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This study explores whether ethnic minorities exhibit varying levels of income inequality compared to the host population.

The research leverages a unique immigration event in Italy, specifically the settlement of multiple Albanian groups in southern Italy during the 16th century. This historical occurrence enables an investigation into the role of cultural traits in income inequality, as these groups are situated in the same geographical region and often share borders.

The results, which remain consistent after undergoing various robustness checks, indicate that Albanian villages, while still preserving their identity and tradition, tend to experience an approximately 2% lower level of income concentration compared to similar Italian municipalities.

Our findings aim to provide supporting evidence for future policy considerations regarding the long-term impact of immigration on income inequality.

This paper aims to propose a dynamic stochastic general equilibrium (DSGE) model for the State Bank of Vietnam (SBV) to assess the response from the household sector to monetary policy shocks through the consumption function. Moreover, the transmission from monetary policy to household consumption and income distribution is experimented with through the vector autoregression (VAR) model.

In this study, the authors used the maximum likelihood estimation to estimate the DSGE and VAR models with the sample from 1996Q1 to the end of 2021Q4 (104 observations).

The DSGE model’s results show that the response of the household sector is as expected in the theory: a monetary policy shock occurs that increases the policy interest rate by 0.29%, leading to a decrease in consumer spending of about 0.041%, the shock fades after one year. Estimates from the VAR model give similar results: a monetary policy shock narrows income inequality after about 2–3 quarters and this process tends to slow down in the long run.

Based on the research results, the authors propose policy implications for the SBV to achieve the goal of price stability, and stabilizing the macro-economic environment in Vietnam.

The findings of the study have theoretical contributions and empirical scientific evidence showing the effectiveness of the implementation of the SBV’s monetary policy in the context of macro-instability, namely: flexibility, caution and coordination of different measures promptly.

The manufacturing sector is witnessing the need to continuously improve overall performance by eliminating inefficiencies in the supply chain. The adoption of lean concepts to address wasteful or non-value-adding activities in the supply chain is crucial. This article determines key factors of lean supply chain management (LSCM) for continuous improvement in the manufacturing sector.

The methodology comprises three steps. The first step identifies critical factors of LSCM in manufacturing from prior research and a series of expert consultations. Critical factors are identified and validated that industries can leverage to attain their lean goals. The second step uses the decision-making and trial evaluation laboratory (DEMATEL) method to determine the causal relationship among the factors. DEMATEL analysis categorizes factors into cause and effect, which will assist industry personnel in decision-making. The third step involves further data analysis to visualize the importance of the most critical factors. It develops a machine learning (ML) model in the form of a decision tree that helps in assessing the factors into cause or effect groups via a threshold value of expert ratings.

IT tools, JIT manufacturing and material handling and logistics form the most critical factors for LSCM implementation.

The analysis from DEMATEL and ML together will be beneficial for manufacturing practitioners to improve the supply chain performance based on the identified factors and their criticality towards LSCM implementation.

This paper investigates the impact of microfinance on poverty gap which is the shortfall in income or consumption expenditures below $1.90, $3.20 and $5.50 per day. The paper’s primary goal is to investigate how microloans have impacted the severity of poverty and influenced the cost of poverty eradication in Latin America, empirically evaluate these effects and offer appropriate policy recommendations.

This paper used panel data for 13 Latin American countries from world bank spanning the period 2001–2019 and Fully Modified Ordinary Least Squares model for heterogeneous cointegrated panels. This study used Gross Loan Portfolio per active borrowers, gross domestic product per capita, Gini index, Inflation and Unemployment rate as independent variables and poverty gaps as dependent variables.

Poverty gaps narrow as the loan per borrower increases, and the degree of effect differs with the poverty line, with the magnitude increasing as the poverty line falls, underscoring microloans as an effective tool in closing poverty gaps and lowering the cost of poverty eradication. Growth of GDP per capita is helpful reducing the poverty gap, especially for the less poor of the poor. Inflation and unemployment have no to little impact on the severe poverty gaps, but they start to matter when the poverty line is $5.5 per day. Finally, income distribution inequality widens the poverty gap regardless of the poverty line used.

This study suggests several implications. For example, Latin American nations need to embrace tangible policies that encourage economic growth while reducing inequalities in income distribution to effectively eradicate poverty. More supportive environment is necessary to increase the effectiveness of microfinance operations, particularly for the poorest populations. Microfinance institutions need to set less stringent conditions for loan accessibility and repayment schedules that are commensurate with different levels of poverty. Finally, strengthening microfinance as a strategic policy to gradually close poverty gaps and reduce the cost of poverty eradication.

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

This study investigates how enhancing information and communication technology (ICT) affects female economic participation in sub-Saharan African nations.

Three female economic participation indicators are used, namely female labour force participation, female unemployment and female employment rates. The engaged ICT variables are fixed broadband subscriptions, mobile phone penetration and Internet penetration. The Generalized Method of Moments is used for the empirical analysis.

The following main findings are established: First, there is a (1) negative net effect in the relevance of fixed broadband subscriptions in female labour force participation and female unemployment and (2) positive net effects from the importance of fixed broadband subscriptions on the female employment rate. Secondly, an extended analysis is used to establish thresholds at which the undesirable net negative effect on female labour force participation can be avoided. From the corresponding findings, a fixed broadband subscription rate of 9.187 per 100 people is necessary to completely dampen the established net negative effect. Hence, the established threshold is the critical mass necessary for the enhancement of fixed broadband subscriptions to induce an overall positive net effect on the female labour force participation rate.

This study complements the extant literature by assessing how increasing penetration levels of ICT affect female economic inclusion and by extension, thresholds necessary for the promotion of ICT to increase female economic inclusion.

This paper investigates whether and to what extent operating in inner areas affects the profitability of innovative Italian small and medium-sized enterprises (SMEs) over 2012–2018.

Guided by the National Strategy for Inner Areas and the “Investment Compact,” this study distinguishes between inner and core innovative SMEs. It employs various econometric models to estimate a regression for the return on assets of SMEs, differentiating between firms operating in inner and non-inner areas of northwest, northeast, centre and south Italy.

Findings reveal that innovative SMEs in inner areas generally exhibit lower profitability compared to those in non-inner municipalities. However, huge heterogeneity in results is observed across the country. Specifically, innovative SMEs in the inner areas of the south register lower profitability than those operating in non-inner zones. Conversely, innovative SMEs located in the inner municipalities of northwest and northeast Italy show higher profitability than their peers in non-inner areas. The results imply that targeted policies for inner areas are crucial. However, due to the diversity of local impacts, a differentiated approach, depending on the geographic context, is necessary.

The study aims to explore the relationship between inner areas and the performance of innovative SMEs in Italy. More precisely, it examines the effect of operating in a municipality located within an inner area on the profitability of innovative SMEs. This issue has been overlooked in existing literature. Importantly, we aim to determine whether there is a heterogeneous impact based on geographical localisation, specifically in the Northwest, the Northeast, the Centre and the South of the country. Therefore, this paper contributes to the literature by investigating the factors influencing the performance of innovative SMEs and suggesting new policy recommendations for developing inner areas in Italy.

This paper investigates one of the potential costs of rising segregation in American cities by evaluating empirically the extent at which ethnic-based segregation contributes to the onset and the speed of propagation of the COVID-19 pandemic.

Regression analysis based on matched data on early incidence of COVID-19 cases, segregation and covariates. Identification resorts on variations in segregation across MSAs and heterogeneity in the geography and timing of stay-at-home orders.

One cross-MSA standard deviation increase in segregation leads to a significant and robust rise of COVID-19 cases of 8.7 per 100,000 residents across urban counties.

Combines spatial data on COVID-19 cases and segregation; use of a new segregation measure; focus on early incidence of the pandemic and its drivers.