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Investigation of the STIRPAT model of environmental quality: a case of nonlinear quantile panel data analysis

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Abstract

The determination in the quality of the environment is the outcome of increasing intensity and complexity of the economic activity. This predicament has gained attention leading to several research studies. This study adds on to the literature in estimating EKC within STIRPAT perspective. An investigation of 198 countries between 1990 and 2018 was assessed using Panel Quantile Regression. This study confirmed robust U-shaped EKC for the case of industry-, agriculture- and service-based affluence effect which denotes that over-reliance reap footprint and there is a need of aligning these real sectors sustainably. The quadratic function specification utilized helped this study to categorize sample countries in terms of sustainable or non-sustainable with respect to average affluence. Policymakers are urged to pursuit sustainable composition of real sector economic activity, which will help in increasing environmental quality.

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Funding

This study was funded by the Innovation Team Project of Guangzhou, China (Grant No. 201831799), National Social Science Fund of China (Grant No. 16BGL094), Science and Technology, Guangzhou Province, China (Grant No. 2017A040403072), and Foundation of Humanities and Social Science Research Program, Ministry of Education (Grant No. 15YJCZH225).

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Authors and Affiliations

  1. School of Innovation and Entrepreneurship, Entrepreneurship Institute, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Mansi Wang & Samma Faiz Rasool

  2. School of Management, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Mansi Wang

  3. Department of Economics, School of Business and Economics, University of Management and Technology, Lahore, 54000, Pakistan

    Noman Arshed

  4. Department of Quantitative Methods, School of Business and Economics, University of Management and Technology, Lahore, 54000, Pakistan

    Mubbasher Munir

  5. Postdoctoral Station of Statistics, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Samma Faiz Rasool

  6. College of Economics and Statistics, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Weiwen Lin

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Wang, M., Arshed, N., Munir, M. et al. Investigation of the STIRPAT model of environmental quality: a case of nonlinear quantile panel data analysis. Environ Dev Sustain 23, 12217–12232 (2021). https://doi.org/10.1007/s10668-020-01165-3

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