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Club convergence analysis of fossil fuels material footprint at the global level

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Abstract

Material footprint is vital for playing a role in increasing the pace of climate change and the sustainability of development efforts. Fossil fuels material footprint (FFMF) remains a critical indicator of environment-friendly economic development. Fossil fuels have also retained their dominance as prominent drivers of global growth since the Industrial Revolution. FFMF levels show considerable variations in economic growth worldwide as awareness of sustainability and climate change propagates. Although biomass/carbon emission convergence have been discussed extensively in the existing literature, FFMF convergence is still scanty despite its vital role in climate change. Hence, this study adds to the existing literature by examining the convergence of FFMF for 154 countries for the period from 1970 to 2019 using club convergence analysis. The results show that FFMF converges to a single steady state, stating a symmetric decline in FFMF growth. Further, the findings from sigma and beta tests are consistent with the main results. Thus, the demonstrated convergence of FFMF directs that global efforts regarding FFMF control should be continued. Moreover, future climate change policies should also be formulated to enhance the awareness of FFMF and long-term sustainability.

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Notes

  1. A consumption-based measure of resource use is called a material footprint. It is described as a worldwide distribution of utilised raw material extraction to the economic system’s end need (Wiedmann et al., 2013). The ecological footprint measures the overall impact of human activities on the environment, including the consumption of various natural resources such as land, forests, fisheries, and agricultural land. It provides a comprehensive assessment of how human activities affect the planet’s ecosystems.

  2. σ-Convergence measures the distribution properties across regions, groups, or countries over time by examining the standard deviation (Aldy 2006; Apergis et al. 2017).

  3. β-Convergence measures the ability of an economy with relatively low initial levels of emissions to grow faster than developed economies and so create a catch-up effect with respect to relatively more polluting economies (Brock and Taylor; Apergis et al. 2017).

  4. Stochastic conditional convergence theory posits that even if two or more economies have similar initial conditions and are implementing similar policies, they may not necessarily converge in a deterministic or predictable manner. Instead, the convergence process is influenced by random shocks and fluctuations. As a result, economies may converge in a probabilistic sense, meaning that while there is a tendency for them to converge, there is no certainty or guarantee that they will do so in a linear or deterministic fashion.

  5. You can read more about how clubs are formed using these four phases in the original Phillips and Sul (2007, 2009) article. PS claims that their method overestimates clubs. Therefore, they recommend running another log(t) test to merge the clubs.

  6. https://www.unep.org/explore-topics/resource-efficiency/what-we-do/international-resource-panel

  7. \(CV \left(\mathrm{\%}\right)=\frac{(\mathrm{Standard deviation of FFMF})}{Mean of FFMF}\times 100\)

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Authors and Affiliations

  1. Economics & Business Environment Area, Indian Institute of Management Jammu, Permanent Campus, NH-44, Jagti, Nagrota, Jammu, Jammu and Kashmir, 181221, India

    Vaseem Akram

  2. Jindal Institute of Behavioural Sciences, O. P. Jindal Global University, Sonipat-Narela Road, Near Jagdishpur Village, Sonipat, Haryana-131001, India

    Sushant Bhargava

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VA conducted methodology, data and literature review, and initial draft; SB prepared the final draft of the paper.

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Akram, V., Bhargava, S. Club convergence analysis of fossil fuels material footprint at the global level. Environ Sci Pollut Res 30, 114283–114293 (2023). https://doi.org/10.1007/s11356-023-30515-7

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