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- Modeling the relationship between economic complexity and environmental degradation: evidence from top seven economic complexity countriesPublication . Moleiro Martins, José; Adebayo, Tomiwa Sunday; Mata, Mário Nuno; Oladipupo, Seun Damola; Adeshola, Ibrahim; Ahmed, Zahoor; Correira, Anabela BatistaThe continuous growth in CO2 emissions of nations around the globe has made achieving the aim of sustainable development extremely challenging. Therefore, the current research assesses the connection between CO2 emissions and economic complexity in the top 7 economic complexity countries while taking into account the role of economic growth, renewable energy consumption, and globalization for the period between 1993 and 2018. The research aims to answer the following questions: 1) What is the association between CO2 and the regressors in the long-run? 2) What are the effects of renewable energy consumption, economic growth, economic complexity, and globalization on CO2 emissions? The research utilized the CS-ARDL, CCEMG and panel causality approaches to investigate these interconnections. The empirical outcomes revealed that economic growth and economic complexity increase CO2 emissions while renewable energy consumption and globalization mitigate CO2 emissions. The outcomes of the causality test revealed a feedback causal connection between economic growth and CO2, while a unidirectional causality was established from economic complexity, globalization and renewable energy consumption to CO2 emissions in the top 7 economic complexity countries.
- Modeling the Dynamic Linkage between Renewable Energy Consumption, Globalization, and Environmental Degradation in South Korea: Does Technological Innovation Matter?Publication . Adebayo, Tomiwa; Coelho, Manuel Francisco; Onbaşıoğlu, Dilber Çağlar; Rjoub, Husam; Mata, Mário Nuno; Carvalho, Paulo Viegas; Xavier Rita, João; Adeshola, IbrahimThe present research assesses the influence of globalization and technological innovation on CO2 emissions in South Korea as well as taking into account the role of renewable energy consumption and energy consumption utilizing datasets between 1980 and 2018. The autoregressive distributed lag (ARDL) bounds testing method is utilized to assess long-run cointegration. The outcome of the ARDL bounds test confirmed cointegration among the series. Furthermore, the ARDL reveals that economic growth, energy consumption and globalization trigger environmental degradation while technological innovation improves the quality of the environment. In addition, the study employed the frequency domain causality test to capture causal linkage among the series. The major advantage of this approach is that causal linkage between series can be captured at the short, medium and long term, respectively. The outcomes of the causality test revealed that globalization, technological innovation, economic growth and energy use can predict CO2 emissions in South Korea.