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The global relevance of food security has attracted a plethora of research, because it is a determinant of either the prosperity or poverty of any nation. Accordingly, food security is directly associated with the poverty in many developing countries of the world today. Rural people around the world continue to struggle with food insecurity, persistent poverty and inequality, and environmental degradation. This necessitated a research study on food security in the North West province of South Africa, with a view to evaluate the food security status and its determinants in the area, as well as to compare the impact of gender on the food security status of households. A cross-sectional survey was conducted, where 346 maize farmers in the Ngaka Modiri Molema District Municipality of the North West, South Africa, were interviewed. A logically structured questionnaire was used to collect data where household expenditure survey was used to evaluate the food security status of these farmers, after which a logistics regression model was used to determine the factors responsible for food security. The findings reveal that, with more farming experience, the probability of household food security decreased. Also, an increase in the household size, by one member, decreases the probability of a household achieving food security. Similarly, a unit increase in the age of the head of household decreases the probability or likelihood of being food secured in the study area. The result also revealed that more than half of the farming households were food secure, while the female-headed households were more food secure, proportionately, compared to male-headed households.

This study aims to scrutinize the determinants of household energy consumption needs in Kebbi State, Nigeria. The data for the study were sourced from household heads within the study area. The paper analyzes the determinants of household energy consumption using six energy consumption indicators (household expenditure on energy, electricity, LPG, kerosene, charcoal, and biomass). To analyze the data, the study used descriptive statistics and binary logistic regression (which has rarely been used in this kind of study) which broaden our understanding of social, economic, and environmental perspectives on energy usage. Our empirical strategy indicates that all the instruments used are appropriate based on Cronbach's alpha scale value of greater than 0.9. Education level was found to be a significant factor in energy expenditure by household, electricity, LPG, and kerosene usage, while negatively correlated with biomass usage. A binary logit regression model revealed that household head income, availability of different energy choices, reliability, and affordability are the major determinants of household energy consumption needs. Findings further show that low-income household heads which account for more than 60% of the respondents rely heavily on the traditional methods of biomass to meet their energy needs. The finding further revealed that 72.80% of the respondents confirmed that accessibility is one of the driving forces which determines their energy choice. Based on the findings, the study therefore, recommends the need to ensure the availability and affordability of safer forms of energy as well as invest more in making renewable energy available and affordable.

To examine socio-economic status (SES) and time-related factors associated with less healthy food purchases in Australia. Data were from the 2009/10 Household Expenditure Survey (HES) conducted by the Australian Bureau of Statistics. Regression analysis was used to examine the associations between the proportion of the household food budget spent on various food types (processed and unprocessed foods, foods purchased from takeaways and restaurants) and SES and time constraint variables. Australia, 2009-2010. Nationally representative sample of Australian households. Household income seems to be the most important correlate with food expenditure patterns once other SES indicators are controlled for. Time constraints appear to explain some, but not all, of the adjusted SES gradients in food expenditure. Comparing home food consumption categories (processed and unprocessed foods) with foods purchased away from home (takeaway and restaurant foods) shows that wealthier, more highly educated and least disadvantaged households spend relatively less of their total food budget on processed and unprocessed foods prepared at home and more on foods purchased away from home at restaurants. Simple SES gradients in dietary behaviour are influenced by correlations between different SES indicators and between SES and time constraints. Examining these factors separately obscures some of the possible causal effects of disadvantage on healthy eating. When formulating policy responses to unhealthy diets, policy makers should consider alternative sources of disadvantage, including time pressure.

In this study, we explore how to use household expenditures and income surveys (HEIS) to provide replicable and comparable measures of nutrients availability at the population level. Our method formalizes the common practice in the literature and consists of three steps: identification of relevant food categories, pairing of food contents food groups in HEIS data, and calculation of the typical amount of nutrients by food group. We illustrate the usage of the method with Mexican data and provide a publicly available data set to readily convert food purchases into six nutrients: calories, proteins, vitamins A and C, iron, and zinc. We perform a descriptive analysis of the evolution of nutrients intake among Mexican households between 2008 and 2020, considering differences by income level. Our results reflect the effect of the COVID-19 pandemic on nutrient availability in Mexican households, mainly driven by a substantial reduction in the expenditure in food consumed away from home, although for most nutrients the trend was stable over most of the period.

The overall objective of the Sustainable Development Goals is to end poverty in all its manifestations by 2030. To achieve this, international remittance inflows have been identified as crucial external financing, especially for developing countries, to secure the resources needed to improve the living conditions of the poor in these countries. It is on this premise that this study investigates the nexus between remittances and poverty in selected countries in Asia, Africa and Latin America, given that these regions receive the highest amount of remittances globally. The study uses annual data on 38 top recipients of remittances between 1990 and 2021. To ensure the robustness of the results, the study employs two indicators of poverty: household consumption expenditure and poverty headcount. On the methodological front, the study addresses the issue of cross-sectional dependence in a panel study and also corrects for endogeneity, using both static and dynamic methods of analysis, respectively. Empirical findings from the cross-sectional dependence test confirm the interdependence of countries in the study. Interestingly, the study confirms the optimistic view that remittance reduces poverty in the selected countries. This finding is consistent for the two poverty indicators regardless of the methodology adopted. The study concludes that remittance inflows play a pivotal role in alleviating poverty in the selected countries. Based on the findings, governments in the three regions are advised to devise appropriate policies and structures that can support and channel the proceeds from remittances to productive ventures to reduce the incidence of poverty in their respective countries.

PurposeThe present study evaluates the impact of special economic zones (SEZs) on poverty, both rural and urban with special reference to Andhra Pradesh in India, using household consumption expenditure data. In addition to estimating the effects of the SEZs on poverty, the authors explore some of the possible mechanisms generating these effects.Design/methodology/approachThe authors apply a difference-in-differences (DID) technique on a pooled, cross-sectional, district-level dataset based on official annual household surveys for the period from 2001 to 2012 to estimate the average effects of SEZs on household expenditure per capita, a commonly used measure of household poverty.FindingsThe establishment of the SEZs constituted a major exogenous shock to rural economies by creating demand for large chunks of land, which had an immediate impact on the economic and social settings of these economies and aggravated rural poverty. However, over time the poverty aggravating effects of SEZs in rural areas dampened. The effects of SEZs on urban poverty are found to be different from those on rural poverty. It is also revealed that the districts with multiple SEZs experienced larger effects than those with only one or two SEZs. Overall, the SEZs did have positive expenditure effects, but this transition might have been accompanied by heightened inequality between the rural and urban areas.Research limitations/implicationsFirst, the authors did not have access to village or municipal-level consumption data. It is therefore assumed here that district level performance is a reliable proxy for the relevant impacts of SEZ operations. Second, panel data, which would allow more precise measurement of effects than the pooled cross section data used in this study, are not available. Third, the authors’ econometric analysis is essentially comparative statics in nature and does not capture possible spillover dynamics, issues of relocation of economic activity, or migration.Practical implicationsFirst, land acquisition is likely to emerge as a major political and social challenge for the localities that host SEZs. For effective policy implementation, it is necessary to establish legal institutions to address this challenge. Second, governments in developing countries often announce new SEZ programmes on a very large scale and insist that they be implemented over short periods of time. The authors recommend that the government should adopt an experimental approach in implementing the policy. Third, the authors provide evidence that in the long run, effects of SEZs hinge on the success of SEZs in attracting investment and generating additional employment. The policy must therefore be informed by rigorous analysis of the potential of SEZs in the country, as well as alternative policy options.Social implicationsThe authors’ results show that large-scale land acquisitions to implement large industrial projects are likely to result in shocks to the rural economy exacerbating rural-urban inequalities: village communities lose their resource base, are marginalised in the process, and, as a result, face economic deprivations. It may lead to severe economic, social and political consequences. The authors’ study implies that any strategy for large-scale industrialisation should take cognisance of its effects on the affected communities and should be designed to include strategies to improve their economic opportunities and to ensure social inclusion.Originality/valueSEZs are one of the most controversial topics within development policy discourse. Their regional development effects are subject to intense debate. Yet, there is surprisingly little systematic evaluation to inform the debate and to guide policymakers. This is one of the earliest studies to assess the poverty effects of SEZs and is the first for India, using household consumption data.

We measure the change in household spending caused by receipt of the economic stimulus payments of 2008, using questions added to the Consumer Expenditure Survey and variation from the randomized timing of disbursement. Households spent 12–30 percent (depending on specification) of their payments on nondurable goods during the three-month period of payment receipt, and a significant amount more on durable goods, primarily vehicles, bringing the total response to 50–90 percent of the payments. The responses are substantial and significant for older, lower-income, and home-owning households. Spending does not vary significantly with the method of disbursement (check versus electronic transfer). (JEL D12, D14, E21, E62)

To investigate trends in out-of-pocket health-care payments and catastrophic health expenditure in India by household age composition. We obtained data from four national consumer expenditure surveys and three health-care utilization surveys conducted between 1993 and 2014. Households were divided into five groups by age composition. We defined catastrophic health expenditure as out-of-pocket payments equalling or exceeding 10% of household expenditure. Factors associated with catastrophic expenditure were identified by multivariable analysis. Overall, the proportion of catastrophic health expenditure increased 1.47-fold between the 1993-1994 expenditure survey (12.4%) and the 2011-2012 expenditure survey (18.2%) and 2.24-fold between the 1995-1996 utilization survey (11.1%) and the 2014 utilization survey (24.9%). The proportion increased more in the poorest than the richest quintile: 3.00-fold versus 1.74-fold, respectively, across the utilization surveys. Catastrophic expenditure was commonest among households comprising only people aged 60 years or older: the adjusted odds ratio (aOR) was 3.26 (95% confidence interval, CI: 2.76-3.84) compared with households with no older people or children younger than 5 years. The risk was also increased among households with both older people and children (aOR: 2.58; 95% CI: 2.31-2.89), with a female head (aOR: 1.32; 95% CI: 1.19-1.47) and with a rural location (aOR: 1.27; 95% CI: 1.20-1.35). The proportion of households experiencing catastrophic health expenditure in India increased over the past two decades. Such expenditure was highest among households with older people. Financial protection mechanisms are needed for population groups at risk for catastrophic health expenditure.

To investigate the equity and policy implications of different methods to calculate catastrophic health spending. We used routinely collected data from recent household budget surveys in 14 European countries. We calculated the incidence of catastrophic health spending and its distribution across consumption quintiles using four methods. We compared the budget share method, which is used to monitor universal health coverage (UHC) in the sustainable development goals (SDGs), with three other well-established methods: actual food spending; partial normative food spending; and normative spending on food, housing and utilities. Country estimates of the incidence of catastrophic health spending were generally similar using the normative spending on food, housing and utilities method and the budget share method at the 10% threshold of a household's ability to pay. The former method found that catastrophic spending was concentrated in the poorest quintile in all countries, whereas with the budget share method catastrophic spending was largely experienced by richer households. This is because the threshold for catastrophic health spending in the budget share method is the same for all households, while the other methods generated effective thresholds that varied across households. The normative spending on food, housing and utilities method was the only one that produced an effective threshold that rose smoothly with total household expenditure. The budget share method used in the SDGs overestimates financial hardship among rich households and underestimates hardship among poor households. This raises concerns about the ability of the SDG process to generate appropriate guidance for policy on UHC.

We study the effect of financial resources on decision-making. Lowincome US households are randomly assigned to receive an online survey before or after payday. The survey collects measures of cognitive function and administers risk and intertemporal choice tasks. The study design generates variation in cash, checking and savings balances, and expenditures. Before-payday participants behave as if they are more present-biased when making intertemporal choices about monetary rewards but not when making intertemporal choices about nonmonetary real-effort tasks. Nor do we find beforeafter differences in risk-taking, the quality of decision-making, the performance in cognitive function tasks, or in heuristic judgments.