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Asymmetric role of non-renewable energy consumption, ICT, and financial development on ecological footprints: evidence from QARDL approach

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Abstract

This study examines long-term connection and short-term dynamics concerning ecological footprint and six independent variables, named fossil fuel consumption, energy consumption, financial depth, trade, GDP, and ICT for Pakistan’s duration from 1960 to 2019. The “QARDL-quantile autoregressive distributed lag” technique is used for time series and panel estimation. The QARDL model exhibits the connection between variables over the quantiles range, reflecting varying stages of Pakistan’s ecological footprint. The results exhibit noticeable quantile-varying co-integration connection among ecological footprint and six independent variables. The results accentuate the significant influence of energy consumption, strong financial position, economic growth, and ICT technologies on ecological well-being, which assists in understanding short and long-term impact on the environment in Pakistan.

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Fig. 1

Source: authors’ estimation

Fig. 2

Source: authors’ estimation

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Data availability

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. “LI-low income; LMI- lower-middle-income countries”.

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Authors and Affiliations

  1. Department of Business Administration, IQRA University, Karachi, 75300, Pakistan

    Syed Ali Raza, Sara Qamar & Maiyra Ahmed

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  1. Syed Ali Raza
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  2. Sara Qamar
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Syed Ali Raza: conceptualization, writing — original draft, writing — review and editing, and supervision. Sara Qamar: writing — original draft, writing — review and editing, data curation, methodology, and formal analysis. Maiyra Ahmed: writing — original draft, writing — review and editing, data curation, methodology, and formal analysis.

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Correspondence to Syed Ali Raza.

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Raza, S.A., Qamar, S. & Ahmed, M. Asymmetric role of non-renewable energy consumption, ICT, and financial development on ecological footprints: evidence from QARDL approach. Environ Sci Pollut Res 30, 20746–20764 (2023). https://doi.org/10.1007/s11356-022-23549-w

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