Analyzing the Impact of GDP on CO2 Emissions and Forecasting Africa’s Total CO2 Emissions with Non-Assumption Driven Bidirectional Long Short-Term Memory
| Autor: | Bismark Ameyaw, Li Yao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
020209 energy
Geography Planning and Development lcsh:TJ807-830 lcsh:Renewable energy sources Climate change forecasting 02 engineering and technology Management Monitoring Policy and Law CO2 emissions Energy policy Gross domestic product Causality (physics) Order (exchange) West Africa 0202 electrical engineering electronic engineering information engineering Econometrics Economics lcsh:Environmental sciences diversification of energy sources Consumption (economics) lcsh:GE1-350 Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants bidirectional long short-term memory (BiLSTM) climate change lcsh:TD194-195 Africa Nexus (standard) Panel data |
| Zdroj: | Sustainability, Vol 10, Iss 9, p 3110 (2018) Sustainability Volume 10 Issue 9 |
| ISSN: | 2071-1050 |
| Popis: | The amount of total carbon dioxide (CO2) emissions emitted into the environment threatens both human and global ecosystems. Based on this background, this study first analyzed the relationship between gross domestic product (GDP) and CO2 emissions in five West African countries covering the period of 2007&ndash 2014 based on a panel data model. Our causality analysis revealed that there exists a unidirectional causality running from GDP to CO2 emissions. Second, after establishing the nexus between GDP and CO2 emissions, we forecast Africa&rsquo s CO2 emissions with the aim of projecting future consumption levels. With the quest to achieve climate change targets, realistic and high accuracy total CO2 emissions projections are key to drawing and implementing realizable environmentally-friendly energy policies. Therefore, we propose a non-assumption driven forecasting technique for long-term total CO2 emissions. We implement our bidirectional long short-term memory (BiLSTM) sequential algorithm formulation for both the testing stage (2006&ndash 2014) and forecasting stage (2015&ndash 2020) on Africa&rsquo s aggregated data as well as the five selected West African countries employed herein. We then propose policy recommendations based on the direction of causality between CO2 emissions and GDP, and our CO2 emissions projections in order to guide policymakers to implement realistic and sustainable policy targets for West Africa and Africa as a whole. |
| Databáze: | OpenAIRE |
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