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Assessing the influence of green innovation and environmental policy stringency on CO2 emissions in BRICS

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Abstract

This article examines the effect of environmental policy stringency and green innovation on CO2 emissions in the BRICS nations, using annual data from 1990 to 2019 utilizing panel FMOLS and DOLS estimators and Method of Moments Quantile Regression (MMQR). To this end, we estimate an equation in which CO2 emissions are explained by GDP, trade openness, nonrenewable and renewable energy consumption, the environmental stringency index, and green innovation, as measured by the number of patent applications for environmentally related inventions. FMOLS and DOLS results reveal that GDP, nonrenewable energy consumption, and trade openness have a positive effect on environmental pollution, whereas improvements in renewable energy consumption and environmental regulations lead to a drop in CO2 emissions. However, green innovation does not have a significant effect on CO2 emissions. MMQR estimates demonstrate that the GDP has a positive effect on CO2 emissions across all quantiles, suggesting that a higher degree of economic growth is associated with higher emissions. Based on findings, empirical evidence suggests that BRICS countries should follow the policies encouraging the reduction of nonrenewable energy consumption in the region without harming the development of the economy. Besides, policymakers should promote renewable energy consumption and enhance investment in green innovation to achieve sustainable development and environmental quality.

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Availability of data and materials

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. Readers may refer to Machado and Silva (2019) for more details on the estimation steps of the MMQR model.

  2. Individual effects and a deterministic time trend are included in the panel unit root test specifications. The Akaike information criterion (AIC) is employed to determine lag length, with a maximum lag of four. The Bartlett kernel is used for spectral estimation, and the bandwidth is chosen by Newey and West's automatic lag selection.

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Authors and Affiliations

  1. Department of Public Relations and Advertising, Faculty of Communication, Ondokuz Mayıs University, Samsun, Turkey

    Ozlem Akguc Çetinkaya

  2. Department of Economics, Faculty of Economics and Administrative Sciences, Ege University, Izmir, Turkey

    Abdurrahman Nazif Çatik

  3. Department of Economics, Faculty of Economics and Administrative Sciences, Erzincan Binali Yıldırım University, Erzincan, Turkey

    Esra Balli & Muge Manga

  4. Department of Economics, Gaziantep University, Gaziantep, Turkey

    Mehmet Akif Destek

  5. Adnan Kassar School of Business, Lebanese American University, Beirut, 1102-2801, Lebanon

    Mehmet Akif Destek

  6. Research Methods Application Center of UNEC, Azerbaijan State University of Economics (UNEC), AZ1001, Baku, Azerbaijan

    Mehmet Akif Destek

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  1. Ozlem Akguc Çetinkaya
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Appendix

Appendix

See Figs. 2 and 3.

Fig. 2
figure 2

Number of environment-related patent applications (green innovation) in BRICS countries and OECD

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Fig. 3
figure 3

EPSI Index Scores for BRICS countries and OECD

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Çetinkaya, O.A., Çatik, A.N., Balli, E. et al. Assessing the influence of green innovation and environmental policy stringency on CO2 emissions in BRICS. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04802-3

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