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

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  • 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
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    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. 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.
    5. 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).

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