Search results

The paper assesses the role of natural resource rents in Nigeria's economy through the channel of institutional quality.

The analysis is done with the use of autoregressive-distributed lag (ARDL) bounds testing approach to cointegration, vector error correction model (VECM), Granger causality test and cointegrating regression over the period 1996–2019.

Findings support the notion that overreliance on natural resources could exacerbate the growing number of dysfunctional economic outcomes in the country. The study confirms that a mix of weak governance quality and natural resource rents could have a negligible effect on economic growth and possible retardation impact on the economy in the long run as well as in the short run. The evidence further reveals that there is unidirectional causality running from the interaction term to growth, suggesting that growth trajectory could be jointly determined by natural resource rents and the quality of institutions.

The divergent arguments associated with the mechanisms of resource curse in each of the resource-rich countries offer ample support for the contention that economic outcomes in resource-abundant states may not be a product of resource windfalls per se, but rather the quality of governance or ownership structure. Hence, the ultimate aim of the analysis is to further understanding on the link between resource rents and growth in Nigeria via governance channel.

This paper aims to test the causal relationship between urban-biased policy and urban-rural income gap and further examine the moderating role of government intervention.

Based on the provincial Government Work Reports and the long-term policy practice of implementing the target responsibility system, the authors construct a unique indicator of urban-biased policy in China. Further, applying the panel data of 30 Chinese provinces in 2003–2018, the authors explore the causal relationship between urban-biased policy and urban-rural income gap.

The results show that urban-biased policy has contributed to the widen urban-rural income gap in China, which supports Lipton's urban-biased hypothesis. Further research shows that the stronger the government intervention, the bigger the role of urban-biased policy in widening urban-rural income gap.

On the one hand, this study not only investigates the direct effect of urban-biased policy on urban-rural income gap, but also examines the moderating effect from the perspective of government intervention, which helps to enrich the relevant studies of urban-biased theory. On the other hand, the authors' findings provide the latest empirical evidence for urban-biased policy to widen urban-rural income gap and presents a reference and warning for China and other developing countries about balancing the relationship between equity and efficiency during economic development.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

This study examines the non-linear effect of board independence on the investment efficiency of listed firms worldwide. This study further tests whether the COVID-19 pandemic, industry competition and economic development influence the relationship between board independence and investment efficiency.

The data are retrieved from the Thomson Reuters (Refinitiv) database and include international data from 33 countries, comprising 21,363 firm-year observations. The authors' regression analyses include firm-specific variables as controls that may impact investment efficiency. The authors also perform various robustness tests including, alternative measures of investment efficiency, weighted least squares regression, quantile regression and endogeneity issues.

The results reveal a non-linear relationship between board independence and investment efficiency. Specifically, the relationship follows a U-shaped pattern, indicating that the negative impact of board independence on investment efficiency becomes positive after it reaches its optimal point, thus supporting optimal board structure theory. Interestingly, the authors find no significant evidence of board independence’s effect on investment efficiency during the pandemic. In contrast, the relationship between board independence and investment efficiency is significant only during the non-pandemic period. Furthermore, the authors discover evidence of a U-shaped relationship in both emerging and developed markets, as well as in industries with high and low competition.

The authors' study discovers new evidence on the non-linear impact of board independence on investment efficiency, which has not been explored previously in existing research.

This study has practical implications for investors by emphasising the importance of corporate governance and the appointment of independent directors. Investors should consider the findings of this study when making decisions related to corporate governance, as they can impact a firm's investment efficiency.

Despite a considerable body of literature exploring the link between corporate governance and investment effectiveness, there is a dearth of research on the non-linear effects of board independence. Furthermore, the effects of the COVID-19 pandemic, industry competition and economic development remain unexplored.

The research objective was to check the impact of industry 4 (I4) technologies on environmental sustainability (ENS) with the mediating role of green supply chain management (GSCM) of textile companies in Saudi Arabia.

Data was collected from those respondents who were linked with management and also have knowledge of I4 technologies. The researchers distributed 500 questionnaires among respondents for data collection, 350 questionnaires were received, and used for analysis. The researchers employed the quantitative research approach and cross-sectional research design.

The results indicate that I4 has a positive effect on ENS and GSCM practices except for green purchasing where I4 has an insignificant impact on green purchasing. On the other hand, GSCM practices also significantly mediate between I4 and ENS except for green purchasing which has an insignificant mediating effect.

This study has a great theoretical contribution to literature as it provides strategic insight to managers as well as policymakers. From the perspective of resource-based view, this study is supportive to use I4 technology practices in GSCM. Furthermore, the current research suggests managers to implement I4 technologies and adopt the GSCM practices. These practices should be part of environmental strategies. The implementation of these practices will assist in building a strong reputation and satisfaction of customers and to fulfill the requisites of stakeholders.

The research was conducted with the extended framework of the mediating effect of GSCM between I4 and ENS of Saudi Arabia textile companies which are considered to be a pioneer study in the extant literature.

This study examines the differences in the economic stimulus effects, transmission mechanisms, and output multipliers of government consumption, government traditional investment, and government science and technology investment.

This study constructs and estimates a New Keynesian model of endogenous technological progress embedded in the research and development (R&D) and technology transfer sectors. Using Chinese macroeconomic time series data from 1996 to 2019, this study calibrates and estimates the model and analyzes the impulse response function and a counterfactual simulation of expenditure structure adjustment.

The results show that compared with the traditional dynamic stochastic general equilibrium (DSGE) model, the endogenous process of technological progress amplifies the impact of government consumption shock and traditional government investment shock on the macroeconomy, leading to greater economic cycle fluctuations. As government investment in science and technology has positive external spillover effects on firm R&D activities and the application of innovation achievements, it can promote more sustainable economic growth than government consumption and traditional investment in the long run.

This study constructs an extended New Keynesian model with different types of government spending, which includes endogenous technological progress within the R&D and technology transfer sectors, thereby linking fiscal policy, business cycle fluctuations and long-term economic growth. This model can study the macroeconomic impact of fiscal expenditure structure adjustment when fiscal expansion is limited. In the Bayesian estimation of model parameters, this study not only uses macroeconomic variables but also adds a sequence of private R&D investment.

The purpose of this study is to check the impact of financial development on green technological innovation (GTI).

The sample size includes the 20-year (2001–2020) financial statistics of six Gulf Cooperation Council (GCC) region countries. To check the proposed relationship, this research uses a series of econometric models including fixed effect, fully modified ordinary least square and robust least square models.

The statistical results imply that financial sector development has a direct significant impact on GTI. A developed financial sector can uplift green technological development by offering more loans to industrial sectors and the import of modern technology. The statistical analysis further reveals the positive impact of gross domestic product (GDP), foreign direct investment inflow and trade volume while the negative impact of resources contribution on GTI.

The findings suggest key policy suggestions regarding the role of the financial sector in promoting GTI in the GCC region.

The novelty of this study lies in its examination of the relationship between FD and GTI in the GCC countries, a region with its unique economic and environmental dynamics.

The purpose of this study is to construct a new index to assess the impact of an energy price shock on macroeconomic indicators of India. This paper also shows a comparative analysis of the constructed index along with pre-existing World Bank and International Monetary Fund indices on energy.

This paper uses three vector autoregressions and compute the long-term impact of the indices on the considered macroeconomic variables through impulse response functions.

This paper finds that an energy price shock has a detrimental impact on the macroeconomic indicators of India in the long run. This study also finds that the constructed index acts as a relatively more sensitive index in comparison to the International Monetary Fund and World Bank indices, which is bespoke to a developing economy case. This sensitivity is ascribed to dynamic weighting for a different basket of energy components, which are more pertinent to an Indian context.

The novelty of this research lies in the construction of a new index and its comparison to the existing ones. This study justifies why a developing economy would require a different measure of energy as opposed to the existing indices.

This study aims to explore how subsidiary capabilities collectively configure for performance. Additionally, it seeks to examine whether these configurations of capabilities can provide equifinal solutions through developing a comprehensive research framework that focuses on subsidiaries in China.

With a data set collected through a questionnaire from 172 Korean multinational enterprises (MNEs) in China, this study used a fuzzy-set qualitative comparative analysis to detect the capability conditions and configurations. These configurations represent combinations of various subsidiary capabilities linked to high performance.

This study identified several complex pathways with distinct configurations for high subsidiary performance. The findings demonstrate the importance of configurations over individual conditions. Thus, the results highlight that the effectiveness of diverse capabilities, which are widely believed to singularly contribute to the high performance of MNE subsidiaries, depends on how each combines with other capabilities. Overall, the findings provide a richer and fine-grained understanding of the role and relative importance of various forms of MNE subsidiary capabilities and how the joint effect of these subsidiaries contributes to high performance.

This study suggests that MNE managers should comprehensively understand how subsidiary capabilities are configured to produce subsidiary performance outcomes. This specifically illustrates the importance of understanding the mutually conflicting yet collectively exhaustive results of multi-selective solutions and aims to align with China’s industrial and regional heterogeneity.

By examining the role of MNE subsidiary capability configurations, which may collectively influence the subsidiary’s performance, this study contributes to the literature. It elucidates how MNE subsidiaries may achieve superior performance by developing and possessing various capabilities tailored to the local context.

The study explores the evolution of Indian domestic electronics manufacturing post-economic reforms and also investigates the lack of natural growth stages among Indian start-up/SME electronics manufactures.

The theoretical framework is inspired by Dawar and Frost's survival strategy theory that local companies may follow to overcome competitive threats from MNCs. The study adopts a qualitative methodology, more precisely, a phenomenological approach to walking through policy/regulatory reforms amid market distortions, technological gaps and colonial mindset from the perspective of Indian domestic electronics manufacturers. The study has adopted Gioia method of data analysis to inductively suggest a few research propositions.

The phenomenological approach revealed eight essential structure (essence) narratives to explore the complex issue that plague the industry: make in India, made in India, preferential market access strategy, equitable market access strategy, blue ocean strategy, competitive positioning strategy, technical capability and importance of policy/regulatory arbitrage.

The situation of Indian electronics manufacturing units is comparable to the bonsai tree situation, where natural evolution in business stages does not exist; they are born and die as start-ups/MSMEs. The study advocates for equitable market access by removing market distortions. The long-term solution may lie in making available locally manufactured products as a dependable alternative to the imported products or produced locally by MNC OEMs in terms of cost, quality, technology, volume, after-sale service and integrated supply chain.

While the favorable FDI policies, digital India and make-in India initiatives have strengthened domestic electronics production, it is yet to significantly impact India's position in global trade, including manufacturing and exports.