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This research aims to systematically compare the impact of macro drivers on labor efficiency (LEFF) in high and low trade openness economies, employing the Solow model as the theoretical framework.

This study examines the influence of macro drivers on LEFF from 1995 to 2020, employing advanced panel regression methods such as stepwise regression (SR), fully modified ordinary least squares (FMOLS) and panel OLS. It utilizes Pedroni and Johansen co-integration tests to assess long-term dynamics and Granger causality tests to explore causal relationships between macro drivers and LEFF.

The results reveal both long-term and short-term relationships between LEFF and the macro drivers: gross capital formation (GCF), per capita income (PCI), foreign direct investment (FDI), trade openness (TOP) and gross national savings (GNS). The findings show that these macro drivers positively and significantly influence LEFF in both high and low TOP economies. Specifically, FDI, PCI and GNS have a more substantial positive impact on LEFF in low TOP economies, while GCF and TOP have a greater influence in high TOP economies. Furthermore, in high TOP economies, FDI, TOP and PCI exhibit a unidirectional relationship with LEFF, while GNS and GCF show a bidirectional relationship. In low TOP economies, all five macrodrivers exhibit bidirectional relationships with LEFF.

This research focuses on countries with high and low TOP, limiting the generalizability of its findings to other economic systems due to the unique trade, institutional and governance frameworks of these two distinct groups.

To the best of the authors’ knowledge, this study is the first to compare the impact of theoretical macro drivers on LEFF across groups of countries differentiated by their degrees of TOP (high and low).

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

This study aims to investigate the impact of extensive board diversity on firm performance from the perspective of resource-based view (RBV) theory in the context of Pakistan.

The analyses are made using a panel random-effects model and generalized method of moment (GMM) across 188 non-financial firms listed in the Pakistan Stock Exchange (PSX) over the period of 2009–2020. The robustness of findings is checked through alternative measurements of the variables and alternative estimation techniques.

The results show that board members' nationality, ethnicity and educational level diversities are significantly positively related to firm performance. In contrast, age and educational background diversities negatively affect firm performance. However, gender and tenure diversities have an insignificant relationship with firm performance.

This study is conducted in the context of Pakistani firms; thus, the findings may not be generalizable to other economies because different economies have different institutional settings and governance structures.

The policy-makers should encourage the inclusion of board members' nationality, ethnicity and educational level diversities having relevant educational backgrounds to improve firms' competitive performance. The suggested structure of the corporate board may improve firm performance by attracting multiple stakeholders and fulfilling their expectations.

The appointment of a director should be based on merit rather than on political connections or personnel relationships to improve social welfare and avoid their negative impact on firm competitive performance.

To the best of the authors' knowledge, this is the first study that investigates the impact of board diversity on firm accounting-based performance and market-based performance in the emerging economy of Pakistan. This study uses RBV theory to provide a unique corporate governance structure based on board diversity, particularly in Pakistan.

This paper aims to examine the influence of financial inclusion (FI) on poverty, income inequality and financial stability from the perspective of public good (PG) theory in developing countries.

This study applies the fixed effects model (FEM), pooled ordinary least square (OLS) regression and generalized method of moment (GMM) across panal data of 69 developing countries from 2002 to 2020 inclusive.

Multiple regression analyses show that FI reduces poverty and income inequality while improving financial stability. Secondary enrolment ratio, GDP per capita, and trade openness reduce poverty and income inequality. However, a higher inflation rate increases poverty and income inequality while reducing financial stability. Finally, age dependency ratio and population do not affect poverty, income inequality or financial stability.

The regulators and policymakers in developing countries should raise the level of formal FI by expanding the size of the formal financial sector and improving the access of the large unbanked population to financial products/services. Improving FI enables the unbanked population to take over productive activities and ease consumption, which in turn complementing economic growth.

The increase in FI enables the developing countries to include the financially excluded population through formal financial products and services, which improve financial stability and eradicate poverty and income inequality in society. Thus, the FI enhances the social welfare of society.

This is the first study that examines the impact of FI poverty, income inequality and financial stability in the context of developing countries. This study contributes to the theoretical implications of the PG theory by examining the influence of FI on poverty, income inequality and financial stability in the context of developing countries.