Abstract
This research aims to investigate the relationship between carbon dioxide (CO2) emissions and energy consumption on the economic growth of countries in the world based on Gross Domestic Product (GDP). We use a large volume of data related to CO2 emissions per capita and energy consumption per capita of each country in the world, so a clustering process is needed using the K-Means method, which divides the country into three cluster labels: high, medium, and low. Then, we performed multiple linear regression using the Generalized Least Square with Autoregressive (GLSAR) method for data that did not satisfy the Best Linear Unbiased Estimator (BLUE) criteria. The results are that countries included in the high cluster have a closer relationship between CO2 emissions and energy consumption to GDP than the medium cluster. Likewise, for the medium cluster against the low cluster.
| Original language | English |
|---|---|
| Pages (from-to) | 657-669 |
| Number of pages | 13 |
| Journal | European Journal of Pure and Applied Mathematics |
| Volume | 16 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 8 Decent Work and Economic Growth
Keywords
- Carbon dioxide (CO) emissions
- Economic growth
- Energy consumption
- Generalized Least Square
- K-Means
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