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This paper focuses on three key metrics of poverty, income distribution and employment to ascertain the pro-poor and inclusive-growth position of the western African region. The roles of governance structures and their interactive effects are also accommodated to capture the peculiarity of the region.

The paper employs fixed and dynamic models.

Evidence suggests that growth is pro-poor, although virtually all governance indicators are sterile in stimulating poverty reduction. The authors observe that health and education spending coupled with trade-openness stimulate pro-poor growth potentials, whereas conflicts culminate the pervasiveness of poverty in the region. By empirically answering the question of how inclusive is economic growth through the lens of income-distribution and employment, the authors show that growth has been exclusive as per-capita-GDP growth rather dampens income shared by the poorest 20%. Also, it is observed that growth has not been inclusive as the jobless-growth argument remains valid while high inequality further exacerbates unemployment in the region. It is further shown that governance has been generally weak in propelling inclusive growth except where the institutional-component of governance stimulates inclusive growth through improvement in equality and labor employability.

The study jointly examines the metrics of poverty, income distribution and employment to ascertain growth pro-poorness and inclusivity which are key for the achievement of African-union (AU) agenda 2063. The study captures cross-sectional dependence among selected countries which previous studies ignored.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

Achieving sustainable development goals (SDGs) demands mobilising finance and aligning it with elements of sustainability. This study, thus, aims to investigate the impact of financial development of an economy on the achievement of SDGs.

The authors analyse a sample of 35 Asian countries based on their SDG trends and representative SDG indicators. An ordered probit model is employed for analysing the impact of financial development on the SDG trend. Subsequently, pairwise Granger causality test is employed for investigating the causality between the SDG and the financial development.

The findings indicate that financial development positively impacts the progress towards SDG achievement in the areas: (1) gender equality, (2) economic growth, (3) industry, innovation and infrastructure and (4) sustainable cities and communities; and adversely impacts the climate action. The causality test indicates a bidirectional causality for financial development and industry, infrastructure and innovation, financial development and sustainable cities and communities and financial development and climate action, and unidirectional causality from gender equality to financial development.

The findings have implications for the government of a nation as well as the private businesses. The goals allow businesses to implement well-articulated strategies which pay attention to the SDGs.

The novelty of the paper is that the authors provide evidence supporting the view that focusing on building a resilient and robust financial system is of importance for the achievement of SDGs.