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http://hdl.handle.net/2080/5939Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Mohapatra, Ankit | - |
| dc.contributor.author | Mishra, Bikash Ranjan | - |
| dc.date.accessioned | 2026-09-10T12:27:45Z | - |
| dc.date.available | 2026-09-10T12:27:45Z | - |
| dc.date.issued | 2026-08 | - |
| dc.identifier.citation | International Conference on Climate Change and its Impact on Economy, Business and Society: A Global Perspective (ICCCIEBS), Pondicherry University, Pondicherry, 26-28 August 2026 | en_US |
| dc.identifier.uri | http://hdl.handle.net/2080/5939 | - |
| dc.description | Copyright belongs to proceeding publisher | en_US |
| dc.description.abstract | This study examines the relationship among renewable electricity transition, coal dependence, and electricity-sector carbon intensity in nine coal-dependent emerging economies during 2000-2022. The selected countries are characterized by sustained reliance on coal for at least one-third of total electricity generation, making them highly relevant for analysing electricity-sector decarbonization challenges in emerging markets. The study employs an Error Correction Mechanism (ECM) based Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) approach to address cross-sectional dependence, heterogeneous dynamics, and long-run equilibrium relationships among the variables. Electricity-sector carbon intensity is considered the dependent variable, while renewable electricity share, coal-based electricity share, energy imports, and industrial value added are the explanatory variables. The empirical analysis confirms the presence of cross-sectional dependence across countries, indicating the influence of common global energy and climate-related shocks. The CIPS unit root and Westerlund cointegration tests validate the suitability of the ECM-based CS-ARDL framework. The estimated error-correction coefficient is negative and highly significant, confirming strong long-run convergence dynamics. The findings reveal that renewable electricity transition significantly reduces electricity-sector carbon intensity in both the short run and long run, whereas coal dependence substantially increases carbon intensity across the sampled economies. In contrast, energy imports and industrial structure exhibit statistically insignificant effects after controlling for electricity-generation composition and cross-sectional dependence. Robustness analysis using FGLS estimation confirms the consistency and stability of the core findings. The study suggests that electricity-generation composition remains the primary determinant of electricity-sector climate sustainability in coal-dependent emerging economies. From a policy perspective, the findings highlight the urgent need to accelerate renewable electricity deployment, reduce structural coal dependence, modernize electricity infrastructure, and promote cleaner transition pathways to achieve long-term decarbonization and climate sustainability objectives | en_US |
| dc.subject | Energy Security | en_US |
| dc.subject | Climate Sustainability | en_US |
| dc.subject | Carbon Intensity | en_US |
| dc.subject | Electricity Sector Transition | en_US |
| dc.title | Electricity Sector Transition, Energy Security and Climate Sustainability in Coal-Dependent Emerging Economies: Evidence from an ECM-based CS-ARDL approach | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Conference Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2026_ICCCIEBS_AMohapatra_Electricity.pdf | 762.45 kB | Adobe PDF | View/Open Request a copy |
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