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The purpose of this study is to investigate the nexus between financial inclusion and human development for countries belonging to different income groups during 2009–2019, and whether this relation differs across these groups.

The paper constructs an index of financial inclusion (IFI) for different income group countries employing dynamic panel data models estimated by generalized method of moments (GMM) to analyse the relation between financial inclusion and human development.

Financial inclusion in low and lower-middle-income countries has higher effect on human development than in high and upper-middle income countries.

The study examines the effect of IFI on the human development index (HDI) at the aggregate level. Future research can tackle the IFI effect on every component of HDI and other aspects of financial inclusion could be incorporated like financial technology.

The originality lies in constructing an index for financial inclusion using the most recent data for a wide range of countries, in addition to examining the impact of financial inclusion on the human development levels of different income groups allowing for more accurate analysis tackling the differences in terms of adopted policies across various income groups; unlike other studies that are carried out on a one country basis or only across one or two country groups that do not allow for comparison across various groups of countries.

Existence of working poverty reduces the effectiveness of the strategy of “increasing employment to reduce poverty”. Developed countries are already concerned about it but insufficient attention has been made by developing countries. Focusing on developing countries this study identifies (1) the effects of trade openness (TO) on working poverty and (2) whether the working poverty trap exists or not in developing countries. Both objectives are also analyzed for three subsamples of low income, lower-middle income and upper-middle income developing countries.

Panel data for 98 developing countries over the period of 2000–2016 have been collected for the study. Fixed effect and GMM methods are applied for static and dynamic analysis, respectively.

The study finds that TO significantly reduces working poverty rate (WPR) (mainly driven up by upper-middle income developing countries). The positive association between WPR with its previous year's rate proves the existence of working poverty trap.

The study's outcome is subject to selected time, countries and methods. Future research should use more improve methods and should identify the channels through which TO could affect working poverty.

Middle income and upper-middle income developing countries should increase TO to reduce the working poverty. Low income developing countries that have the highest working poverty should search the way to derive beneficial effects of trade on working poverty.

Working poverty is not only a developed country issue rather it is a global phenomenon. Hence, it is expected that the study will raise the social consciousness about this phenomenon in developing countries too.

The study fulfills the gaps of identifying the effects of TO on working poverty and existence of in-work poverty trap in developing countries.

This paper provides a state-of-the-art review of the financial development in the Middle East and Central Asia (MECA) and examines its impact on its economic growth.

The authors use a Panel Data Regression Analysis on a sample of 21 countries in MECA for the period 2008–2018.

Using the financial development indices and subindices retrieved from IMF, the study finds that the whole region has a below average index compared to other developing regions. However, this hides a great deal of variation across MECA countries. Surprisingly, financial development does not necessarily contribute to economic growth. It seems that some developing countries are still not predisposed to benefit from financial development due to several obstacles.

The authors recommend policymakers and regulators in MECA to promote financial stability and keep inflation in check so that economic agents can reap the fruits of financial development and foster economic growth. Policymakers should also stimulate competition in the financial sector, build skillful human capital, attract foreign direct investments, strengthen supervision and forensic audit and more importantly reinforce the independence of central banks.

The authors mitigate the shortcomings of single indicators as proxies for financial development by using the IMF Financial Development index that captures the depth, access and efficiency of both financial institutions and financial markets. The authors employ lower-middle-, upper-middle and high-income country groups to test the magnitude of income level on the relationship between financial development and economic growth.

This study aims to contribute to the existing literature by empirically investigating the impact of digital competitiveness and technology on corruption under the moderating effect of some cultural and economic control variables and providing evidence on the links between corruption and various cultural dimensions at the country level.

The cross-sectional sample covers 61 countries (41 high-income and 20 lower-income countries) during the 2016–2020 period, and the analysis was carried out for both the full sample and the subsamples.

The results provide clear evidence supporting the hypothesis that digitalisation and technology significantly affect the perceived level of corruption under the moderating role of cultural framework and economic development. Furthermore, the most significant cultural dimensions of corruption are individualism versus collectivism, uncertainty avoidance, long-term orientation and indulgence versus restraint, even if, in some cases, its influence might be felt differently when the results are estimated on subsamples. Thus, in the case of indulgence versus restraint, high-income countries with higher indulgence scores would register higher scores for the corruption perception index and thus a better control of corruption, while for lower-income countries, the more indulgent these countries are, the weaker the corruption control will be. Furthermore, our results validate a powerful and significant correlation between the index of economic freedom and corruption in both digitalisation and technology.

This study may have relevant implications for policymakers who need to recognise the role of digitalisation and technology in the fight against corruption but considering the cultural and economic characteristics specific to each country.

To the authors' knowledge, the relationship between digital competitiveness, technology and corruption within an economic and cultural framework, while highlighting the differences between high-income and lower-income countries, has not been previously documented in the literature. Thus, this article argues that the level of digital competitiveness and the adoption of technology would significantly impact the level of perceived corruption, although this impact could be felt differently by countries in the high-income category compared to countries in the lower-level income category.

This paper aims to analyse empirically the association between flows of foreign direct investment (FDI), net official development assistance (ODA) inflows and trade-related illicit financial outflows.

With this purpose, a linear model was estimated, using different panel-data estimators, and using a database for a sample of 49 countries spanning the period 2008–2017. The used measure of illicit financial outflows was based on the estimates by Global Financial Integrity of deliberate misinvoicing in merchandise trade.

Research findings show a significant and positive association between changes in both relative lagged net FDI flows and relative FDI outflows (as % of gross domestic product) and changes in the ratio of trade-related illicit capital outflows to total trade. However, these positive associations were only observed in the case of low-income countries. Also, the positive association of net ODA inflows on the IFFT outflows were restricted to the cluster of lower-middle-income countries.

To the best of the authors’ knowledge, this is one of the first studies to empirically estimate the association between FDI and ODA flows and trade misinvoicing at a macroeconomic level. Research findings may contribute to substantiate the concerns expressed in previous research about the potential unintended effects of aid on illicit capital flight in the case of lower-middle-income countries. They also shown that FDI flows could be an additional conduit for trade-related illicit financial flows in these countries

The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?

By specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.

According to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.

This article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).

1. The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

2. We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

3. The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

4. The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

This paper aims to investigate the effects of financial access, financial depth, financial efficiency and financial stability pillars on income inequality and poverty among a panel of sub-Saharan African (SSA) countries.

This paper captures cross-sectional dependence among the income groups through the dynamic common correlated effect approach for a data set of 28 selected SSA countries from 2000 to 2017.

This study reveals that the financial development pillars exert positive and significant impacts on income inequality across the income groups. The results show that the effects of the financial development metrics on poverty are different across the income groups. The results also indicate that the pillars improve poverty reduction for low- and lower-middle-income countries. However, there is a minimal effect on poverty reduction in upper-middle-income countries. The differences among these income categories suggest the need for policymakers to account for income levels when prescribing policies that could engender financial development and poverty reduction in the region.

This paper examines the effects of financial development on both income inequality and poverty by using the newly developed World Bank financial development strategic metrics. It captures cross-sectional dependence in the full sample of selected SSA countries and their income categories.

The study aims to investigate the impact of financial inclusion (FI) on environmental quality and the mediating role of industrialization (IZ). In addition, these relationships among the counties with different levels of income and carbon emissions were also analyzed.

This paper used the International Monetary Fund database for indicators of FI. The environmental indicators were obtained from the World Bank database for a panel of worldwide countries from 2004 to 2019. Separate indices of environmental sustainability (ES) and environmental degradation (ED) were created by using principal component analysis . The generalized method of moments regression was applied to examine the relationship between variables.

The study found full mediation of IZ between FI and ES, whereas partial mediation between FI and environmental degradation. The results were found robust against alternative measures of carbon emissions. Furthermore, the study also bifurcated the sample according to the level of income and carbon emission. It was found that FI plays a positive role in the betterment of environmental quality for high-income countries, while a negative role in upper-middle-income, lower-middle-income and low-income countries. Besides, FI has a negative role in the ES of the countries having higher or lower carbon emission levels.

Empirically this study contributes by creating two different novel measures of ES and environmental degradation, in contrast to other studies that solely relied on carbon emission. Contrary to previous studies, this study suggests that FI is not solely responsible for environmental damages, and IZ is the key channel by which FI shifts its impact on ES. Moreover, for environmental degradation, there are some other channels involved that need to be investigated further. This study has also noted that the relationship between FI and ES is context-dependent. Theoretically, this paper contributes to the literature by using ecological modernization theory in the nexus of FI, IZ and environmental quality.

The authors extend the World Bank's Logistics Performance Index (LPI) for 30 additional countries and 13 additional years. The authors develop an inexpensive method for extending survey data when frequent, universal surveys are unavailable. The authors identify groups of country characteristics that influence LPI scores.

Using data from the World Development Indicators—the broadest global dataset of country socioeconomic features—the authors test machine learning algorithms for their ability to predict the LPI. The authors examine importance scores to identify factors that influence LPI scores.

The best performing algorithm produces predictions on unseen data that account for nearly 90% of observed variation, and are accurate to within 6%. It performs twice as well as an OLS model with per capita income as the only predictor. Explanatory factors are business environment, economic structure, finance, environment, human development, and institutional quality.

Machine learning offers a simple, inexpensive way of extending the coverage of survey data. This dataset provides a richer picture of logistics performance around the world. The factors the authors identify as predicting higher LPI scores can help policymakers and practitioners target interventions.

This paper is one of the first applications of machine learning to extend coverage of an index based on an international survey. The authors use the new data to provide the most wide-ranging analysis of logistics performance across countries and over time. The output is an important resource for policymakers tracking performance, and researchers particularly in smaller and lower income countries. The authors also examine a wider range of explanatory factors for LPI scores than previous work.

This study aims to empirically analyze the symmetries and asymmetries among the critical factors affecting building information modeling (BIM) implementation between countries with different income levels. To achieve that aim, the study objectives are to identify: critical factors affecting BIM implementation in low-, lower-middle-, upper-middle- and high-income countries; overlapping critical factors between countries with different income levels; and agreements on the critical factors between countries with different income levels.

This study identified potential BIM implementation factors using a systematic literature review and semi-structured interviews with architectural, engineering and construction (AEC) professionals. Then, the factors were inserted into a questionnaire survey and sent to AEC professionals in Afghanistan, India, Malaysia and Saudi Arabia. The collected data was analyzed using the following techniques and tests: mean, standard deviation, normalized value, Kruskal–Wallis, Dunn and Mann–Whitney.

Five critical factors overlap between all countries: “availability of guidelines for implementing BIM,” “cost-benefit of implementing BIM,” “stakeholders’ willingness to learn the BIM method,” “consistent views on BIM between stakeholders” and “existence of standard contracts on liability and risk allocation.” Also, the criticality of the factors often differs between income levels, especially between low- and high-income countries, suggesting a significant gap between low- and high-income countries in BIM implementation.

This study differs from prior works by empirically analyzing the symmetries and asymmetries in BIM implementation factors between countries with different income levels (i.e. low-, lower-middle-, upper-middle- and high-income countries).