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Energy poverty is a global phenomenon, but its prevalence is enormous in most African countries, with a potential impact on quality of life. This study aims to investigate the impact of energy poverty on the shadow economy.

The study uses panel data from 45 countries in Africa over a period of 1996–2018. Using panel cointegrating regression and panel vector auto-regression model in the generalized method of moments technique.

This study provides that energy poverty deepens the size of the shadow economy in Africa. It also documents that there is a bidirectional causality between shadow economy and energy poverty. Therefore, the two variables can predict each other.

The study suggests that lack of access to clean and modern energy services contributes to the depth of the shadow economy in Africa. African authorities are advised to strengthen rural and urban electrification initiatives by providing adequate energy infrastructure so as to reduce the level of energy poverty in the region. To ensure energy sustainability delivery, the study proposes that the creation of national and local capacities would be the most effective manner to guarantee energy accessibility and affordability. Also, priorities should be given to the local capital mobilization and energy subsidies for the energy poor. Energy literacy may also contribute to the sustainability and the usage of modern energy sources in Africa.

Previous studies reveal that income inequality contributes to the large size of shadow economy in developing economies. However, none of these studies analyzed the role of energy poverty and its implications for underground economic operations. Inadequate access to modern energy sources is likely to deepen the prevalence of informality in developing nations. Based on this, this study provides fresh evidence on the implications of energy deprivation on the shadow economy in Africa using a heterogeneous panel econometric framework. The study contributes to the literature by advocating that the provision of affordable modern energy sources for rural and urban settlements, and the creation of good energy infrastructure for the firms in the formal economy would not only improve the quality of life but also important to discourage underground economic operations in developing economies.

Despite a reduction in poverty the global population in 2015, the incidence of poverty remains very high in Sub-Saharan African countries. Most of the countries in the region are agrarian, with most of their population residing in rural areas, and a majority of the poor in the region are found in Nigeria. This study examined the nexus between participation in nonfarm enterprises (NFEs) and poverty among rural farm households in Nigeria and across the six geopolitical zones.

The Nigerian Living Standard Survey (NLSS) conducted in 2018–2019 by the National Bureau of Statistics was used. We made use of 13,440 farm households with useful information for the purpose of this study. The sample comprises 6,885 households that participated in NFEs and 6,555 nonparticipating households. The data were analyzed with Foster, Greer, and Thorbecke (FGT) (1984) metrics, probit, and fractional probit models at p = 0.05.

The incidence of poverty was lower among the participating households than in the nonparticipating households. Participation in NFEs had a mitigating effect on poverty. We also established that zonal differentials in poverty rates exist among households in all the analyses. Participation in NFEs was influenced by individual, household, and institutional factors and was also able to explain the depth of poverty among the respondents.

It is suggested that poverty alleviation policies should be targeted at improving access to nonfarm economic activities by rural farm households residing in vulnerable geopolitical zones.

This study is the first attempt to profile household poverty based on the type of NFEs they are involved in. The study also provides an insight into the effect of the state of residence on zonal poverty models, which is expedient if the country must achieve Sustainable Development Goal 1 on the eradication of poverty everywhere.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0493

The objective of this paper is to investigate the impact of institutional quality, foreign direct investment (FDI) inflows and human capital development on Indonesia’s poverty rate.

The quantile regression on data ranging from 1984 to 2019 was used to capture the relationship between the impact of the independent variables (FDI inflows, institutional quality and human capital development) on Indonesia’s poverty rate at different quantiles of the conditional distribution.

The empirical results reveal that low-quantile institutional quality is detrimental to poverty eradication, whereas FDI inflows and human capital development are significant at higher quantiles of distribution. This implies that higher-value FDI and advanced human capital development are critical to lifting Indonesians out of poverty.

Policymakers should prioritise strategies that advance human capital development, create an enticing investment climate that attracts high-value investments and improve institutional quality levels.

This study contributes to the existing literature because, compared to previous studies that focussed on estimating the conditional mean of the explanatory variable on the poverty rate. It rather provides a more comprehensive understanding of the quantiles of interest of FDI inflows and institutional quality on the Indonesian poverty rate, allowing for more targeted policies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2023-0733

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.

By using the World Bank's new poverty data that are based on the most recent International Comparison Program report, this research aims to revisit the response of poverty rate to increase in real gross domestic product (GDP) per capita.

The response is summarized in terms of elasticity of poverty with respect to real GDP per capita, which is the ratio of annual percentage fall in poverty rate to annual percentage increase in real GDP per capita. The main calculations are done for the entire group of less‐developed countries (LDCs), poverty‐dense South Asia region, and India, which probably has the highest poverty rate. The periods studied are 1981‐1990, 1990‐1999, and 1999‐2005. The calculations are done for four different poverty measures.

Five major points are noted. First, the elasticities generally show a declining tendency over the period, indicating that poverty‐reducing impact of income growth has been weakening. Second, the elasticities show huge differences across the poverty lines, and generally decline with higher poverty lines. Third, while global elasticities for $1.00 poverty line bear some resemblance to those reported or used by many scholars, elasticities for $2.00 and 2.50 poverty rates are dramatically lower, and reinforce the view that many influential estimates show the effect of income growth on poverty to be much higher than the data indicate. Fourth, elasticities for poverty‐dense South Asia are again seen to be much lower than those for the entire LDC group. Fifth, for India, where $2.00 and 2.50 poverty rates are higher than even in Sub‐Saharan Africa, the elasticities are extremely low and have been declining despite an acceleration in income growth. The overall implication seems to be that income growth has generally been less pro‐poor during the globalization era of the 1990s and the 2000s than during the 1980s. In particular, income growth in India seems to have had an extremely small impact on poverty, and that impact, notably for $1.00 and 1.25 poverty lines, has been declining.

First, although there is a vast literature on growth elasticities of poverty, this seems to be the first study that uses World Bank's new poverty data to judge the impact of income growth on poverty. Second, this is the only study that directly estimates and compares elasticities for the four poverty lines of $1.00, 1.25, 2.00, and 2.50, and shows large differences in the elasticities for different poverty lines. Third, this is probably the only work that compares elasticities for the 1980s, 1990s, and the 2000s. Fourth, although some indication of very low elasticities for South Asia and India does exist in a recent study, $2.50 elasticities reported in the present work for India, and even South Asia, should constitute an eye‐opener for scholars, policy‐makers, and international organizations in regard to the potential role of income growth in poverty reduction. Fifth, the observed decline in most elasticities during the 1990s and 2000s, as compared with the 1980s, despite higher income levels and growth rates, may shed light on the likely role of globalization in reducing poverty.

The analysis of poverty is fundamentally focused on examining the well-being condition of the poor. We usually neglect the information provided by the rich. Nevertheless, perhaps the non-considered information indicating the determinants of non-poverty is also useful for fighting against poverty. The purpose of this paper is to analyze poverty under a new angle i.e. focusing on the information provided by the non-poor instead of the poor. For that a richness index is calculated in order to estimate econometric models regressing both indices i.e. poverty and richness indices on same selected characteristics. Thus, the comparison of the determinants of poverty and non-poverty for Tunisian case have allowed the classification of the selected explanatory variables with significant effect into four categories: the variables having significant effect on both sides (permanent effect), the variables having significant effect on the poor but not on the non-poor (transitory effect), the variables having significant effect on the non-poor but not on the poor (insurance effect) and the variables without any effect on both cases (neutral effect). This procedure is thus important given that it provides additional information and new way to enhance the targeting efficiency of the poor and fighting against poverty.

Using Tunisian data, an original procedure is proposed for calculating a richness index, defined based on the common formula of calculating the poverty index. Next econometric models are estimated regressing both the indices i.e. poverty and richness index on same selected characteristics.

The comparison of the determinants of poverty and non-poverty have allowed the classification of the selected explanatory variables with significant effect into four categories: the variables having significant effect on both sides (permanent effect), the variables having significant effect on the poor but not on the non-poor (transitory effect), the variables having significant effect on the non-poor but not on the poor (insurance effect) and the variables without any effect on both cases (neutral effect).

The analysis and the classification of the determinants of poverty according to the determinants of non-poverty is never made before in the litterature. This procedure is important given that it provides additional information and a new way to enhance the efficiency of targeting the poor and fighting against poverty.

Using the latest census data (2010), this paper investigates housing poverty conditions in Shanghai, the largest city in China. The data shows that a large fraction of Shanghai households are still living in excessively over-crowded housing. Meanwhile, the incidence ratio of housing poverty among migrants is more than five times than among natives. In particular, 45% of rural migrant households were living in housing poverty. Poverty decomposition analysis shows that approximately 70% of total housing poverty in Shanghai is attributable to rural migrants. Our finding is supported by estimating the multidimensional poverty index (MPI). The findings in this paper have significant implications to general housing policy making in urban China.

Poverty numbers have decreased in the United States over the past few decades but these statistics tend to mask trends for different demographic groups. Aged women living alone make up 95 per cent of non‐family households, and 47 per cent of these women had annual incomes of less than $10,000 and most were living at the poverty threshold in 1989. Concern about poverty among the aged is addressed from two perspectives. First, changes in the magnitude, characteristics and incidence of poverty among the aged population are reviewed. Secondly, analytical models of the severity of poverty are presented and these models are used to describe techniques that may be employed in attempting to alleviate poverty in one category of the aged poor where it seems most acute and most intractable, i.e. aged women living alone. Three poverty models are presented: (1) concentrating economic aid to those just below the poverty threshold and reducing numbers; (2) concentrating aid to those in deepest need; and (3) a sliding scale. The modified welfare ratio model showed that concentrating economic aid to the aged poor in deepest need (furthest from the poverty threshold) yields greater social and economic benefits.

The purpose of this paper is to yield more plausible rural poverty lines for China and then assess the determinants of rural poverty using these newly revised rural poverty lines.

In this paper it is argued that the Chinese official poverty line substantially misestimates the actual rural poverty situations. The poverty lines are derived with Ravallion's method with a rural household survey data of China's two provinces, Hubei, and Inner Mongolia. Poverty determinants using the derived as well as the other rural poverty lines are compared.

The results indicate that the poverty lines derived from a pan‐country level food bundle cannot fully reflect the regional poverty situation. Merely adjusting rural poverty lines at the country‐level consumer price index without fully considering changes in the structure of food consumption and food prices with respect to different regions may also lead to wrong poverty estimates. The comparisons between the model regression results using the newly derived poverty lines with the alternative rural poverty lines suggest that the current literature uses the World Bank or the Chinese official rural poverty lines to assess how the rural poverty determinants might yield implausible policy implications.

China needs to adjust the rural poverty lines with full consideration to the structure of food consumption and food prices with respect to different regions.

It is indicated that the Chinese official poverty line substantially misestimates the actual rural poverty situations in China and this in turn affects the associated policy implications.

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.