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The purpose of this paper is to test the impact of financial development (FD) indicators, namely banking and stock market (SM) indicators, on the household final consumption expenditure as a poverty index.

The authors study an international sample of 138 countries over the period 1980-2014. A series of estimation methods are used on different measures of bank-based and stock-based FD. Subgroups of countries, namely low, middle, upper-middle and high-income countries are also investigated.

In the study, the authors concluded that FD fails to reach the poorest segments of each society in the international sample. For the selected subgroups of countries, the authors concluded that the impact of the bank and the SM indicators, on the poorest population segments, changes depending on, the estimated FD variables, the selected group of countries and the adopted estimation technique.

The present study recommends appropriate economic and financial reforms, with focus on the roles of banks and SM roles to reduce poverty and stimulate channels that allow the poorest population to exploit from financial services.

This paper is the first of its kind to empirically examine, separately, the impact of banks development and SM development, on an international panel and subgroups of countries, using modern econometric techniques.

This paper examines the impact of financial inclusion on poverty through access to mobile money in developing economies.

The authors employ the principal component analysis to construct an index of financial inclusion using demand and supply indicators, including mobile accounts. The authors use the two-step system GMM estimator for the analysis because of its efficiency and robustness in addressing heteroscedasticity and autocorrelation.

The main finding is that financial inclusion generally increased and significantly reduces poverty in the sample period. Furthermore, income inequality worsens poverty.

This study has few limitations. First, the empirical analysis of the study is restricted to macroeconomic factors only because of limited Household Finance Survey data set and time availability. Second, the study is limited to developing countries and the results cannot be generalized.

Financial inclusion is a significant policy tool for poverty reduction. There is the need to enhance strategies that further improve financial inclusion by expanding and improving the use of mobile money accounts.

The paper sheds light on how developing countries can harness financial inclusion to reduce poverty.

The paper differs from the previous studies in two ways. Firstly, mobile money account is included in the computation of financial inclusion index over the sample period. It also determines the impact of financial inclusion on poverty for short-run and long-run periods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0690

Nowadays, informed decision-making is catching up. Technological advancements and computing ability further fuel and facilitate this tilt toward informed decision-making. In such a scenario, data is cynosure. Therefore, the ability to gather data by a nation (incredibly accurate public data) becomes equally important and relevant, as measured by statistical performance indicators (SPI). This study aims to explore the association of financial inclusion (FI); environmental, social and governance (ESG); poverty; and SPI.

The panel data of 140 nations for nine years are gathered to explore the association of FI, ESG and poverty with the SPI. Panel data estimation is conducted to arrive at the results.

The findings of this study highlight mixed outcomes for FI. ESG is positively associated with SPI, but poverty is not associated with SPI. These findings imply that an increase in FI may reduce the statistical capacity of the nations. An increase in ESG increases the capacity. However, change in poverty does not influence the SPI. The recommendation based on this study’s outcome suggests auditing the FI and poverty vis-à-vis SPI to ensure SPI’s veracity and robustness in the long run.

The way in which the individual social, economic and environmental indicators influence the SPI needs to be tested to establish the veracity and robustness of the SPI, which is barely researched as observed in the literature.

This paper is a study on child poverty from two perspectives: child income poverty (derived from family income) and child deprivation (evaluated by non‐monetary indicators). On the one hand, empirical evidence supports the thesis that income‐based poverty measures and deprivation measures do not overlap. On the other hand, the relationship between poverty and the child's living conditions is not linear. Uses micro‐econometric techniques to analyse child income poverty and present deprivation indicators, and thereby an index of child deprivation, to study child poverty. The measurements used are centred on the child. The results obtained support the thesis that the study of child poverty differs whether the focus is on the child or on the family.

Background: Rising food bank usage in the UK suggests a growing prevalence of food insecurity. However, a formalised, representative measure of food insecurity was not collected in the UK until 2019, over a decade after the initial proliferation of food bank demand. In the absence of a direct measure of food insecurity, this article identifies and summarises longitudinal proxy indicators of UK food insecurity to gain insight into the growth of insecure access to food in the 21st century.

Methods: A rapid evidence synthesis of academic and grey literature (2005–present) identified candidate proxy longitudinal markers of food insecurity. These were assessed to gain insight into the prevalence of, or conditions associated with, food insecurity.

Results: Food bank data clearly demonstrates increased food insecurity. However, this data reflects an unrepresentative, fractional proportion of the food insecure population without accounting for mild/moderate insecurity, or those in need not accessing provision. Economic indicators demonstrate that a period of poor overall UK growth since 2005 has disproportionately impacted the poorest households, likely increasing vulnerability and incidence of food insecurity. This vulnerability has been exacerbated by welfare reform for some households. The COVID-19 pandemic has dramatically intensified vulnerabilities and food insecurity. Diet-related health outcomes suggest a reduction in diet quantity/quality. The causes of diet-related disease are complex and diverse; however, evidence of socio-economic inequalities in their incidence suggests poverty, and by extension, food insecurity, as key determinants.

Conclusion: Proxy measures of food insecurity suggest a significant increase since 2005, particularly for severe food insecurity. Proxy measures are inadequate to robustly assess the prevalence of food insecurity in the UK. Failure to collect standardised, representative data at the point at which food bank usage increased significantly impairs attempts to determine the full prevalence of food insecurity, understand the causes, and identify those most at risk.

The purpose of this paper is to examine the impact of microfinance programs sponsored by Sudanese microfinance institutions (SMFIs) on monetary poverty reduction in Sudan where poverty is widely spread.

The study adopted the control group approach, where income and expenditure are taken as welfare indicators. The updated World Bank’s international poverty line of 1.90 per person per day was adopted to separate the poor from non-poor. The data were collected by the means of a questionnaire distributed to a random sample of beneficiaries in the institution under study. The study adapted the Foster, Greer and Thorbecke (FGT) model to evaluate the role of microfinance programs in poverty reduction. Furthermore, to gain more insight into the impact of the program, a preliminary analysis was conducted using the independent-samples t-test to examine the difference in the welfare indicators for the sample of the control group and treatment group as well as that of the small loan group and micro-loan group.

The findings show that the microfinance program provided by SMFIs has reduced the monetary poverty among the participants. The results also reveal that beneficiaries who had received a larger volume of loan were noted lesser poverty than those who had received very small loan size. Moreover, the results demonstrate that poverty indices based on expenditure as a welfare indicator are far lower than those based on income for both groups.

This study contributes to the available literature by filling the gaps through including income and expenditure as monetary variables, which included separately in previous studies adopted the FGT model in the area of microfinance, in addition to exploring the role of loan size in the effect of microfinance on poverty reduction.

In recent years, there is growing recognition of the importance of geography and space in the analysis of economic convergence by focusing on the dynamics of monetary indicators. The analysis of spatial convergence based on socio-economic indicators are rare. These variables present a complement to understand the spatial dynamics of territorial units. The purpose of this paper is, first, to analyzes and describes trends in multidimensional poverty in Morocco and second it explores the convergence hypothesis.

Data are driven from HCP (2017). It concerns 75 provinces over the period 2004 and 2014. In addition to the availability of data, this period corresponds to significant changes in public policy. The nature of the observations necessitates the use of the spatial analysis techniques.

The results show that poverty is a geographical phenomenon with low speed of convergence. The paper propose some solutions to help policymakers implement an effective targeting policy aimed at reducing spatial inequalities in terms of multidimensional poverty in Morocco.

The analysis of spatial convergence based on socio-economic indicators are rare. This paper will focus on the convergence of the poverty index for a developing country.

The authors estimate the reduction of electricity poverty in Vietnam. The essential argument is that human development is about subjective feeling as much as technology and income.

The authors use a self-reported satisfaction indicator as complementary to objective indicators based on national household surveys from 2008 to 2018.

In 2010, the fraction of households with access to electricity was over 96%. However, over 24% declared their electricity use did not meet their needs. Since 2014, the satisfaction rate is around 97%, even if 25% of the households used less than 50 kWh/month. Today there is electricity for all in Vietnam, but electricity bills weigh more and more in the budget of households.

The subjective energy poverty measure allows better international statistics: unlike poverty or needs-based criteria, self-assessed satisfaction of needs compares across income levels and climates.

Inequalities in electricity use among Vietnamese households decreased during the 2008–2018 period, but are not greater than inequalities in income, contrary to the findings of Son and Yoon (2020).

Engineering and econometric objectivist approaches dominate the literature on sustainability monitoring. Out of 232 sustainable development goal (SDG) indicators, only two are subjective. Yet the findings show that subjective indicators tell a different part of the story. Access is not grid building, but the meaningful provision of electricity to satisfy the needs.

Italy has become a migrant receiving country and it has to face with the problem of social inclusion of immigrants. The purpose of this paper is to measure the gap on poverty and deprivation between immigrants and natives since manifest conditions of both of them are an important signal, although not exclusively, of social exclusion.

Poverty analysis typically relies on a single monetary variable such as income and it is characterized by a simple dichotomization of the population into poor and non-poor. In this paper the authors stress the importance of using a multidimensional and fuzzy approach in order to study disparities between immigrants and natives. The authors cover several of the multifaceted aspects of resources necessary to maintain adequate living standards in a developed country. With the fuzzy methodology, the authors also overcome any limitation of the conventional approach based on the simple dichotomization of the phenomenon.

The empirical analysis is based on data from two official surveys. The authors find that between Italian and immigrant households there are significant differences in poverty and deprivation levels, with a strong disadvantage for the latter. The authors argue that any serious attempt to reduce poverty and deprivation must now include comprehensive reforms in the nation's immigration policies if they are to be taken seriously.

The paper makes an original contribution to the understanding of inequality between immigrants and natives, by studying a complex phenomena such as poverty and deprivation in a multidimensional perspective using a fuzzy approach.

The purpose of this paper is to analyze the effect of the different components of off-farm income on multi-dimensional poverty. Furthermore, the study aims to measure multi-dimensional poverty and also identify the determinants of multi-dimensional poverty in Nigeria. The paper reveals the different contributions of the dimensions of education, health and living standard.

The study focuses on rural farm households in Nigeria. Data are obtained from the Nigeria General Household Survey, 2013. The survey covers both urban and rural areas of the 36 states of Nigeria. Owing to the interest of this study in the rural farm household’s sub-sector, a nationally representative sample of 836 rural farm households are selected for the study after the data merging process. Rural farm households in this paper earn 50 percent of their total income from crop and livestock production. The paper employs the Multi-dimensional Poverty Index (MPI) to measure multi-dimensional poverty across the six different geographical zones of Nigeria. The probit regression model is used to estimate and analyze the effect of off-farm income components on multi-dimensional poverty and also to identify the determinants of multi-dimensional poverty.

The results of the study show that among the off-farm income components, the non-farm wage income and non-farm self-employment income have negative association with multi-dimensional poverty. Findings show that multi-dimensional poverty is high in Nigeria with deprivations in health contributing the most. Northern Regions have a higher estimate. Results reveal that sex, age, number of adults, formal credit access, access to extension services and location characteristics are key determinants of multi-dimensional poverty. The MPI for Nigeria averaged 47 percent. Across regions, deprivation in the health dimension contributes about 44 percent to multi-dimensional poverty. Deprivation in living standards contributes 40.5 percent, while deprivation in education contributes 15.5 percent to multi-dimensional poverty.

Due to the nature of the data used, the health indicators (nutrition and child mortality) are absent but proxies are used instead. Future research could introduce gender dimensions.

Improving the involvement of rural farm households in non-farm self-employment sector could improve their livelihoods and prevent migration to urban centers, especially among the youths.

Improving the quality of health, education and living standards will lead to lower poverty levels in Nigeria. Farmers can best reduce their multi-dimensional poverty by engaging in more off-farm jobs.

This paper provides information to policy makers on the effect of different components of income from the off-farm sector on multi-dimensional poverty alongside with the determinants of multi-dimensional poverty at a national level for the rural farm households. By using MPI, the contribution of the different dimensions used in computing the MPI across the six geographical regions within the country is revealed. This provides policy makers with more information for development purposes.