Panel-corrected Standard Errors Research Articles

Capital mobility, financial development and sustainable trade development in sub-Saharan Africa: a GMM-PVAR based analysis

PurposeThe existing literature on the effects of capital mobility and financial development on sustainable trade development in sub-Saharan African (SSA) countries has been centered on production-based carbon emissions without investigating consumption-based or trade-adjusted carbon emissions. The purpose of this paper is to examine the effects of capital mobility and financial development on sustainable trade development, specifically trade-adjusted carbon emissions in SSA economies.Design/methodology/approachThe study employed the novel GMM-PVAR estimator and the Drisc-Kraay fixed effect panel corrected standard error (PCSE) dynamic ordinary least squares (DOLS) and the fully modified least squares (FMOLS) approaches on panel data from 46 sub-Saharan African (SSA) countries over the period 1992–2021.FindingsThe study established that capital mobility has a significant positive effect on sustainable trade development in SSA in the long run. Further, the empirical results reveal that the link between financial development and sustainable trade development is significantly positive in the long run. Moreover, the results suggest that capital mobility and financial development have predictive power on sustainable trade development.Practical implicationsThe findings of the study imply that policymakers ought to pay equal attention to capital mobility and financial development when developing sustainable trade development policies.Originality/valueThe existing literature has been centered on production-based carbon emissions, without specifically considering sustainable trade development (consumption-based carbon emissions). To the best of our knowledge, this is the first study to examine the effect of capital mobility and financial development on sustainable trade development in SSA countries context.

The Moderating Roles of Economic Complexity in the Entrepreneurship‐Sustainable Environment Nexus for the Gulf Cooperation Council Economies

ABSTRACTThere are conflicting views on the effect of business and entrepreneurial activities on environmental degradation in developing economies. However, none of this study examines whether economic complexity can serve as a policy tool for mitigating the effect of entrepreneurial business activities on a sustainable environment. Economic complexity consists of the structural and economic transformation process from a simple production system to a more complex and innovation‐based one. It predicts the variations in income level and its impact on the choice of goods being produced in an economy. This study examines the moderating effect of economic complexity on the link between entrepreneurship and sustainable environment in Gulf Cooperation Council (GCC) countries from 2006 to 2020. It further examines the validity of the Entrepreneurial Environmental Kuznets Curve (EEKC). The study uses the Driscoll‐Kraay standard error fixed effect, Panels Corrected Standard Errors (PCSE), method of moment quantile regression and Dumitrescu–Hurlin causality that are robust to heteroscedasticity, cross‐sectional dependency and other pitfalls of least square estimating technique. The results validate the inverted U‐shaped EEKC hypothesis across all the quantiles. Economic complexity increases ecological degradation at the lower quantile levels, while it decreases environmental footprint at the upper quantiles. Furthermore, economic complexity moderates the detrimental impact of entrepreneurial activity on the environment at the higher quantiles. A two‐way relationship is established between entrepreneurial activity and the environment, while one one‐way connection from economic complexity to the environment was found. The study recommends that policymakers should encourage innovative rather than necessity entrepreneurs. Entrepreneurs should be encouraged to engage in business activities that are friendly toward preserving the ecological environment, and green innovative activities should be prioritised in their entrepreneurial activities.

Navigating Carbon Peaking and Neutrality in MENA: The Impact of Foreign Direct Investment and Trade Openness Using Panel PCSE and FGLS Techniques

ABSTRACTIn response to the global challenge of climate change and the drive towards carbon neutrality, this study investigates the effects of foreign direct investment (FDI) and trade openness (TO) on carbon emissions (CEM) within the Middle East and North Africa (MENA) region. The research spans 18 countries from 1990 to 2022, focusing on Sustainable Development Goal 13. Utilizing Porter's hypothesis and the Environmental Kuznets Curve (EKC) theory, the study applies quantitative methods including panel corrected standard errors (PCSE) and feasible generalized least squares (FGLS) to ensure robustness. To address potential endogeneity, two‐stage least squares and lagged effect estimations are employed. The findings reveal that both FDI and TO are associated with reduced CEM, indicating positive environmental impacts. Also, the pairwise causality tests show bidirectional causality between FDI, TO, and CEM, while a unidirectional causality is found from industrialization (IND) and energy consumption (EC) to CEM. These results underscore the importance of integrating FDI and TO into strategies for achieving carbon neutrality and advancing sustainable development goals, offering actionable insights for policymakers.

Austrian FDI in Asian economies: Does knowledge capital matter?

PurposeWhile Austrian foreign direct investment (FDI) in Asian economies experiences a rising trend, the following question arises: Why does Austria invest more in certain economies over others? This study intends to assess the factors that drive Austrian investment in Asian economies.Design/methodology/approachBased on the ownership, location and internalization framework and the knowledge capital approach, this study hypothesizes that knowledge capital significantly attracts FDI from Austria. Meanwhile, this study applies the panel-corrected standard error method to analyze data for 11 Asian economies from 1990 to 2022.FindingsAfter considering endogeneity, the results show a positive and significant correlation between expenditure in research and development per gross domestic product (GDP) in the host economies and FDI inflow from Austria. In addition, the study reveals that factors such as market size, trade openness and natural resources in the host economies significantly influence Austria’s FDI, which indicates that Austrian investors fall into the three main FDI typologies: market-seeking, resources-seeking and efficiency-seeking.Originality/valueThis study fills the literature gap by becoming the first to analyze the determinants of Austrian FDI in Asian economies, thus enriching our understanding of Austria’s global investment pattern.

The effect of crop insurance on the financial risk of smallholder rice farmers in Cameroon

This study examined the effect of crop insurance on the financial risk of smallholder rice farmers in the grass field of Cameroon. Panel data from 76 Smallholder rice farming groups from 2019-2022 was used, while the Panel-corrected standard error technique was used for estimation. The results revealed that crop insurance captured using inputs (fertilizers, herbicides, and treated seeds) and land preparation had a positive and statistically significant effect on financial risk. These results validate the risk balancing hypothesis for smallholder rice farmers. Control variables like Farm size and labour had a positive and statistically significant effect, while training cost and buying price had a negative and statistically significant effect on financial risk. The results therefore, indicate that smallholder rice farmers need to adopt crop insurance practices such as use of quality farm inputs and better land preparation techniques in order to manage financial risk.

How the social dimension of ESG influences CEO compensation: Role of CEO and board characteristics

AbstractThis paper examines whether social disclosures impact CEO compensation considering various CEO and board controls. By categorizing CEO‐specific attributes into CEO duality, CEO academic diversity, and insider CEO, as well as including board size and board independence as board‐specific controls, the study tests their effects on CEO compensation. This research further explores whether board gender diversity moderates the association between social disclosures and CEO compensation. The paper uses a balanced panel dataset of 67 firms extracted from the NSE Nifty 100 ESG index and applies the panel‐corrected standard error (PCSE) model as a baseline methodology. The findings revealed that the environmental, social, and governance (ESG) disclosure score significantly impacted the CEO compensation, whereas social disclosure scores assessed independently failed to create a significant association with the same. Subsequent investigation also showed a significant positive relationship between the number of female directors on the board and CEO compensation. However, female directors on the board could not amplify the firm's social disclosure practices, leading to an insignificant impact on CEO compensation. While board independence, board size, ownership structure, and CEO duality significantly affected the above relationship, insider CEO status could not. Furthermore, robustness checks using the propensity score matching (PSM) and generalized method of moments (GMM) models were also conducted to test the validity of the above results. The findings of the work offer insights to help managers, organizations, and policy planners make decisions concerning women directors, social disclosures, and CEO compensation.

Bridging the green gap: Unveiling the complex interplay of national cultural dimensions, management effectiveness and corruption in driving green innovations

The objective of this research is to investigate the relationship between national culture, management score, corruption, and its implication on firms’ green innovation. This paper analyses 2588 firm year data using panel corrected standard errors (PCSE), two stage least regression (2SLS) and Generalized Method of Moments (GMM). This paper also conducts quantile regressions and propensity score matching (probit regression) for the effect of national cultures on country’s corruption. Our initial observation found that national culture of long-term orientation is positively associated with green innovation. But in contrast to earlier findings, green innovation is negatively associated with individualism and indulgence. Nonetheless, when management score is used as a moderating variable for long term orientation national culture, a negative observation is made, likely due to restrictive regulatory compliance, conflict of interest or even inconsistent ideas amongst the management and the employees during the long-term execution of the project.

Empowering rural South Asia: Off-grid solar PV, electricity accessibility, and sustainable agriculture

This study investigates the impact of off-grid solar photovoltaic (PV) systems on electricity accessibility and agricultural sustainability in rural South Asia, employing panel data methodology: least square dummy variable (LSDV) and Lewbel instrumental variable (IV) approach. The findings demonstrate a robust positive association between solar PV adoption and increased electricity access, even when accounting for individual and period-specific factors. Increased electricity access significantly contributes to higher agricultural value added per worker, but not necessarily to the overall share of agriculture in the economy. This analysis also reveals a positive and significant impact of solar PV (SPV) on agricultural value added per worker, independent of rural electrification levels. Heterogeneities across time and context, along with country-specific factors, play crucial roles in shaping these relationships. While factors like government effectiveness and GDP per capita have complex and sometimes counterintuitive effects, access to land, agricultural employment, and capital investments all contribute positively to agricultural sustainability. The Lewbel IV method offers strong impact of SPV on electrification, independent of external factors, and its direct contribution to agricultural output, make it a compelling tool for empowering rural communities and building a more sustainable future in South Asia. Robustness of the result is validated through three approaches: measuring variable averages at three-year sub-periods, applying three-stage least squares (3SLS), and utilizing alternative methods (panel corrected standard errors (PCSE), feasible generalized least squares (FGLS)) to consider various data characteristics. Off-grid solar PV emerges as a game-changer for rural electrification and a catalyst for sustainable agricultural development in South Asia. Governments and development agencies can prioritize investments in solar PV systems to address energy poverty and boost agricultural productivity.

Energy poverty and the green energy transition's impact upon income inequality in Latin America

In this study, we examine the relationships arising from the transition process to green economies and energy poverty in relation to income inequality across 22 Latin American countries during the period from 2000 to 2021. Our estimations are conducted using various estimators for energy poverty and the transition to green economies, employing feasible generalized least squares (FGLS) and panel corrected standard errors (PCSE) to ensure robustness. The results reveal a significant effect of both sets of variables on income inequality. Specifically, energy poverty contributes to higher levels of income inequality, while the ecological transition has the potential to address income inequality issues, provided an effective distribution of renewable energy resources among society is ensured. Failure to achieve equitable distribution of renewable energy resources may hinder the attainment of more egalitarian societies. To address this, a comprehensive set of policies is required to ensure equal access to renewable energy sources for the entire population, along with effective long-term measures that contribute to the equitable distribution of energy resources.

How energy transition and fintech influence income inequality in Sub-Saharan Africa: Evidence from a panel-corrected standard error approach

This study explores the role of financial technology (FinTech) and the energy transition in shaping income inequality across 45 sub-Saharan African economies (SSA). By employing the panel-corrected standard errors approach, the analysis takes into account contextual and institutional factors, as well as regional specificities, for the period extending from 2000 to 2021. This research elucidates the connections among energy transition, FinTech, and income inequality, emphasizing their significance for economic progress and clean energy access. The findings reveal significant inequality in the outcomes of SSA countries, with an average Gini index of 43.197, indicating that most countries are unequal. This study reveals a notable connection between transitioning to renewable energy sources and a reduction in income inequality, with a one-unit increase in the energy transition indicator resulting in a 5.10% decrease in inequality. Moreover, FinTech is also found to contribute to a reduction in income inequality, with a 1.31% decrease observed for every unit increase in the FinTech indicator. The analysis also revealed a weak, yet statistically significant, link between population density and income inequality, with a one-unit increase in inequality of 0.00632%. Notably, industrial value added is found to be an influential factor with a statistically significant coefficient of 0.129. The key implications of the study emphasize the importance of redistributive policies, financial inclusion, and the promotion of renewable energy sources in constructing more inclusive economic systems. Furthermore, the study underscores the significant value of accurate energy production prediction for informed decision-making in energy planning and policy-making on regional and global scales.

Renewable energy, energy efficiency, and economic complexity in the middle East and North Africa: A panel data analysis

This paper aims to investigate how economic complexity and structural transformation affect energy security. This study differs from previous research by focusing on energy efficiency and renewable energy transition as indicators of energy security. The employed methods include econometric techniques such as Panel-Corrected Standard Errors, Driscoll and Kraay's Spatial Correlation Consistent (SCC) method, and Generalized Least Squares, covering data from the Middle East and North Africa (MENA) countries between 1990 and 2017. The results show that economic complexity has a negative effect on energy efficiency but a positive impact on renewable energy. However, economic growth positively affects energy efficiency but negatively influences renewable energy. These results imply that economic complexity is energy-intensive but green, whereas economic growth is energy-saving but brown. The comparative analysis reveals that the negative effects of economic complexity and growth are larger than their positive effects, highlighting the necessity of restructuring economic activities and sectors. Accordingly, decision-makers should encourage the utilization of more energy-efficient technologies in economic activities and production, while promoting renewable energy consumption to enhance energy security in the MENA region.

The economic impact of terrorism in South Asia

This study examines the economic impact of terrorism in South Asia. The region is currently home to 123 active terrorist/insurgent groups and is accountable for over 27 % of recorded global terrorist attacks. The annual data from the six most-terror-affected South Asian countries (Afghanistan, Bangladesh, India, Nepal, Pakistan, and Sri Lanka) during the US-led war on terror (2001 - 2022) is used. For econometric estimation, the five models: fixed-effect, generalized least squares (GLS), generalized estimating equation (GEE), quantile regression (QR), and panel-corrected standard errors (PCSE) are applied. Terror-related death (a proxy for human capital loss) and per capita income (a proxy for purchasing power) are considered to measure terrorism and its economic impact. In addition, four economic indicators (military expenditure, population, official development assistance (ODA), and USAID) and three institutional indicators (electoral democracy index, political violence index, and mobilization for autocracy index) are taken into account as control variables. The result suggests that every additional 886 terror-related human capital loss across the region significantly reduces the purchasing power of each South Asian person by at least 9.800 US dollars. Moreover, among the control variables, military expenditure, political violence, and mobilization for autocracy negatively affect per capita income, while electoral democracy, population, ODA, and USAID positively impact it. This study will also help understand the implications of the United Nations' Sustainable Development Goals (SDGs) agenda and achieving specific targets such as SDG 8 (promoting economic growth) and SDG 16 (promoting just, peaceful, and inclusive societies) based on the most terror-affected region.

Artificial intelligence and wealth inequality: A comprehensive empirical exploration of socioeconomic implications

This study introduces a global database on artificial intelligence (AI) capital stock and related AI indicators. Using the data constructed, we investigate the impact of AI and capital stock accumulation on wealth inequality, a dimension not extensively explored in the literature. This study contributes to the growing body of literature on the socioeconomic consequences of AI, with implications for scholars, policymakers, and corporate executives. An innovative database detailing AI capital stock is developed by incorporating data from various sources, including corporate reports, industry databases, and scholarly literature. This novel dataset, focusing on the US, the EU, and Japan from 1995 to 2020, is a critical resource for future investigations. The research methodology is centered on an extended Solow–Swan model, conceptualizing AI as a form of capital that can substitute for or complement traditional forms of labor. A panel-corrected standard errors model is used to analyze the data, accounting for potential cross-sectional dependence and heteroscedasticity. Our findings reveal a positive and statistically significant correlation between AI technology adoption, AI capital stock accumulation, and wealth disparity. The analysis further indicates a complex interaction between income and wealth disparities, suggesting a mutually reinforcing cycle. This study fills a significant gap in the existing literature by offering a novel perspective on the distributional impact of AI. Our results underscore the importance of considering the broader socioeconomic implications of AI, extending beyond considerations of immediate productivity and economic growth. This study offers valuable insights for policy formulation and business decision making, emphasizing the necessity of a comprehensive understanding of the influence of AI on wealth distribution.

Determinants and convergence of biodiversity or extinction disclosures of mining firms in Africa

This study probes into the biodiversity disclosure practices of mining firms in Africa, the determinants and the evidence of convergence using information economics analysis. Data was sourced from 21 mining firms covering the period 2006 to 2019 operating in Morocco and South Africa with various mine sites owned in other countries like Ghana. Using a combination of panel-corrected standard errors regression, logistic regression and the test of beta and sigma-convergence, the study found that there is a moderate level of biodiversity disclosure across African mining firms and there is both beta and sigma-convergence. The study found that board size enhances disclosures on all biodiversity indicators, viz, biodiversity disclosure index, 304-1 (proximity of sites to biodiversity hotspots) being the most disclosed, followed by 304-3 (habitats protected or restored), 304-4 (IUCN Red List Species) and 304-2 (impact of activities on biodiversity). Generally, board size drives biodiversity disclosures but board independence does not. Additionally, the membership of the United Nations Global Compact, a multistakeholder initiative significantly affects every disclosure indicator. Financial leverage drives the disclosure of 3 indicators. Other factors like firm size, multinational enterprise status, profitability, cross-listing, human capital development, and gross domestic product were explored. The results of the analyses are relevant for practitioners, policymakers, regulators and academics alike.

Causes of Deforestation: Evidence from Top Deforested Countries

This study investigates the causes of deforestation using panel data for top deforested countries from 1995 to 2022. We apply Panel Corrected Standard Error (PCSE) technique. The findings affirm that urbanization and water stress has negative and significant effect on deforestation and unemployment and agricultural exports have positive and significant effect on deforestation. The results of this study serve as the basis for the recommendations presented in the present research strategy such as labour opportunity cost might be increased to reduce agricultural rent. Stabilization and regeneration of the forest cover should be prompted by a greater demand for and a restricted supply of forest products. Labour opportunity cost should be increased to reduce agricultural rent. Stabilization and regeneration of the forest cover should be prompted by a greater demand for and a restricted supply of forest products.

The Interplay of Dietary Habits, Economic Factors, and Globalization: Assessing the Role of Institutional Quality.

Dietary habits are pivotal for population health and well-being, yet remain a pressing global issue, particularly in Sub-Saharan Africa (SSA), where economic instability and institutional challenges exacerbate dietary problems. Despite extensive research, there is a notable gap in the literature regarding the direct and interactive effects of institutional quality and inflationary shocks on dietary habits. This study delves into these complex interplays across 44 SSA nations from 2002 to 2022. Employing an innovative entropy method (EM) and the generalized autoregressive conditional heteroskedasticity (GARCH) modeling, the study introduces an inclusive institutional quality index and an inflationary shock predictor as crucial determinants of dietary habits in the literature. The results from the panel-corrected standard error (PCSE) method and feasible generalized least squares (FGLS) model reveal that per capita GDP, school enrollment rate, government expenditures, globalization index, and urbanization are positively associated with population dietary habits, while inflationary shock, food insecurity, and unemployment rate exert negative influences. Notably, institutional quality acts as a catalyst, amplifying the positive effects of the former group and absorbing the negative impacts of the latter on population dietary habits. Additionally, a dynamic panel causality analysis confirms a bidirectional causality nexus between population dietary habits and all variables, except for inflationary shocks, which demonstrate a unidirectional causality link. These findings carry significant policy implications, underscoring the complex dynamics between institutional quality, inflationary shocks, and dietary habits in the region. The bidirectional causality highlights the need for holistic interventions that address economic, social, and institutional factors simultaneously. Moreover, the unidirectional causality of inflationary shocks on dietary habits suggests that stabilizing inflation is critical to protecting dietary habits. These results provide critical insights for policymakers to design targeted interventions aimed at improving nutrition, bolstering institutional frameworks, and ensuring public health resilience in the face of economic and social shocks.

Greenflation, a myth or fact? Empirical evidence from 26 OECD countries

Among the various effects of the green transition on the macroeconomy, we examined the unintended effects of the green transition on inflation, the so-called “greenflation”. We analyzed panel data from 26 OECD countries covering the period from 2005 to 2019 using four models based on the New Keynesian Phillips curve model. To date, only a few studies have examined greenflation, particularly in terms of empirical investigation. The main contribution of this study to the literature is to provide empirical evidence of greenflation. We also provide empirical evidence on the issues in the NKPC literature that the output gap better explains inflation dynamics than unit labor costs and confirm the demise of the Phillips curve. Estimates from the Common Correlated Effect Mean Group (CCEMG), Augmented Mean Group (AMG), and Panel Corrected Standard Error (PCSE) models indicate that the green transition has an upward inflationary impact on headline inflation, but no significant impact on core inflation. In addition, we have examined four circumstances under which the green transition may affect inflation that have not been sufficiently discussed in the literature: increased green transition spending, carbon pricing, increased demand for critical minerals, and the low energy density of renewable energy. Each of these circumstances has the potential to exert both upward and downward pressures simultaneously. Our suggestion to policymakers is that they do not yet need to change their current view of monetary policy with respect to greenflation, but they should carefully consider policy designs that take into account the unintended effects of the energy transition.

Investigating the Effect of Capital Expenditure and Age on Profitability: A Study of Listed Manufacturing Firms in Bangladesh

The study has been conducted to investigate whether firms’ capital expenditure and age have any impact on profitability. To serve this purpose, around 38 listed manufacturing companies of Dhaka Stock Exchange have been considered. Capital expenditure and age of the business since its commencement have been considered as independent variables where return of assets (ROA) as a proxy for profitability has been considered as dependent variable. To normalize the variability, the study used the natural logarithm of the said variables. To consider the confounding effect, the study also considered five control variables: total assets as proxy for firm size, debt to total assets as proxy for financial leverage, GDP growth as proxy for economic growth, the presence of COVID and one period lag on dependent variable. Based on the results of Hausman test, the study used Random Effect Model. In addition, owing to presence of heteroskedasticity and serial correlation, the study further accommodated Panel Corrected Standard Errors (PCSE) to interpret its findings. The findings of the study suggest that both capital expenditure and age of the firm have positive and significant effect on the profitability of the firms.

The role of environmental tax in guiding global climate policies to mitigate climate changes in European region

AbstractThe purpose of this study is to perform a practical inquiry into the influence of environmental tax laws on the execution of climate‐related financial policies. Our research will assess the effectiveness of environmental tax measures in 23 European countries from 2011 to 2020. The panel‐corrected standard error (PCSE) model and the feasible generalized least squares (FGLS) model are used in the empirical examination of the link between environmental tax laws and the implementation of climate‐related financial measures. This study is based on panel data with cross‐sectional dependence. The results of our estimation highlight the need to improve policy effectiveness by using all four ecological tax indicators. These include total environmental tax revenue, energy tax revenue, pollution and resource tax revenue, and transportation tax revenue. Furthermore, we provide actual evidence clarifying the process by which the implementation of environmental tax policies improves the efficacy of climate‐related financial policies in the short term as well as the long term. According to the findings, a third of environmental tax policy indicators have a long‐term effect on the implementation of climate‐related financial measures, with no short‐term effects seen. Our findings are critical for economists and policy‐makers who support the environmental tax as an effective tool to promote a country's climate policy implementations.

THE DIGITAL ENTERPRISE LANDSCAP: HOW DESI METRICS SHAPE ECONOMIC GROWTH IN THE EU

The European Union’s (EU) economic growth is increasingly driven by digitalization across all areas, including the digital transformation of businesses. This paper explores how the digital transformation of enterprises could influence economic growth in the EU by analyzing data from the Digital Economy and Society Index (DESI) and economic metrics from Eurostat for the post-pandemic period (2021-2022). This paper uses econometric techniques like Panel Corrected Standard Errors (PCSEs) and Robust Regression with Huber Iteration (RRHI) to investigate the cause-and-effect relationships between digitalization and economic factors such as GDP growth rate and real GDP per capita growth. The results show that different digital strategies have varying effects on economic performance. The paper also emphasizes the critical role of real labor productivity in connecting digital transformation with economic performance. The implications of this paper highlight the need for nuanced policy strategies that foster digital skills, improve technological infrastructure and support the Small and Medium Enterprises (SMEs) in their digitalization efforts in order to achieve the ambitious objectives of the EUs Digital Decade. The results also propose a strategic focus on specific technologies that offer immediate economic advantages and enable a stronger incorporation of digital progress across various business operations in the member states.