What does the EKC theory leave behind? A state-of-the-art review and assessment of export diversification-augmented models.

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  • Additional Information
    • Source:
      Publisher: Springer Country of Publication: Netherlands NLM ID: 8508350 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-2959 (Electronic) Linking ISSN: 01676369 NLM ISO Abbreviation: Environ Monit Assess Subsets: MEDLINE
    • Publication Information:
      Publication: 1998- : Dordrecht : Springer
      Original Publication: Dordrecht, Holland ; Boston : D. Reidel Pub. Co., c1981-
    • Subject Terms:
      Carbon Dioxide*/analysis ; Economic Development*; Carbon ; Environmental Monitoring ; Environmental Pollution/analysis
    • Abstract:
      Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.
      (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
    • References:
      Environ Sci Pollut Res Int. 2020 Apr;27(11):12717-12724. (PMID: 32008192)
      Environ Sci Pollut Res Int. 2021 Feb;28(7):8922-8926. (PMID: 33410045)
      Appl Energy. 2020 Dec 1;279:115835. (PMID: 32952266)
      Environ Sci Pollut Res Int. 2020 Aug;27(23):29043-29054. (PMID: 32424750)
      Environ Sci Pollut Res Int. 2022 May;29(25):38395-38409. (PMID: 35079970)
      Environ Sci Pollut Res Int. 2020 Oct;27(29):37044-37056. (PMID: 32577977)
      Environ Sci Pollut Res Int. 2019 Oct;26(30):30772-30781. (PMID: 31444727)
      Environ Sci Pollut Res Int. 2018 Aug;25(22):21993-22022. (PMID: 29797200)
      Environ Sci Pollut Res Int. 2016 Jan;23(2):1916-28. (PMID: 26408117)
      Sci Total Environ. 2019 Feb 1;649:128-145. (PMID: 30172133)
      PLoS One. 2019 Mar 26;14(3):e0209532. (PMID: 30913276)
      Waste Manag. 2020 Jul 15;113:508-520. (PMID: 32546447)
      Environ Sci Pollut Res Int. 2021 Jan;28(2):2119-2131. (PMID: 32870430)
      Sci Total Environ. 2021 Feb 10;755(Pt 1):142510. (PMID: 33032130)
      J Environ Manage. 2020 Sep 15;270:110829. (PMID: 32721302)
      Sci Total Environ. 2016 Jan 15;542(Pt A):360-71. (PMID: 26520261)
      Environ Sci Pollut Res Int. 2018 Nov;25(31):31283-31296. (PMID: 30194575)
      Epidemiol Infect. 2021 Nov 16;150:e1. (PMID: 34782027)
      Sci Total Environ. 2020 Jun 1;719:137530. (PMID: 32143100)
      Glob Chang Biol. 2022 Jan;28(1):1-3. (PMID: 34697870)
      Environ Sci Pollut Res Int. 2019 Oct;26(29):30229-30241. (PMID: 31422533)
      Appetite. 2019 Dec 1;143:104402. (PMID: 31421197)
      Environ Sci Pollut Res Int. 2019 Jan;26(3):2613-2622. (PMID: 30474815)
      J Environ Manage. 2021 Nov 1;297:113419. (PMID: 34378543)
      Environ Sci Pollut Res Int. 2020 May;27(13):14702-14710. (PMID: 32052330)
      Environ Sci Pollut Res Int. 2021 Feb;28(6):7200-7211. (PMID: 33026625)
      Environ Sci Pollut Res Int. 2019 Apr;26(11):10846-10853. (PMID: 30778930)
      Environ Res. 2021 Mar;194:110663. (PMID: 33417906)
      Environ Sci Pollut Res Int. 2016 Nov;23(21):21594-21603. (PMID: 27519900)
      Environ Sci Pollut Res Int. 2017 Dec;24(36):27813-27821. (PMID: 28986721)
      Environ Sci Pollut Res Int. 2018 May;25(14):14106-14116. (PMID: 29520551)
    • Contributed Indexing:
      Keywords: Carbon emissions; China; FMOLS; Literature survey
    • Accession Number:
      142M471B3J (Carbon Dioxide)
      7440-44-0 (Carbon)
    • Publication Date:
      Date Created: 20220510 Date Completed: 20220512 Latest Revision: 20220716
    • Publication Date:
      20240105
    • Accession Number:
      PMC9085558
    • Accession Number:
      10.1007/s10661-022-10037-4
    • Accession Number:
      35536397