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Does ICT lessen CO2 emissions for fast-emerging economies? An application of the heterogeneous panel estimations

Environmental Science and Pollution Research volume 27, pages 10778–10789 (2020)Cite this article

Abstract

This study examines the effects of electricity consumption, financial development, economic growth, trade and ICT on CO2 emissions in the fast-emerging countries, excluding Russia due to the unavailability of data. Cross-sectional dependency was identified using the Pesaran (2004) and Breusch and Pagan CD tests from Breusch and Pagan (1980) using annual data from 1993 to 2014 based on data availability. The second-generation panel unit root test was applied to investigate the integration order of the series. The long-run relationship among the variables was confirmed using second-generation panel cointegration techniques, which take cross-sectional dependency into account. Additionally, this study utilized the FMOLS, DOLS and robust least square estimators to determine the long-run coefficients. The results suggested that electricity usage and financial development have a positive and significant impact, while economic growth and trade have a negative and significant impact on CO2 emissions. Additionally, an inverted U-shaped relationship between ICT and CO2 emission was confirmed. This implies that pollution declines after attaining a threshold point as the ICT usage increases. Furthermore, the Dumitrescu and Hurlin (2012) heterogeneous panel causality test suggested that there is a unidirectional causal relationship between electricity consumption and CO2 emissions, CO2 emissions and ICT, gross domestic product and CO2 emissions. Another unidirectional causality exists between financial development and CO2 emissions. The study suggests that renewable energy sources can be adopted to decrease carbon emissions and to promote clean energy. Financial development needs to be further strengthened to promote the use of eco-friendly ICT products.

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Fig. 1

Notes

  1. Our study sample incudes Brazil, India, China, and South Africa. However, Russia has not been included in the list for our study, because of data unavailability for the study period. Therefore, the fast-emerging countries in this study include Brazil, India, China, and South Africa.

  2. Literally, domestic credit is the credit advanced to various sectors by banks, but it does not include the credit to the central government. Domestic credit to the private sector has been used in this study for several reasons. The banking sector performs different functions such as governing the money supply (Monetary policy), managing the deposits of the general public and dealing with other banking institutions. For these reasons, this is a broad parameter in terms of measuring the financial development of an economy (Shahbaz and Lean, 2012a, b. Several other studies, for instance Mac Kinnon (1973), King and Levine (1993), have used liquid liabilities as a share of GDP, however this cannot be used as a justified proxy to measure financial development since it only measures the volume of the financial sector. A high value of liquid liability does not imply the mobilization of savings. This parameter may misrepresent the nations showing high indicators even for underdeveloped financial systems. Among the other proxies included are the ratio of commercial bank assets to the sum of commercial bank and central bank assets. Based on the above discussion, this study applies domestic credit to the private sector as a share of GDP, which is the most common proxy (Shahbaz and Lean, 2012a, b) and was also used in the study of Pradhan et al. (2018) in cross-country panel data. Yucel (2009) can be viewed for further details in this regard.

  3. The Internet users measuring the role of ICT was available for the selected study sample. Following the study of Pradhan et al. (2018), this study uses ICT as a robust parameter since it includes internet use in terms of individuals using the internet via mobile phones, computers, personal digital assistants, gaming consoles and digital TV (World Bank, 2016).

  4. The explanation of the causal results along with the policy implications have been discussed in detail. Please see the conclusion and policy implication section of this study. For more simplicity of the results, the pairwise Dumitrescu and Hurlin (2012) causal results have been shown in figure 1 as well.

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Acknowledgements

The authors would like to thank the Editor and the anonymous reviewers for their suggestions that substantially improved the article.

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Affiliations

  1. Institute of Business Studies and Leadership, Faculty of Business and Economics, Abdul Wali Khan University, Mardan, KP, Pakistan

    Faisal Faisal &  Azizullah

  2. Department of Banking and Finance, Faculty of Economics and Administrative Sciences, Near East University, Nicosia, North Cyprus, Mersin 10, Turkey

    Turgut Tursoy

  3. Faculty of Chemical and Life Sciences, Department of Zoology, Abdul Wali Khan University, Mardan, KP, Pakistan

    Ruqiya Pervaiz

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  1. Faisal Faisal
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  2. Azizullah
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Correspondence to Faisal Faisal.

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Faisal, F., Azizullah, Tursoy, T. et al. Does ICT lessen CO2 emissions for fast-emerging economies? An application of the heterogeneous panel estimations. Environ Sci Pollut Res 27, 10778–10789 (2020). https://doi.org/10.1007/s11356-019-07582-w

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Keywords

  • ICT
  • Westerlund panel
  • Electricity use
  • Environmental degradation