Munir Ahmad’s research while affiliated with Dongbei University of Finance and Economics and other places

This study examines the impact of economic growth, energy prices, digitalization, and climate policy uncertainty key macroeconomic, technological, and political factors-on ESG performance in the U.S. within a comprehensive sustainability framework to mitigate climate change. The study reveals how these variables impact different levels of ESG performance using Quantile and Quantile-on-Quantile analyses. Findings show that economic growth positively impacts ESG performance. This can be interpreted as the economy incentivizing U.S. companies to adopt and enhance their ESG practices. No significant impact of climate policy uncertainty was found. This result can be interpreted as companies mitigating the effects of climate policy uncertainty on ESG through hedging and risk management strategies. The positive relationship between energy prices and ESG indicates that higher energy costs may improve ESG performance. This can be explained by the fact that sectors facing high energy prices may invest more in sustainable practices, such as adopting renewable energy. Therefore, policymakers should encourage businesses to take individual and collective action to adopt behavior against climate change. The negative impact of digitalization on ESG performance can be explained by the rapid pace of technological change, leading business companies to prioritize profitability over ESG considerations. This result may refer to the Corporate Sustainability Theory. 1 Therefore, businesses should integrate digitalization into climate strategies through regulatory measures and enhanced corporate reporting.

Climate change is a significant and urgent threat, gaining traction in the scientific community around the globe and requiring immediate action across many sectors. In this context, the digital economy could provide a mutually beneficial solution by utilizing innovation and technical breakthroughs to establish a sustainable future that addresses environmental deterioration, promotes economic growth, and encourages energy conservation. Against this background, this study examined the diffusion of innovation modeling-based factors affecting small and medium-sized firms’ (SMFs) adoption of the Internet of Things (IoT) technology and its impact on SMFs’ sustainability performance related to environmental, economic, innovation, and energy conservation perspectives. The key findings revealed that (i) the relative advantage, trialability, and observability drive IoT adoption. However, compatibility and complexity hinder IoT adoption. (ii) When prioritizing the adoption factors, the relative benefit is the strongest driver, and compatibility is the most significant barrier to IoT adoption. (iii) IoT technology adopter SMFs spent less on natural resources and more on renewable energy and environmental monitoring systems than non-adopter firms, boosting their environmental sustainability. (iv) IoT technology adopter firms had greater revenue, profits, and credit access than non-adopters and lower input costs, improving their economic sustainability. (v) IoT adopter firms spent more on innovative products than non-adopter enterprises, demonstrating innovation performance. (vi) Compared to non-adopter firms, IoT technology adopter SMFs had lower utility expenses and spent more on energy-efficient technologies. (vii) To realize the full potential of the IoT for a more sustainable and inventive future, authorities may pursue a variety of policy actions involving the strengthening and implementation of IoT technology standards and regulations, securing the incentivization of financial resources to SMFs, diverting the allocation of resources to research and development avenues, prioritizing the capacity development and environmental awareness, and focusing on IoT infrastructure development.

The purpose of this research note is to investigate the nexus between volatility in international tourist arrivals, volatility in foreign aids and gross domestic product (GDP) volatility in Cambodia over the period of 1993-2018 by using partial and vector coherence wavelet models. The partial wavelet coherence models show that volatility in tourist arrival has strong impacts on GDP volatility across all time and frequency domains. Secondly, we find from the vector wavelet coherence plots strong and significant coherence between GDP volatility and volatility in overseas development assistance to Cambodia across all time and frequency domains.

This paper aims to analyze the link between environmental degradation and institutional quality and the price of oil moderated by economic complexity and the underground economy. We use quantile regressions with annual panel data for 15 countries in the Middle East and North Africa during 1995–2021. The findings indicate that institutional quality, economic complexity, and output positively and heterogeneously impact environmental degradation. However, the square of production has a negative impact, confirming an inverted U relationship between production and environmental degradation. Likewise, we find that the price of oil and the underground economy have a negative and heterogeneous impact on environmental degradation. Based on our results, a potential recommendation for policymakers is that the institutional framework of Middle Eastern and North African countries should be accompanied by a more significant concern for the environment instead of prioritizing extractive growth that is detrimental to the environment’s environmental sustainability. Likewise, economic diversification will mitigate environmental degradation and improve formal employment. Our findings are relevant to policymakers and researchers interested in promoting ecological sustainability.

Though construction sector development and economic openness contribute to regional economic development, they have also been debated to pose some environmental challenges. Along these lines, we explored the long- and short-term connections of intensive energy consumption, economic openness, and construction sector development with the chemical oxygen demand throughout the scales of regional development of China’s 30 provincial units over the 2004–2021 period. Theoretically, we contribute to the existing knowledge by incorporating chemical oxygen demand pollution, construction sector development, and economic openness to the Kaya identity’s baseline framework. Empirically, we apply a series of advanced methods of panel data econometrics for robust results. Our key findings are as follows: First, we revealed a long-term stable cointegrating association among our variables of interest. Second, using the common correlated effect mean group estimator, we unfolded that the intensive energy consumption showed a chemical oxygen demand pollution reduction influence in both the long and short term, demonstrating the most substantial influence in the high regional development panel while expressing the least powerful influence the least regional development setting. Third, we unveiled that economic openness and construction sector development showed a linear chemical oxygen demand pollution enhancement influence in moderately and least developed regions. Nevertheless, both established an inverted U-shaped linkage with chemical oxygen demand pollution for the whole country as well as for high regional development data samples. Eventually, we found consistent estimates across long- and short-term investigations regarding signs of relationships; however, long-term effects remained more powerful than short-term ones. These findings would serve as factual scientific knowledge to help local as well as national governments create the optimal environmental regulations for the construction sector to achieve the sustainable development goals (SDGs), especially the Climate Action Plan (i.e., SDG-13).

Purpose This article investigates the long-run impact of remittance inflows on agricultural productivity (AGP) in emerging Asian economies (Bangladesh, Sri Lanka, Malaysia, India, Nepal, Philippines, Pakistan, and Vietnam), employing a panel dataset from 2000 to 2018. Design/methodology/approach This study initially applies cross-sectional dependence (CSD), second-generation unit root, Pedroni, and Westerlund panel co-integration techniques. Next, it uses the augmented mean group (AMG) and common correlated effect mean group (CCEMG) methods to investigate the long-term impact of remittance inflows on AGP while controlling for several other important determinants of agricultural growth, such as cultivated area, fertilizers, temperature change, credit, and labor force. Findings The empirical findings are as follows: The results first revealed the existence of CSD and long-term co-integration between AGP and its determinants. Second, remittance inflows significantly boosted AGP, indicating that remittance inflows played a crucial role in improving AGP. Third, global warming (changes in temperature) negatively impacts AGP. Finally, additional critical elements, for instance, cultivated area, fertilizers, credit, and labor force, positively affect AGP. Research limitations/implications This study suggests that policymakers of emerging Asian economies should develop an exclusive remittance-receiving system and introduce remittance investment products to utilize foreign funds and mitigate agricultural production risks effectively. Originality/value This is the first empirical examination of the long-term impact of remittance flows on agricultural output in emerging Asian economies. This study utilized robust estimation methods for panel data sets, such as the Pedroni, Westerlund, AMG, and CCEMG tests.