IDEAS home Printed from https://ideas.repec.org/a/taf/reroxx/v35y2022i1p5336-5356.html
   My bibliography  Save this article

Socio-economic and environmental drivers of green innovation: evidence from nonlinear ARDL

Author

Listed:
  • Cheng Jin
  • Mohsin Shahzad
  • Abaid Ullah Zafar
  • Norazah Mohd Suki

Abstract

The adoption of green technology is imperative to realise sustainable development. Considering the same, this study explores the drivers of Green Innovation (GI) based on the theoretical foundation of the Triple Bottom Line (environmental, social, and economic factors) with the integration of information and communication technologies (ICT) and institutional governance (INST) in Pakistan. This study employs a nonlinear autoregressive distributed lag (NARDL) framework on quarterly data from Q1-1996 to Q4-2019. The results reveal that positive shocks in human capital (HCI) instigate GI by 1.05%, while negative shock undermines GI by 0.93%. Similarly, positive shocks in carbon dioxide (CO2) emissions increase GI by 0.63%, while any negative shock undermines GI by 0.01%. On the other hand, positive shock in ICT leads to 0.55% advanced GI; however, this effect turned stronger in negative shocks, which leads to reduced GI by 0.78% in the long-run. These results confirm the asymmetricity because positive and negative shocks in HCI, CO2 emissions, and ICT instigated GI differently. Finally, INST and GDP contribute to enhancing GI by 0.12% and 1.69%, respectively. The results indicate that the Pakistan government should improve institutional governance, adapt, and focus on sustainable practices with ICT integration to promote green technologies.

Suggested Citation

  • Cheng Jin & Mohsin Shahzad & Abaid Ullah Zafar & Norazah Mohd Suki, 2022. "Socio-economic and environmental drivers of green innovation: evidence from nonlinear ARDL," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 5336-5356, December.
    • Handle: RePEc:taf:reroxx:v:35:y:2022:i:1:p:5336-5356
    DOI: 10.1080/1331677X.2022.2026241
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1331677X.2022.2026241
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1331677X.2022.2026241?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Li, Wei & Cao, Ning & Xiang, Zejia, 2023. "Drivers of renewable energy transition: The role of ICT, human development, financialization, and R&D investment in China," Renewable Energy, Elsevier, vol. 206(C), pages 441-450.
    2. Sebri, Maamar & Issoufou Ahmed, Ousseini & Dachraoui, Hajer, 2023. "Public spending and the resource curse in WAEMU countries: An asymmetry analysis using the hidden cointegration and non-linear panel ARDL framework," Resources Policy, Elsevier, vol. 82(C).
    3. 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.
    4. Musah, Mohammed & Onifade, Stephen Taiwo & Ankrah, Isaac & Gyamfi, Bright Akwasi & Amoako, George Kofi, 2024. "Achieving net-zero emission target in Africa: Are sustainable energy innovations and financialization crucial for environmental sustainability of sub-Saharan African state?," Applied Energy, Elsevier, vol. 364(C).
    5. Rulia Akhtar & Muhammad Mehedi Masud & Nusrat Jafrin & Sharifah Muhairah Shahabudin, 2023. "Economic growth, gender inequality, openness of trade, and female labour force participation: a nonlinear ARDL approach," Economic Change and Restructuring, Springer, vol. 56(3), pages 1725-1752, June.
    6. Rao, Amar & Talan, Amogh & Abbas, Shujaat & Dev, Dhairya & Taghizadeh-Hesary, Farhad, 2023. "The role of natural resources in the management of environmental sustainability: Machine learning approach," Resources Policy, Elsevier, vol. 82(C).
    7. Ali Nazarian & Mohsin Shahzad & Xiangan Ding & Andrea Appolloni, 2024. "Do TQM Instigate Sustainable Development: Identifying the Key Role of Green Innovation and Knowledge Management," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 2499-2524, March.

    More about this item

    Statistics

    Access and download statistics

    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:taf:reroxx:v:35:y:2022:i:1:p:5336-5356. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/rero .

    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.