School of Commerce and Economics, Presidency University, Bengaluru, India.
GLA University, Mathura, India.
Environ Sci Pollut Res Int. 2023 Aug;30(37):87049-87070. doi: 10.1007/s11356-023-28310-5. Epub 2023 Jul 7.
This paper aims to investigate the dynamic nexus between economic complexity index (ECI), technological development (TIN), human capital (HC) and environmental quality in India for transition towards a sustainable environment. This study is based on secondary data covering the period from 1985 to 2018. For empirical analysis, this study applied "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model framework under the estimation of autoregressive distributed lag (ARDL) model and vector error correction model (VECM) model. The empirical findings of model 1 show ECI, TIN, HC and urbanization (URB) as the helping hands to mitigate the problem of environmental degradation by shrinking the level of EF, whereas for model 2, ECI and TIN failed to influence the CO emissions, but HC served as a stimulant for environmental quality enhancement by declining the level of CO emissions. In contrast, GDP growth and URB strengthen the CO emissions levels. Moreover, in VECM framework, estimated findings reveal that the covariables Granger-cause EF and CO emissions, inferring that causality flows asynchronously from its covariables to EF and CO. Impulse response function (IRF) revealed that the responses in EF and CO emissions ascribed to changes in its covariables. The outcome of the study has some implications for environmental policy strategists to prepare sustainable environment policies and other responsible authorities for sustainable development goal (SDGs), academician and scholars. All the stakeholders involved in environmental economics and policymakers can evaluate this study to design proper policy framework with respect to the environment. There are few studies that explore the dynamic nexus between ECI, TIN and HC with environmental quality in the control environment of URB and GDP growth using the STIRPAT model for India.
本文旨在探讨印度经济复杂度指数（ECI）、技术发展（TIN）、人力资本（HC）与环境质量之间的动态关系，以实现向可持续环境的转型。本研究基于涵盖 1985 年至 2018 年期间的二手数据。在实证分析中，本研究应用“人口、富裕和技术对冲击的随机影响”（STIRPAT）模型框架，并在自回归分布滞后（ARDL）模型和向量误差修正模型（VECM）模型的估计下进行。模型 1 的实证结果表明，ECI、TIN、HC 和城市化（URB）通过降低 EF 的水平有助于缓解环境退化问题，而对于模型 2，ECI 和 TIN 未能影响 CO 排放，但 HC 通过降低 CO 排放水平促进了环境质量的提高。相比之下，GDP 增长和 URB 则增强了 CO 排放水平。此外，在 VECM 框架中，估计结果表明，协变量 Granger 导致 EF 和 CO 排放，这表明因果关系从协变量异步流向 EF 和 CO。脉冲响应函数（IRF）揭示了 EF 和 CO 排放的响应归因于其协变量的变化。研究结果对环境政策制定者制定可持续环境政策以及其他负责可持续发展目标（SDGs）的机构、学者具有一定的启示意义。所有涉及环境经济学的利益相关者和政策制定者都可以评估本研究，以针对环境制定适当的政策框架。很少有研究在控制 URB 和 GDP 增长的环境下，使用 STIRPAT 模型探讨 ECI、TIN 和 HC 与印度环境质量之间的动态关系。
