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Can information and communication technology reduce CO2 emission? A quantile regression analysis

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Abstract

By employing China’s provincial panel data covering period 2001–2016, the present study empirically investigates the impact of ICT on CO2 emission intensity. Specifically, this paper utilizes Internet penetration and mobile phone penetration as proxies to measure ICT respectively and employs quantile regression method to estimate the benchmark model at five quantiles (0.1, 0.25, 0.5, 0.75, and 0.9). It is demonstrated that Internet penetration at the national level has a significant negative effect on the CO2 emission intensity for all quantiles. In addition, Internet penetration has a significant negative effect on CO2 emission intensity at all quantiles except for 0.1 quantile for China’s eastern provinces and has a significant negative effect on CO2 emission intensity at all quantiles for China’s central provinces, whereas Internet penetration has no significant negative impact on CO2 emission intensity at all quantiles for China’s western provinces. By comparison, the reduction effect of Internet penetration on CO2 emission intensity in China’s eastern and central provinces is more obvious and in contrast with the reduction effect of Internet penetration on CO2 emission intensity in China’s eastern provinces, it is greater in China’s central provinces. Finally, the impact of mobile phone penetration on CO2 emission intensity is generally consistent with the impact of Internet penetration. This study provides further evidence that developing countries can simultaneously achieve economic development and reduce carbon emissions through ICT.

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Funding

This study was financially supported by the Key Project of Philosophy and Social Sciences Research, Ministry of Education PRC (16JZD013), and The Key Project of National Natural Science Foundation of China (71431006).

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Chen, X., Gong, X., Li, D. et al. Can information and communication technology reduce CO2 emission? A quantile regression analysis. Environ Sci Pollut Res 26, 32977–32992 (2019). https://doi.org/10.1007/s11356-019-06380-8

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