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Energy consumption, CO2 emissions and economic growth in selected ASEAN countries

Atanu Ghoshray & Marco Lorusso

Letters in Spatial and Resource Sciences2025https://doi.org/10.1007/s12076-025-00398-yarticle
AJG 1
Weight
0.44

What the paper says

This study analyses the link between economic growth, CO2 emissions and energy consumption in Indonesia, Malaysia, Philippines, and Singapore, grouped together as ASEAN-4. Our contribution is novel in two ways. Firstly, we employ patent applications in our study which acts as a proxy for technological progress. This allows us to test whether patents form a part of a possible long run equilibrium relationship between economic growth and CO2 emissions, or whether patents respond to any disequilibrium in the postulated long run relation. Secondly, since we focus on the long run, we compile a unique dataset that is long enough that can lend itself to use time series methods to identify the plausible long run equilibrium relationships for individual countries, obviating the complexities that the heterogenous set of countries may bring when considered together. Our empirical findings identify GDP to be positively associated with non-renewable energy consumption as well as CO2 emissions. In addition, we find that technological advances positively affect real GDP in the short run.

3 citations

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https://doi.org/https://doi.org/10.1007/s12076-025-00398-y

Or copy a formatted citation

@article{atanu2025,
  title        = {{Energy consumption, CO2 emissions and economic growth in selected ASEAN countries}},
  author       = {Atanu Ghoshray & Marco Lorusso},
  journal      = {Letters in Spatial and Resource Sciences},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s12076-025-00398-y},
}

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Energy consumption, CO2 emissions and economic growth in selected ASEAN countries

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.