental Pollution: New Evidence from a Spatial Perspective," IJERPH, MDPI, vol. 19(9), pages 1-23, April.
    2. Kaiming Zhong & Hongyan Fu & Tinghui Li, 2022. "Can the Digital Economy Facilitate Carbon Emissions Decoupling? An Empirical Study Based on Provincial Data in China," IJERPH, MDPI, vol. 19(11), pages 1-25, June.
    3. Yan Ding & Yue Liu & Pierre Failler, 2022. "The Impact of Uncertainties on Crude Oil Prices: Based on a Quantile-on-Quantile Method," Energies, MDPI, vol. 15(10), pages 1-35, May.
    4. Yue Liu & Pierre Failler & Zhiying Liu, 2022. "Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    5. Yanling Li & Mengxin Wang & Gaoke Liao & Junxia Wang, 2022. "Spatial Spillover Effect and Threshold Effect of Digital Financial Inclusion on Farmers’ Income Growth—Based on Provincial Data of China," Sustainability, MDPI, vol. 14(3), pages 1-16, February.
    6. Nikolaos Rodousakis & George Soklis & Theodore Tsekeris, 2022. "A Supply and Use Model for Estimating the Contribution of Costs to Energy Prices," Energies, MDPI, vol. 15(19), pages 1-10, September.
    7. Shuai Wang & Cunyi Yang & Zhenghui Li, 2022. "Green Total Factor Productivity Growth: Policy-Guided or Market-Driven?," IJERPH, MDPI, vol. 19(17), pages 1-19, August.
    8. Jorge E. Galán & María Rodríguez Moreno, 2020. "At-risk measures and financial stability," Financial Stability Review, Banco de España, issue Autumn.
    9. Ibrahim Mohamed Ali Ali & Imed Attiaoui & Rabeh Khalfaoui & Aviral Kumar Tiwari, 2022. "The Effect of Urbanization and Industrialization on Income Inequality: An Analysis Based on the Method of Moments Quantile Regression," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(1), pages 29-50, May.
    10. Łukasz Jarosław Kozar & Robert Matusiak & Marta Paduszyńska & Adam Sulich, 2022. "Green Jobs in the EU Renewable Energy Sector: Quantile Regression Approach," Energies, MDPI, vol. 15(18), pages 1-21, September.
    11. Gnangnon, Sèna Kimm, 2023. "The Least developed countries' TRIPS Waiver and the Strength of Intellectual Property Protection," EconStor Preprints 271537, ZBW - Leibniz Information Centre for Economics.
    12. Yu, Linyue & Wilcox-Gök, Virginia, 2015. "The impact of maternal depression on children’s cognitive development: An analysis based on panel quantile regressions," Economics Letters, Elsevier, vol. 126(C), pages 107-109.
    13. Miao, Yang & Razzaq, Asif & Adebayo, Tomiwa Sunday & Awosusi, Abraham Ayobamiji, 2022. "Do renewable energy consumption and financial globalisation contribute to ecological sustainability in newly industrialized countries?," Renewable Energy, Elsevier, vol. 187(C), pages 688-697.
    14. Galina Besstremyannaya & Sergei Golovan, 2023. "Measuring heterogeneity in hospital productivity: a quantile regression approach," Journal of Productivity Analysis, Springer, vol. 59(1), pages 15-43, February.
    15. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data," The Econometrics Journal, Royal Economic Society, vol. 22(3), pages 292-308.
    16. Nordman, Christophe J. & Rakotomanana, Faly & Roubaud, François, 2016. "Informal versus Formal: A Panel Data Analysis of Earnings Gaps in Madagascar," World Development, Elsevier, vol. 86(C), pages 1-17.
    17. Tobias Adrian & Federico Grinberg & Nellie Liang & Sheheryar Malik & Jie Yu, 2022. "The Term Structure of Growth-at-Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(3), pages 283-323, July.
    18. Alessia Matano & Paolo Naticchioni, 2017. "The Extent of Rent Sharing along the Wage Distribution," British Journal of Industrial Relations, London School of Economics, vol. 55(4), pages 751-777, December.
    19. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    20. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.

    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:jsusta:v:14:y:2022:i:6:p:3242-:d:767919. 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.