Idris A. Adediran, Raymond Swaray, Aminat O. Orekoya and Balikis A. Kabir
This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.
Abstract
Purpose
This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.
Design/methodology/approach
The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.
Findings
The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.
Originality/value
The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.
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Idris A. Adediran, Abdulfatai Salawudeen and Syed Nasir Ashraf Sabzwari
This paper aims to make the first attempt to study the transmission of COVID-19 pandemic-induced shocks to the global Islamic stock markets in the midst of the overall…
Abstract
Purpose
This paper aims to make the first attempt to study the transmission of COVID-19 pandemic-induced shocks to the global Islamic stock markets in the midst of the overall macroeconomic environment and cross-country trade linkages. This is made possible by constructing a global vector autoregressive (GVAR) model and with it the authors arrive at noteworthy conclusions.
Design/methodology/approach
The paper estimates both fixed and time-varying weights GVAR models for 15 Islamic stock markets with 5,000 bootstrap replications and reports impulse response functions. It simulates four shocks associated with the pandemic: first, a standard error negative shock to oil price; second, a standard error negative shock to the global Islamic stock markets; third, a standard error positive shock to equity-based uncertainty index; and fourth, a standard error negative shock to economic activity (inflation).
Findings
The paper shows that the pandemic engenders immediate negative impacts on the Islamic stock markets with the biggest impacts borne by the USA and China and the least by markets in the Middle East. The study documents the magnitudes of the responses to the shocks and shows that the impacts of the pandemic will take about 20 months to wither completely.
Originality/value
The findings throw up diversification benefits for investors toward the UAE, Oman, Bahrain and other Middle East markets especially during crisis. It further reveals the need for counter-cyclical measures in all countries to curtail the negative impacts of the pandemic which could linger for up to 20 months.
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Joseph David, Awadh Ahmed Mohammed Gamal, Mohd Asri Mohd Noor and Zainizam Zakariya
Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil…
Abstract
Purpose
Despite the huge financial resources associated with oil, Nigeria has consistently recorded poor growth performance. Therefore, this study aims to examine how corruption and oil rent influence Nigeria’s economic performance during the 1996–2021 period.
Design/methodology/approach
Various estimation techniques were used. These include the bootstrap autoregressive distributed lag (ARDL) bounds-testing, dynamic ordinary least squares (DOLS), the fully modified OLS (FMOLS) and the canonical cointegration regression (CCR) estimators and the Toda–Yamamoto causality.
Findings
The bounds testing results provide evidence of a cointegrating relationship between the variables. In addition, the results of the ARDL, DOLS, CCR and FMOLS estimators demonstrate that oil rent and corruption have a significant positive impact on growth. Further, the results indicate that human capital and financial development enhance economic growth, whereas domestic investment and unemployment rates slow down long-term growth. Additionally, the causality test results illustrate the presence of a one-way causality from oil rent to economic growth and a bi-directional causal relationship between corruption and economic growth.
Originality/value
Existing studies focused on the effects of either oil rent or corruption on growth in Nigeria. Little attention has been paid to the exploration of how the rent from oil and the pervasiveness of corruption contribute to the performance of the Nigerian economy. Based on the outcome of this study, strategies and policies geared towards reducing oil dependence and the pervasiveness of corruption, enhancing human capital and financial development and reducing unemployment are recommended.
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Social movements, justice campaigns and civil activism have gained recent scholarly attention among non-Western democracies since the end of the Cold War. Yet the meaning and…
Abstract
Social movements, justice campaigns and civil activism have gained recent scholarly attention among non-Western democracies since the end of the Cold War. Yet the meaning and practical implications of civil activism remain contested especially in contexts linked to militarised democracy and the criminalisation of civil activism. Importantly, the broader political terrain within which militarised democracy is situated is increasingly changing, bringing new challenges to its understanding. This chapter builds on liberal democratic theory and discusses militarised democracy in Nigeria to critique state-centric notion of criminology. It draws on two case examples, namely the proscription of the Indigenous People of Biafra (IPOB) in 2017 by the federal government against its organised protests for self-determination and the state repressive response to the nation-wide protest against police brutality of the Special Anti-Robbery Squad (SARS) known as the #End SARS protest in 2020. Both provide on-the-ground evidence of the criminalisation of civil activism. In the alternative, this chapter reflects on how transforming democracy can redress state repression and offer a better understanding of civil activism, which can strengthen developing democracies, including addressing questions of political marginalisation, distributive justice, police brutality, inequality, repressive state response and unequal state structure accounting for organised protests.
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Tiantian Gu, Enyang Hao and Lei Zhang
Smart community construction (SCC) and efficiency require resident participation. This paper aims to explore the determinants of residents’ participation intention (RPI) in the…
Abstract
Purpose
Smart community construction (SCC) and efficiency require resident participation. This paper aims to explore the determinants of residents’ participation intention (RPI) in the SCC.
Design/methodology/approach
Based on the theory of planned behavior (TPB), this study proposed an extended conceptual model to deeply analyze the RPI in the SCC. The relationship between all constructs was verified by processing and analyzing online survey data using confirmatory factor analysis (CFA), structural equation model (SEM), and bootstrapping method.
Findings
Participation attitude, perceived behavioral control, subjective norm, and perceived usefulness significantly and positively affected the RPI. Furthermore, intermediary effects in the extended conceptual model had been confirmed.
Originality/value
To fill the critical gap in the research on the determinants of the RPI in the SCC context, this study developed a novel conceptual model by extending the TPB to analyze the effects of self-driven and externally-driven factors on the RPI from the perspectives of residents’ psychology and external environment. The findings not only clarify the complex process of forming the RPI in the SCC but also provide a theoretical foundation for studying the RPI in similar community construction projects. Additionally, several strategies have been proposed to encourage residents’ participation in the SCC and promote the development of smart communities, such as clarifying residents’ participation obligations, improving the convenience services of smart communities, and diversifying residents’ participation approaches.
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Meenal Arora, Anshika Prakash, Amit Mittal and Swati Singh
Despite the extensive benefits of human resource (HR) analytics, the intention to adopt such technology is still a matter of concern in the engineering and construction sectors…
Abstract
Purpose
Despite the extensive benefits of human resource (HR) analytics, the intention to adopt such technology is still a matter of concern in the engineering and construction sectors. This study aims to examine the slow adoption of HR analytics among HR professionals in the engineering and construction sector.
Design/methodology/approach
A cross-sectional online survey including 376 HR executives working in Indian-based engineering and construction firms was conducted. Hierarchal regression, structural equation modeling and artificial neural networks (ANN) were applied to evaluate the relative importance of HR analytics predictors.
Findings
The results reveal that hedonic motivation (HM), data availability (DA) and performance expectancy (PE) influence the behavioral intention (BI) to use HR analytics, whereas effort expectancy (EE), quantitative self-efficacy (QSE), habit (HA) and social influence (SI) act as barriers to its adoption. Moreover, PE was the most influential predictor of BI.
Practical implications
Based on the findings of this study, engineering and construction industry managers can formulate strategies for the implementation and promotion of HR analytics to enhance organizational performance.
Originality/value
This study draws attention to evidence-based decision-making, emphasizing barriers to the adoption of HR analytics. This study also emphasizes the concept of DA and QSE to enhance adoption among HR professionals, specifically in the engineering and construction industry.