Abstract
This study investigates the impact of information and communication technology (ICT) on carbon dioxide emissions for a panel of 91 countries over the period 1990 to 2017. The study constructs an ICT index through principal component analysis and tests for the presence of cross-sectional dependence (CSD) in the data. The study employs pooled ordinary least squares, fixed-effects model, and system-generalized method of moments estimation techniques with panel-corrected standard errors (PCSE) to tackle the issues of CSD in the data. The findings of the study show that ICT reduces CO2 emissions for the full sample of countries. However, the comparative study of developed and developing countries depicts that ICT encourages environmental sustainability in developed countries whereas opposite results are found for developing countries. Moreover, presence of the environmental Kuznets curve is confirmed for the full sample as well as for developed and developing countries. It suggests that with higher levels of development of a country, it would be possible to contribute towards environmental sustainability along with ICT diffusion. Therefore, the outcome of this study may be helpful for policymaker and policies may be designed to encourage ICT investments in developing countries, as ICT will take care of environmental sustainability with higher levels of development.
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Notes
Ecological footprint is a quantitative measure for environmental impacts and it shows how much of environment is demanded by the individuals. Moreover, it documents the extent to which human activities are within the regenerative capacity of the biosphere (Ulucak and Bilgili 2018).
The employment of POLS to the data with CSD delivers inefficient coefficient estimates and corresponding standard error estimates are also biased.
Our panel causality test results suggest that there is bidirectional causality between CO2 emissions and ICT.
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Khan, F.N., Sana, A. & Arif, U. Information and communication technology (ICT) and environmental sustainability: a panel data analysis. Environ Sci Pollut Res 27, 36718–36731 (2020). https://doi.org/10.1007/s11356-020-09704-1
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DOI: https://doi.org/10.1007/s11356-020-09704-1