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<p>In tracking carbon dioxide emissions (CO2e), several indicators play a decisive part. Among these, the structural change indicator stands out as a central component in understanding the interplay between economic advance and ecological effect, particularly in emerging market economies. The objective of this analysis is to assess the dynamic impact of real GDP, renewable and non-renewable energy (RE, NRE), and the Structural Change Index (SCI) on CO₂ emissions in the top ten emerging economies. The dataset spans annual observations from 2000 to 2021, and the study employs both Symmetric and Asymmetric ARDL (Autoregressive Distributed Lag) techniques to capture the nuanced effects. The Juodis et al. (<CitationRef CitationID="CR36">2021</CitationRef>) Granger approach is applied to discuss the causal links between the analysis variables. The analysis confirms cross-sectional independence, identifies the variables as I(1), and establishes long-run cointegration among them. Long-run results from the linear ARDL estimation indicate that both RE and SCI contribute to emissions reduction, while economic growth and NRE usage are associated with increased pollution levels. The results of the non-linear ARDL analysis indicate that a positive shock to the SCI is related to a decrease in CO2e, while a negative shock to the SCI leads to an increase in CO2e. The causality outcomes flashed a strong relationship between SCI and CO2emissions.</p> Graphical abstract <p></p>

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The impact of structural change on CO2 emissions using an asymmetric panel ARDL approach: evidence from the top ten emerging market economies

  • 期刊论文

  • 发表日期：

    2026年2月14日

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  • Hamrouni Daghbagi,
  • Hasni Radhouane,
  • Ben Jebli Mehdi

摘要

In tracking carbon dioxide emissions (CO2e), several indicators play a decisive part. Among these, the structural change indicator stands out as a central component in understanding the interplay between economic advance and ecological effect, particularly in emerging market economies. The objective of this analysis is to assess the dynamic impact of real GDP, renewable and non-renewable energy (RE, NRE), and the Structural Change Index (SCI) on CO₂ emissions in the top ten emerging economies. The dataset spans annual observations from 2000 to 2021, and the study employs both Symmetric and Asymmetric ARDL (Autoregressive Distributed Lag) techniques to capture the nuanced effects. The Juodis et al. (2021) Granger approach is applied to discuss the causal links between the analysis variables. The analysis confirms cross-sectional independence, identifies the variables as I(1), and establishes long-run cointegration among them. Long-run results from the linear ARDL estimation indicate that both RE and SCI contribute to emissions reduction, while economic growth and NRE usage are associated with increased pollution levels. The results of the non-linear ARDL analysis indicate that a positive shock to the SCI is related to a decrease in CO2e, while a negative shock to the SCI leads to an increase in CO2e. The causality outcomes flashed a strong relationship between SCI and CO2emissions.

Graphical abstract