ORCID Profile
0000-0002-5462-5466
Current Organisation
Bond University
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Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.SCITOTENV.2019.04.353
Abstract: This study examines the impact of globalisation (measured in terms of foreign direct investment and trade openness), and renewable energy on carbon emissions using 46 sub-Saharan African countries for the period 1980-2015. Using fixed and random effect estimation techniques, the study found that renewable energy and foreign direct investment contribute to the reduction of carbon emissions while trade openness deteriorates the environment. It was also found that population growth and financial development contribute to the increase in carbon emissions. The study found evidence for Environmental Kuznets curve hypothesis. Our results revealed that institutional quality measured using regulation has a less pronounced effect for reducing carbon emissions. However, regulation moderates economic growth and foreign direct investment to reduce carbon emissions. These results are robust to alternative estimators such as the instrumental variable generalised method of moment and dynamic fixed effect estimators. The study further demonstrated that there are variations in the results among the regions within sub-Saharan Africa. The policy implications of the paper are discussed.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 03-2023
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 2023
Publisher: JMIR Publications Inc.
Date: 02-02-2022
DOI: 10.2196/32581
Abstract: Hearing loss affects 1 in 5 people worldwide and is estimated to affect 1 in 4 by 2050. Treatment relies on the accurate diagnosis of hearing loss however, this first step is out of reach for % of those affected. Increasingly automated approaches are being developed for self-administered digital hearing assessments without the direct involvement of professionals. This study aims to provide an overview of digital approaches in automated and machine learning assessments of hearing using pure-tone audiometry and to focus on the aspects related to accuracy, reliability, and time efficiency. This review is an extension of a 2013 systematic review. A search across the electronic databases of PubMed, IEEE, and Web of Science was conducted to identify relevant reports from the peer-reviewed literature. Key information about each report’s scope and details was collected to assess the commonalities among the approaches. A total of 56 reports from 2012 to June 2021 were included. From this selection, 27 unique automated approaches were identified. Machine learning approaches require fewer trials than conventional threshold-seeking approaches, and personal digital devices make assessments more affordable and accessible. Validity can be enhanced using digital technologies for quality surveillance, including noise monitoring and detecting inconclusive results. In the past 10 years, an increasing number of automated approaches have reported similar accuracy, reliability, and time efficiency as manual hearing assessments. New developments, including machine learning approaches, offer features, versatility, and cost-effectiveness beyond manual audiometry. Used within identified limitations, automated assessments using digital devices can support task-shifting, self-care, telehealth, and clinical care pathways.
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 10-2023
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 12-2023
Publisher: Springer Science and Business Media LLC
Date: 29-05-2023
DOI: 10.1007/S11205-023-03137-2
Abstract: This study utilized instrumental variable techniques and the Driscoll-Kraay estimator to examine the effect of democracy and natural resources on income inequality using a comprehensive panel dataset from 43 sub-Saharan Africa (SSA). The findings from our empirical analysis indicated that natural resources and democracy indices such as electoral, liberal, participatory, deliberative, and egalitarian drive income inequality in SSA. Regional comparative analysis also showed that the democracy indices increase income inequality in West, Central, and Southern Africa while having a neutral effect on income inequality in Eastern Africa. Natural resources were revealed to reduce income inequality in West and Southern African countries while increasing income inequality in Eastern Africa. In the case of Central Africa, natural resources play an insignificant role in income inequality. The interactive effect analysis indicates that the democracy indices interact with natural resources to increase income inequality in SSA. Finally, the democracy indices interacted with natural resources to drive income inequality in Eastern and Southern African countries while exerting an insignificant effect on income inequality in West and Central African countries. The policy implications of the findings are discussed.
Publisher: Elsevier BV
Date: 08-2018
Publisher: Elsevier BV
Date: 03-2023
Publisher: Hindawi Limited
Date: 25-09-2021
DOI: 10.1002/ER.7301
Publisher: Wiley
Date: 17-07-2023
DOI: 10.1002/PA.2882
Abstract: Global crises have heightened policy uncertainties and efforts to address global climate change. Limited evidence exists in the literature on geopolitical risk's direct and indirect roles in addressing global emissions. In this study, we examine whether geopolitical risk could impede or facilitate efforts to attain a net‐zero emissions target through energy transition using panel data for 42 countries from 1990 to 2020. Various econometric techniques were applied in this study to present robust findings and reliable conclusions. Estimates from the Driscoll‐Kraay, Lewbel two‐stage least squares and method of moment regression techniques consistently showed that countries' geopolitical risk directly increases emissions (total greenhouse gas, carbon, methane, and nitrous oxide). At the same time, energy transition, measured with renewable energy consumption, mitigates these emissions. In addition, evidence from the partial linear functional‐coefficient model technique indicates that renewable energy consumption consistently mitigates emissions when geopolitical is minimal (at a minimum and mean level). However, the role of renewable energy consumption in reducing emissions becomes weaker when geopolitical risk is heightened—thus, when geopolitical risk reaches its maximum level. We recommend that efforts to sustain renewable energy transition and maintain geopolitical stability are vital for achieving net‐zero emissions and climate change mitigation.
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 12-2019
Publisher: Elsevier
Date: 2021
Publisher: Elsevier BV
Date: 07-2022
Publisher: Elsevier BV
Date: 09-2021
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 03-03-2023
DOI: 10.1007/S10888-023-09567-9
Abstract: The income inequality-economic growth linkage is a topical issue in economics and policy discussions. Both theoretical and empirical results on the impact of income inequality on economic growth have been controversial. One of the criticisms of the existing studies relates to using cross-sectional data and linear estimation techniques for empirical analysis. Capitalising on the limitations in the existing literature, this article employs the novel Quantile-on-Quantile Regression (QQR) approach to examine the relationship between income inequality and economic growth in BRICS. Applying the novel QQR technique helps to model how income inequality distributions affect the distributions of economic growth. The quantile cointegration tests reveal cointegration between income inequality and economic growth. The QQR results indicate that income inequality has a stronger negative effect on the lower and middle tails of economic growth in Brazil while having a stronger positive impact on economic growth in Russia, China and South Africa. For India, income inequality has a stronger negative effect on the lower tail of economic growth and a stronger positive impact on the middle and higher tails of economic growth. These results are consistent with quantile regression results. Further analysis from the Granger causality-in-quantiles shows that at various quantiles, a bidirectional causal relationship between income inequality and economic growth exists in China, while a unidirectional causality runs from income inequality to economic growth in Brazil and India. No causal relationship was found between income inequality and economic growth in Russia and South Africa. The policy implications are discussed.
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 05-2020
Publisher: Wiley
Date: 29-12-2022
DOI: 10.1111/JOCA.12505
Abstract: Considering the worsening levels of food insecurity globally, studies exploring the link between financial inclusion and food insecurity have become imperative. This paper contributes to the literature by examining the effect of financial inclusion on food insecurity using a multidimensional index of financial inclusion and a food insecurity construct obtained from the Food Insecurity Experience Scale. Based on data extracted from the seventh round of the Ghana Living Standards Survey, our preferred endogeneity‐corrected results indicate that improvements in financial inclusion is associated with a reduction in food insecurity. This finding is consistent across different conceptualisations of food insecurity, alternative weighting schemes and cut‐offs for the financial inclusion index and different quasi‐experimental methods. Financial inclusion is mainly effective in reducing food insecurity in male‐headed and rural‐located households. Our findings reveal that entrepreneurship is an important pathway through which financial inclusion influences food insecurity.
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier
Date: 2021
Publisher: Elsevier BV
Date: 09-2023
Publisher: SAGE Publications
Date: 15-08-2022
DOI: 10.1177/0958305X221118877
Abstract: Climate change remains one of the world’s significant threats today, and thus Sustainable Development Goal (SDG) 13 prioritizes countries to reduce global greenhouse gas emissions and mitigate climate change by 2030. Recent studies have scrutinized the impact of Information and Communications Technologies (ICTs) on the environment. However, the majority of these studies assumed that the environmental impact of ICT is homogenous across countries. This study, therefore, investigated the impact of ICT on environmental degradation, considering the difference in ICT quality among countries. Applying a panel dataset of 110 countries between 2000 to 2018 and the instrumental variable generalized method of moments (IV-GMM) technique, the findings revealed that ICTs improve environmental sustainability in countries with high ICT quality while degrading the environment in countries with moderate and low ICT quality. The results of the causality analysis also showed bi-directional causality between ICT and carbon emissions in countries with high and moderate ICT quality, while there is a uni-directional causality running from carbon emissions to ICT in countries with low ICT quality. Policies that enhance ICT usage through low pricing were recommended for moderate and low ICT quality countries to help mitigate environmental degradation.
Publisher: Elsevier
Date: 2021
Publisher: World Scientific Pub Co Pte Ltd
Date: 15-12-2021
DOI: 10.1142/S0217590822500035
Abstract: Prior empirical studies have employed various econometric estimation techniques to study the environmental effect of tourism demand. Prominently, these econometric modeling techniques implicitly assume that the environmental effect of tourism is symmetrical, which could sometimes be problematic. This study, therefore, utilized two econometric estimation techniques, namely, the Pesaran et al. ( 2001 ). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326) symmetric autoregressive distributed lag (ARDL) and Shin et al. ( 2014 ). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In Festschrift in Honor of Peter Schmidt, pp. 281–314. New York: Springer) nonlinear ARDL (NARDL) estimation technique to disentangle the effect of tourism demand on carbon emissions in Australia. The results from the symmetric ARDL model reveal that tourism demand significantly increases carbon emissions in the long run, indicating that a 1% increase in tourism demand contributes to a 0.155% increase in carbon emissions in the long run. Contrarily, the NARDL model shows that a positive shock (an increase) in tourism demand reduces carbon emissions while a negative shock (a decrease) in tourism demand increases carbon emissions in the long run. From the NARDL estimate, a 1% increase in tourism demand is associated with a 0.220% decline in carbon emissions, while a 1% decrease in tourism demand increases carbon emissions by 0.250%. Therefore, I argue that carbon emissions depend not only on the size of tourism demand but also on the pattern — thus the increase and decline — of tourism demand. The implications of these results for policy are discussed.
Publisher: Elsevier
Date: 2021
Publisher: Informa UK Limited
Date: 03-04-2022
Publisher: Elsevier BV
Date: 09-2019
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer International Publishing
Date: 2020
Publisher: CRC Press
Date: 18-11-2020
Publisher: Elsevier BV
Date: 11-2021
Publisher: Springer Nature Singapore
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 08-02-2021
Publisher: Elsevier BV
Date: 05-2022
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 05-2023
Publisher: Informa UK Limited
Date: 06-06-2022
Publisher: Wiley
Date: 03-10-2022
DOI: 10.1002/BSE.3269
Abstract: We augment the existing knowledge on the role of economic complexity in the environment and sustainable development debate by examining the effect of economic complexity on environmental degradation (measured by ecological footprint, CO 2 emissions, N 2 O emissions and greenhouse gas emissions) contingent on income, using data from 35 OECD countries between 1998 and 2017. With the fixed effects model estimator, we find that income facilitates economic complexity to mitigate ecological footprint, CO 2 emissions, N 2 O emissions and greenhouse gas emissions. Also, we fit a partial linear functional‐coefficient model to find that income influences economic complexity to exert a nonlinear effect on ecological footprint, CO 2 emissions, N 2 O emissions and greenhouse gas emissions. We find that economic complexity leads to an increase in ecological footprint, CO 2 emissions, N 2 O emissions and greenhouse gas emissions at lower income levels but gradually d ens them as income rises. Finally, by applying the Method of Moments Quantile regression to control for distributional heterogeneity, we also find that the mitigating effect of economic complexity on ecological footprint, CO 2 emissions, N 2 O emissions and greenhouse gas emissions is transmitted through income across quantiles. The policy implications are discussed.
Publisher: Wiley
Date: 28-04-2022
DOI: 10.1002/BSE.3104
Abstract: This study contributes to the literature by investigating the effect of environmental degradation on foreign direct investment (FDI) using comprehensive panel data from 103 developing countries between 1970 and 2019. In this study, nine variables, namely, CO 2 emissions, total greenhouse gas emissions, methane emissions, PM2.5, nitrous oxide emissions, ecological footprint of consumption, ecological footprint of production, total area (ecological footprint), and total biocapacity, were used to measure environmental degradation/sustainability. Using Lewbel's two‐stage least squares to control endogeneity issues, the result from the aggregated s le indicates that while CO 2 emissions significantly reduce FDI, the remaining environmental degradation variables stimulate FDI. Further analysis reveals that, generally, environmental degradation boosts FDI flows to low and lower‐middle income countries while reducing FDI flows to upper‐middle income countries. The regional analysis also shows that environmental degradation generally reduces FDI flows to Europe and Central Asia, and the Middle East and North Africa regions while stimulating FDI flows to South Asia, Sub‐Saharan Africa, Latin America, and the Caribbean. Environmental degradation was found to have a neutral effect on FDI flows to East Asia and the Pacific. These results are robust to alternative econometric techniques. The policy implications are discussed.
Publisher: Emerald
Date: 14-10-2019
DOI: 10.1108/IJESM-06-2019-0008
Abstract: This paper aims to use artificial neural networks to develop models for forecasting energy demand for Australia, China, France, India and the USA. The study used quarterly data that span over the period of 1980Q1-2015Q4 to develop and validate the models. Eight input parameters were used for modeling the demand for energy. Hyperparameter optimization was performed to determine the ideal parameters for configuring each country’s model. To ensure stable forecasts, a repeated evaluation approach was used. After several iterations, the optimal models for each country were selected based on predefined criteria. A multi-layer perceptron with a back-propagation algorithm was used for building each model. The results suggest that the validated models have developed high generalizing capabilities with insignificant forecasting deviations. The model for Australia, China, France, India and the USA attained high coefficients of determination of 0.981, 0.9837, 0.9425, 0.9137 and 0.9756, respectively. The results from the partial rank correlation coefficient further reveal that economic growth has the highest sensitivity weight on energy demand in Australia, France and the USA while industrialization has the highest sensitivity weight on energy demand in China. Trade openness has the highest sensitivity weight on energy demand in India. This study incorporates other variables such as financial development, foreign direct investment, trade openness, industrialization and urbanization, which are found to have an important effect on energy demand in the model to prevent underestimation of the actual energy demand. Sensitivity analysis is conducted to determine the most influential variables. The study further deploys the models for hands-on predictions of energy demand.
Publisher: Elsevier BV
Date: 07-2023
Publisher: Springer Science and Business Media LLC
Date: 10-09-2021
DOI: 10.1007/S11356-021-16368-Y
Abstract: Sustainable development policies for achieving net-zero emissions require understanding the factors that influence carbon emissions. Capitalizing on the limitations of the existing literature, this study applies the quantile-on-quantile approach to investigate economic globalization's impact on carbon emissions in Australia for 1970-2018. The results from the quantile-on-quantile revealed a positive feedback linkage between globalization and carbon emissions at all quantiles. The results further indicated that while there is a positive feedback linkage between economic growth and carbon emissions at most quantiles, a positive feedback interconnection exists between carbon emissions and coal consumption at all quantiles. As a robustness check, we employed the quantile regression test, and the results from quantile regression are consistent with the findings from the quantile-on-quantile approach. The consistency of the results suggests that these study findings are reliable and suitable for informing policies that seek to address carbon emissions in Australia. The policy implications for Australia are discussed.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 10-2023
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 07-2021
No related grants have been discovered for Alex Opoku Acheampong.