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- 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.
- Another look into the relationship between economic growth, carbon emissions, agriculture and urbanization in Thailand: a frequency domain analysisPublication . Mata, Mário Nuno; Oladipupo, Seun Damola; Rjoub, Husam; Ferrão, Joaquim; Altuntaş, Mehmet; Martins, Jessica Nunes; Kirikkaleli, Dervis; Dantas, Rui; Lourenco, AntonioThis empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand’s economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand’s economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand’s economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand’s macroeconomic indicators.
- Implications of Governance, Natural Resources, and Security Threats on Economic Development: Evidence from Sub-Saharan AfricaPublication . Rjoub, Husam; IFEDIORA, CHUKA; Odugbesan, Jamiu Adetola; Iloka, Chiemelie Benneth; Xavier Rita, João; Dantas, Rui; Mata, Mário Nuno; Moleiro Martins, JoséSub-Saharan African countries are known to be bedeviled with some challenges hindering the economic development. Meanwhile, some of these issues have not been exhaustively investigated in the context of the region. Thus, this study aimed at investigating the implications of government effectiveness, availability of natural resources, and security threats on the regions’ economic develop ment. Yearly data, spanning from 2007 to 2020, was converted from low frequency (yearly) to high frequency (quarterly) and utilized. Data analysis was conducted using Dynamic heterogeneous panel level estimators (PMG and CS-ARDL). Findings show that while PMG estimator confirms a long-run causal effect of governance, natural resources, and security threats on economic development, only natural resources show a short-run causal effect with economic development, while the CS-ARDL (model 2) confirms the significance of all the variables both in the long and short-run. Moreover, the ECT coefficients for both models were found to be statistically significant at less than 1% significance level, which indicates that the systems return back to equilibrium in case of a shock that causes disequilibrium, and in addition, reveals a stable long-run cointegration among the variables in the model. Finally, this study suggests that the policy makers in SSA countries should place more emphasis on improving governance, managing security challenges, and effectively utilizing rents from the natural resources, as all these have severe implications for the economic development of the region if not addressed.