College of Business, University of Jeddah, Jeddah, Saudi Arabia.
Nord University Business School, Bodø, Norway.
Environ Sci Pollut Res Int. 2024 Feb;31(6):9288-9316. doi: 10.1007/s11356-023-31571-9. Epub 2024 Jan 8.
In this paper, we examined the asymmetric dynamics and causality of technological progress--proxied by green technology innovation--on both consumption-based carbon (CCO) and territory-based carbon (TCO) emissions in Saudi Arabia using quarterly data from 1990Q1 to 2021Q4. Our initial results reject the normality and linearity assumptions of data series and thus emphasize that the observed associations are quantile dependent. We firstly utilized the quantile-on-quantile regression (QQR) approach to draw the interdependency between green technology innovation and both CCO and TCO emissions. We found a strong emission-mitigating impact of green technology innovation only at (extreme) upper emission levels. We also identified a weak positive effect at (extreme) higher emission quantiles. Furthermore, we found that higher emission levels are linked with lower green technology innovation across all emission quantiles whereas a weak positive effect is perceived at lower and medium emission quantiles. We further utilized linear and nonlinear Granger causality-in- quantiles (GCQ) tests to capture an entire picture of the impact of green technology innovation on both CCO and TCO emissions. Under linear specifications of the quantile regression model, we found evidence of strong bidirectional causality between carbon emissions and green technology innovation across lower and upper quantiles. However, we found unidirectional causalities from carbon emissions to green technology innovation at medium quantiles of the conditional distribution. Besides, there is no causality at both extreme lower and extreme upper quantiles. Under nonlinear specifications of the quantile regression model, we found a weak unidirectional causality from green technology innovation to carbon emissions at (extreme) lower quantiles. We also found a weak unidirectional causality from carbon emissions to green technology innovation at medium and extreme upper quantiles. Overall, our findings indicate that green technology innovation helps abate both CCO and TCO emissions in Saudi Arabia. Our study shows policies that target green technology innovation would significantly change carbon emissions.
本文利用 1990 年第一季度至 2021 年第四季度的季度数据，考察了绿色技术创新（以绿色技术创新为代表）对沙特阿拉伯基于消费的碳（CCO）和基于领土的碳（TCO）排放的不对称动态和因果关系。我们的初步结果拒绝了数据序列的正态性和线性假设，因此强调观察到的关联是分位数依赖的。我们首先利用分位数分位数回归（QQR）方法来绘制绿色技术创新与 CCO 和 TCO 排放之间的相互依存关系。我们发现绿色技术创新对减排有很强的影响，仅在（极端）较高的排放水平上。我们还发现，在（极端）较高的排放分位数上，存在较弱的正效应。此外，我们发现，在所有排放分位数上，较高的排放水平与较低的绿色技术创新相关，而在较低和中等排放分位数上则存在较弱的正效应。我们进一步利用线性和非线性分位数格兰杰因果检验（GCQ）来捕捉绿色技术创新对 CCO 和 TCO 排放的影响的全貌。在分位数回归模型的线性规范下，我们发现碳排放量和绿色技术创新之间存在强烈的双向因果关系，跨越较低和较高分位数。然而，我们发现，在条件分布的中部分位数上，碳排放量对绿色技术创新存在单向因果关系。此外，在较低和较高分位数的极值处没有因果关系。在分位数回归模型的非线性规范下，我们发现绿色技术创新对碳排放量存在较弱的单向因果关系，在（极端）较低分位数上。我们还发现，在中部分位数和极端较高分位数上，碳排放量对绿色技术创新存在较弱的单向因果关系。总的来说，我们的研究结果表明，绿色技术创新有助于减少沙特阿拉伯的 CCO 和 TCO 排放。我们的研究表明，以绿色技术创新为目标的政策将显著改变碳排放量。
