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This study investigates the integration of social justice concepts using an introductory business statistics course at a Jesuit university, with a focus on poverty and income inequality. The study aims to enhance students' awareness, understanding, and empathy for social justice issues while strengthening their statistical knowledge. The pedagogical approach comprises three main elements: Twitter-based assignments centered on poverty statistics, a documentary on poverty in America, and a 5K race mission project. The results reveal a notable increase in poverty awareness, deepened empathy, and the development of moral and spiritual character among students. By combining knowledge, reflection, and action, this approach aligns with the Ignatian pedagogical paradigm and upholds the Jesuit mission of higher education. The study exemplifies fostering change by integrating social justice into higher education, encouraging students' active engagement as agents for positive impact, aligning with the principles for responsible management education set forth by the United Nations. [ABSTRACT FROM AUTHOR]

We investigate the current method of derivation of the international poverty line used for monitoring SDG 1 in two key directions: (a) we ask whether the official method used by the World Bank is fit for the purpose of measuring extreme poverty and if their method is defensibly valid both internally and externally; and (b) we ask whether the resulting statistics perform acceptably well in terms of accuracy and precision. Using comparative analysis, error accounting methods, and minimization criteria, on key poverty indicators, our investigation gathers compelling evidence that leans towards a negative answer to both questions. We conclude that the adoption of alternative methods for monitoring global poverty should be considered in an official capacity with urgency. [ABSTRACT FROM AUTHOR]

Poverty exists not only in low and middle-income countries but also in high-income countries. Brunei, a rich country heavily reliant on hydrocarbon in Southeast Asia, is not an exception. Though poverty is not a topic that is politically taboo in Brunei, there are no statistics on poverty in Brunei. Yet, having such statistics would aid the government to achieve the target of zero poverty in 2035. Therefore, this technical paper provides a pioneering estimation of poverty rates in Brunei, utilising published data from 'Household Expenditure Surveys' and focusing on the basic need approach. It calculates monthly household poverty rates based on the World Bank's poverty lines and OECD median income approach. It produces poverty rates based on expenditure and income. The research employs two models: a proportional model and a refined model. The results show declining rates of poverty, regardless of the poverty lines and models. [ABSTRACT FROM AUTHOR]

The purpose of this study is to provide a model to determine the economic variables affecting the multidimensional poverty index in the Middle East in the period (1995-2017). The method of the present research is descriptiveanalytical. The statistical population of this study is Middle Eastern countries. Data collection has been done using official statistical centers in different countries in cooperation with the Statistics Center of Iran. Data analysis was performed using Eviews and SPSS software version 21. Various variables were effective in estimating the multidimensional poverty index in Middle Eastern countries. But the variables of human capital, capital formation, foreign trade, inflation rate due to terrorist threats, gross domestic stability) were analyzed as the most important influential variables. The generalized torque (GMM) method was used to analyze the proposed model and tests such as Sargan, regression coefficient, Jarco-Braha test, Watson camera statistics were used. The results of multidimensional poverty index analysis in the Middle East using the period from 1995 to 2017 in terms of manpower index (balanced fluctuations), gross domestic stability (constant fluctuations), inflation due to terrorist threats (high fluctuations with steep slopes into increase poverty), capital formation (poverty reduction fluctuations), foreign trade (very large fluctuations to reduce poverty). The results of estimating the research model in the form of a dynamic model by the generalized torque (GMM) method showed that the probability value related to the validity of the null hypothesis that the coefficient of variables FI (t-1), foreign trade (trade), inflation) is zero. Due to terrorist threats (IN), CF capital formation, Gross Domestic Stability (INV), and Human capital (H), the fixed value of the model is equal to 0.062, 0.042, 0.025, 0.046, 042, respectively. 0.8, 0.844, is smaller than the probability of the first type error 0.05. Therefore, at this level of error, the significance of the effect of these variables and the presence of a constant value in the model is not denied. The explanation coefficient of the model is equal to 0.738 and is larger than the standard limit of 0.7. Therefore, predicting the multidimensional poverty variable in Middle Eastern countries according to the independent variables considered in the model has relatively high accuracy. [ABSTRACT FROM AUTHOR]

This article discusses the impacts of the energy crisis on households in England and Wales, with a focus on the equity implications. The study utilizes a large collection of microdata to quantify the energy shock experienced by households and examines how it varies across different demographics and building characteristics. Low-income households were particularly affected by the crisis, as energy costs represented a disproportionate burden on their income. The study suggests that wealthier regions experienced larger shocks due to the characteristics of the properties in those areas. However, the analysis is limited by the high level of data aggregation, which masks within-region heterogeneity. The author recommends using more granular data sources, such as income data at the Lower Layer Super Output Area (LSOA) level, to better understand the distributional impact of the crisis. Future research could also explore household-level energy consumption and household responses to energy price changes. [Extracted from the article]

Household Consumption and Expenditure Surveys (HCES) collect comprehensive information on households' consumption and can provide a range of analyses on access to food. They are key to estimating poverty (SDG 1.2.1) and Prevalence of Undernourishment (SDG 2.1.1). Before the food data becomes meaningful for analysis, it needs extensive preparation. While NSOs are responsible for poverty statistics and typically prepare the data for this purpose, it is often organizations or researchers that use the data for food security. Although the preparation of the data for these two purposes has a lot in common, they rely on different traditions and guidelines. This paper presents results from an ongoing project that aims to bridge the gap between these two processes. The project's goal is that NSOs take the lead in preparing the HCES food data for all uses. An expected result is that the food security statistics will be available at the same time as the other main outputs from the survey and can be used for planning for improved food security. The project includes preparing a guideline for NSOs and others (endorsed by the United Nations' Statistical Commission in 2024), building capacity in NSOs, and using results in a regional context. [ABSTRACT FROM AUTHOR]

Household Consumption and Expenditure Surveys (HCES) collect comprehensive information on households' consumption and can provide a range of analyses on access to food. They are key to estimating poverty (SDG 1.2.1) and Prevalence of Undernourishment (SDG 2.1.1). Before the food data becomes meaningful for analysis, it needs extensive preparation. While NSOs are responsible for poverty statistics and typically prepare the data for this purpose, it is often organizations or researchers that use the data for food security. Although the preparation of the data for these two purposes has a lot in common, they rely on different traditions and guidelines. This paper presents results from an ongoing project that aims to bridge the gap between these two processes. The project's goal is that NSOs take the lead in preparing the HCES food data for all uses. An expected result is that the food security statistics will be available at the same time as the other main outputs from the survey and can be used for planning for improved food security. The project includes preparing a guideline for NSOs and others (endorsed by the United Nations' Statistical Commission in 2024), building capacity in NSOs, and using results in a regional context. [ABSTRACT FROM AUTHOR]

The article, titled "Michelle Hewitt," discusses the issue of disabled individuals living in poverty and the implications it has on their access to medical assistance in dying (MAiD). The author, Michelle Hewitt, who is a disabled woman with multiple sclerosis, highlights the overrepresentation of disabled people among those living in poverty in Canada. The article presents two examples of individuals who have considered MAiD due to the unbearable suffering caused by their poverty-induced conditions. Hewitt argues that the current safeguards for MAiD are failing and calls for support of the Canada Disability Benefit bill and wide reform in care systems to address the needs of disabled individuals. [Extracted from the article]

In Spain there is a high incidence of in-work poverty, which has not changed much after the so-called Great Recession, despite its strong impact on the economy and the labour market. The first objective of this article is to analyse the evolution of poverty during the economic cycle between the previous crisis and the period immediately prior to the COVID-19 pandemic, using indicators with a poverty line anchored at the beginning of that period. This addresses the relative nature of the official indicator, which is calculated for each year, preventing it from capturing changes in the incidence of poverty over time. A second objective is to determine which dimensions are most relevant for in-work poverty and its evolution. Thus, in-work poverty is conceptualised as a phenomenon composed of an individual and a household reality, distinguishing between individual poverty (low-pay situations), household poverty (coming from in-work poverty statistics), and severe poverty (the conjunction of family poverty and low pay). In addition, the last purpose is to analyse the influence of economic cycles, both on the weight of each of the types of in-work poverty and on the factors that explain them, exploring which groups suffered most from the Great Recession and whether this was a temporary situation. Our findings were mainly threefold. First, in 2019, just before the COVID crisis, in-work poverty rates had not recovered from the previous crisis, especially in the case of severe poverty. Second, individual in-work poverty declines during the crisis, associated with an increase in the overall unemployment rate and a parallel increase in severe poverty, but partially recovers in 2019. Third, the most severe type of in-work poverty, where the individual and household dimension converge, has similar characteristics to household in-work poverty, mainly influence by the presence of children and single-parent families. [ABSTRACT FROM AUTHOR]

Accurate and comprehensive urban poverty monitoring is undoubtedly essential to support the urban poverty alleviation targets in many developing countries. The currently available urban poverty monitoring in Indonesia is, however, primarily depends on the expensive and resource-demanding Indonesia National Socio-Economic Survey (SUSENAS). Despite its high-quality poverty statistics, such national-scale survey collection methods are indispensably labor and cost expensive to scale. Alternative data is essentially required to be explored for supporting government poverty data in order to increase the data granularity. In this study, we aim to develop the spatially granular poverty index (SGPI) consisting of multisource remote sensing satellite imageries and big data sources. With 1 km resolution, the SGPI is composed of nighttime light (NTL), normalized difference built-up index (NDBI), carbon monoxide (CO) and nitrogen dioxide (NO2) pollution levels, education and healthcare Point of Interest (POI) data, as alternative economic activity and poverty proxy indicators. Three different approaches of the equal-weighted sum method, the Pearson correlation coefficient method weighted method, and PCA weighted method are compared and evaluated to combine different indicators. Our result shows that the SGPI built in the scope of Jakarta Metropolitan Area (JMA) by using the equal weighted sum with Yeo-Johnson transformation (EWS-YJ) has the highest correlation with official poverty data which is 0.954. Based on visual identifications through high-resolution satellite imagery, the areas with a relatively high SGPI value are densely populated, and vice versa. Our findings suggest that multi-source remote sensing and geospatial big data integration are promising alternative approaches for granular urban poverty mapping based on spatial characteristics. [ABSTRACT FROM AUTHOR]

In recent decades, poverty has increasingly been marginalised in Australian policy discourse. One strategy used by social justice advocates to revitalise a poverty policy agenda has been the annual Anti‐Poverty Week campaign, which aims to stimulate community debate around policy innovations to relieve poverty. This paper analyses the Commonwealth parliamentary debates around Anti‐Poverty Week for 10 years from 2012 to 2021. We analyse and compare how politicians from three political parties – the Liberal and National Party Coalition, the Australian Labor Party and The Australian Greens – identified the key statistics for and groups in poverty, their sources of evidence, the consequences of poverty for those affected, the causes of poverty including whether or not disadvantage was linked to wider structural inequities, and the framing of poverty and potential policy solutions. Some conclusions are drawn from these findings about potential strategies for reinvigorating the poverty debate. [ABSTRACT FROM AUTHOR]

Purpose The study analyzes the dimensions of poverty that have enveloped humanity, the Outlook and the factors affecting child poverty, the living conditions of impoverished children, activities to reduce child poverty, and the situation of poor children in Turkey. Methodology/Approach/Design- Firstly, a literature review was conducted in order to find an answer to the question, “Why are children poor?” and the contents of the child poverty documents were analyzed based on the research question. In this study, qualitative analysis method was used and TUIK child research statistics, OECD child poverty statistics were also analyzed. Findings- The study concluded that child poverty is associated with family poverty. In order to reduce family poverty, in-kind and financial aid should be increased, and family conditions should be improved. However, it should be monitored whether in-kind and financial aids are directed toward alleviating the children's poverty within the family, and it should be aimed to improve the present conditions of impoverished children and invest in their future. Originality/Value- This study provides a holistic view of child poverty using a multidimensional approach. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study is to evaluate whether nighttime luminosity sourced from the Defense Meteorological Satellite Program-Operational Linescan System satellite sensors is a suitable proxy for measuring poverty in Africa. Design/methodology/approach: Our study performs wavelet coherence analysis to investigate the time-frequency synchronization between the nightlight data and "income-to-wealth" ratio for 39 African countries between 1992 and 2012. Findings: All-in-all, the authors find that approximately a third of African countries produce positive synchronizations between nighttime data and "income-to-wealth" ratio and hence conclude that most African countries are not at liberty to use nighttime data to proxy conventional poverty statistics. Originality/value: In differing from previous studies, the authors examine the suitability of nightlight intensity as a proxy of poverty for individual African countries using much more rigorous analysis. [ABSTRACT FROM AUTHOR]

The present paper seeks to empirically verify the question: what impacts informality? The paper is based on recent analyses of cross-sectional data obtained from various sources for selected Asia-Pacific countries covering the period 2016 to 2019. It makes use of the path analysis technique and Stata-15 software. The findings presented here suggest that human development and poverty rates negatively and significantly impact informality. This empirical exercise makes the case for human capital development strategies by leveraging digital technologies on the one hand and "one-time big-push" poverty reduction interventions on the other to avoid the poverty-informality trap. In addition, by finding a positive and significant relationship between tax revenue and informality, the paper suggests for tax rationalization policies so that informal sector firms are incentivized to pay taxes and become formalized instead of hiding out. The paper also advocates for well-conceived, reality-tailored policies for the formalization of the informal sector by addressing the underlying causes of informality so that economic growth gets spurred in these economies. [ABSTRACT FROM AUTHOR]

The third part of the book consists of 60 brief national poverty country reports, which contain information on monetary poverty estimates over time (with different poverty lines), as well as OPHI's MPI estimates. The chapter also describes the different methods for constructing Consumer Price Indices and the difficulties in collecting data on prices, highlighting the lack of data on the prices the poor face. [Extracted from the article]

This data brief describes the European Union Statistics on Income and Living Conditions (EU-SILC). Detailed data on income and taxes are collected, as well as information on material deprivation, labour, housing, childcare, health, access to and use of services, and education. Although primarily a social policy instrument that addresses the information needs of policymakers and is used for social monitoring at the European level, EU-SILC is also closely geared to the needs of researchers and provides an excellent database for evidence-based research on a wide variety of aspects of income, income poverty, material poverty, health, and well-being in Europe. EU-SILC is composed of national probability sample surveys and is conducted annually. The target population comprises private households. Observation units are households and all current household members. EU-SILC provides cross-sectional and longitudinal data. The data are composed of a fixed core module, and annually changing ad-hoc modules. Launched in 2003 and revised with effect from 2021, EU-SILC is currently implemented in all EU Member States and in 11 non-EU countries. During the revision process, many suggestions from the research community were incorporated. [ABSTRACT FROM AUTHOR]

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We show that economies of scale estimated individually for each EU country differ from the officially adopted OECD‐modified scale; the differences across the countries further confirm the prevailing East‐West disparity. Using the minimum income question in the 2019 EU‐Statistics on Income and Living Conditions survey, we demonstrate that applying the estimated country‐specific subjective equivalence scales, instead of the uniform OECD‐modified scale, results in up to a 6 pp change in the at‐risk‐of‐poverty rate. If inadequate equivalence scales are used, the equivalised income fails to inform the statistics of income poverty and prevents national social policies from being correctly targeted. [ABSTRACT FROM AUTHOR]

The article explores cartographic and statistical registers of poverty as geo-legal technologies operating across shifting visual economies which structure ways of seeing and concealing 'the poor' in the urban landscape. Drawing on the fields of critical cartography and digital urbanism, and taking a 2013 controversy around Google Maps' mapping of favelas in Rio de Janeiro as a starting point, it investigates the aesthetic role of digital maps and data in the legal geographies of urban poverty. It is argued that sociospatial encodings give form to poverty in ways that activate antipoverty responses and continuously support correlations between poverty and criminality. This argument entails a post-representational approach to maps considering their inscriptional, propositional and normative functions. Cartography, statistics and law are interrogated as devices of global governance that work aesthetically to shape poverty and its modes of appearance in the city, i.e., as productive methods of documentation as well as world-making, through which geocodings simultaneously create images of poverty and become functional of spatial transformations. Poverty is thus conceptualized as it is made into an aesthetic category subjected to continuous geo-legal modulations. [ABSTRACT FROM AUTHOR]

Poverty statistics are conventionally compiled using data from socioeconomic surveys. This study examines an alternative approach to estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial distribution of poverty in Thailand. In particular, the geospatial data examined in this study include the intensity of night-time light (NTL), land cover, vegetation index, land surface temperature, built-up areas, and points of interest. The study also compares the predictive performance of various econometric and machine-learning methods such as generalized least squares, neural network, random forest, and support-vector regression. Results suggest that the intensity of NTL and other variables that approximate population density are highly associated with the proportion of an area's population that are living in poverty. The random forest technique yielded the highest level of prediction accuracy among the methods considered in this study, primarily due to its capability to fit complex association structures even with small-to-medium-sized datasets. This obtained result suggests the potential applications of using publicly accessible geospatial data and machine-learning methods for timely monitoring of the poverty distribution. Moving forward, additional studies are needed to improve the predictive power and investigate the temporal stability of the relationships observed. [ABSTRACT FROM AUTHOR]

Agriculture is an important part of the rural economy in sub-Saharan Africa; however, statistics for poverty and underemployment in the region are highest in the world. One of the support mechanisms for economic growth are ministerial strategies to create and support new small- and medium-sized enterprises that add value to primary agricultural products through food processing. Urbanization, the expansion of supermarkets, and the demand for convenience food, present potential opportunities for economic growth to these new food processing businesses. Given the significant incidence of foodborne illness in the region, this article will consider the food safety challenges new food processing businesses in sub-Saharan Africa will face. [ABSTRACT FROM AUTHOR]

As many other countries, India leverages on a pre‐existing workfare programme as a COVID‐19 response. We combine monthly administrative data with migration and poverty statistics and provide four insights on the recent expansion of the programme. First, poorer districts include more households, that is, increasing extensive margin. Second, in districts with a high proportion of return migrants, there is no increase, and third, unmet demand for work is higher than the national average of 22.7%. Fourth, despite the expansion, the programme provided just 13.5 days per rural household. The programme requires attention to fulfil its promise as a credible safety net. [ABSTRACT FROM AUTHOR]

Children born to unmarried parents make up an increasing share of American children. But official poverty statistics provide little insight into their economic well-being because these statistics use an outdated definition of the family unit and an incomplete measure of family resources. Using Current Population Survey data and an improved measure of poverty, the Census Bureau's Supplemental Poverty Measure, we reassess long-term trends in poverty for children in unmarried parent families—those led by single mothers, those led by single fathers, and those led by cohabiting couples—as opposed to their counterparts in married couple families. We find that single-mother families have the highest poverty rates among families, both historically and today, but the improved measure shows much larger declines in single-mother families' poverty rates over time. Single-father and cohabiting families also have high poverty rates, but those rates have also fallen by approximately one third since the 1960s. [ABSTRACT FROM AUTHOR]

The recent methodological development has entirely shifted the identification of poor in the multidimensional spectrum; thereby addressing the multiple health spheres. The present research primarily examines the dynamics of multidimensional health poverty on the basis of HIES & PSLM nationwide survey data from 2013–14 to 2018–19. The study employed Alkire & Foster Alkire, S (2007) Multidimensional Poverty Index to estimate the seven distinct dimensions of health aspects to identify the poor. The results of health poverty demonstrate a declining trend over time at national, provincial and regional level in Pakistan. Interestingly, the regional statistics indicated the poverty as a rural phenomenon of Pakistan. Comparative measures of provinces reveal that Baluchistan has been a severe victim of health poverty at overall as well as regional level during the study period. The population decomposition elaborates that individuals residing in two most populated provinces Punjab & Sindh, were the major contributor to overall profile of health poverty. Findings of dimensional decomposition exposes that five key dimensions i.e. use of health services, quality of health services, maternal health, child health and malnutrition have contributed to the overall profile of multidimensional health poverty. [ABSTRACT FROM AUTHOR]

The establishment of the Sustainable Development Goals in 2015 entails generating relevant and timely statistics for monitoring and policymaking. The Philippine Statistics Authority (PSA) generates poverty statistics using the Family Income and Expenditure Survey (FIES). However, due to certain limitations, the FIES collection and calculation of official poverty statistics is done only every three years. In this regard, this paper presents a method of filling in the gaps by interpolating annual poverty statistics, particularly the poverty incidence, using macroeconomic indicators and demographic and employment information from the Labor Force Survey (LFS). These explanatory variables were related to the poverty incidence using the Dynamic Factor Model (DFM) in the state-space form to produce estimates for years when poverty statistics are not available. Relatively high forecast accuracy was observed for the predicted values of poverty incidence. [ABSTRACT FROM AUTHOR]

First, Howard shows that while politicians have incentives to meddle in official statistics for short-term gain, they are rarely successful at doing so. Each country's unique administrative tradition, in Howard's view, affects how politicians and statisticians perform credibility, and hence the allocation of statistical authority. The politics of government statistical agencies tends to be baked into their organizational DNA, what Terry Moe would call a "politics of bureaucratic structure". [Extracted from the article]

We assume the Foster-Greer-Thorbecke (FGT) poverty index as a centered and normalized empirical process indexed by a particular Donsker class or collection of functions and define this poverty index as a bootstrapped empirical process, to show that the weak convergence of the FGT empirical process centered and normalized is a necessary and sufficient condition for the weak convergence of the FGT bootstrap empirical process centered and normalized. Thus, this result re ects that under certain conditions, the consistency in weak convergence of the FGT empirical process considered as a classical estimator of poverty (statistics) and the consistency in weak convergence of the FGT bootstrap empirical process considered as a bootstrap estimator of poverty (bootstrap statistics) are asymptotically equivalents for random samples of incomes statistically large and representative of a statistical universe of households. [ABSTRACT FROM AUTHOR]

Both Canada and the United States are considered liberal welfare states, yet exhibit notable differences in income poverty attributed to social policy. While a more generous welfare system lifts many above income poverty, models of household financial behaviour suggest that more income from the state should displace private savings via a substitution effect. Using nationally representative wealth surveys from Canada and the US from 1998/1999 to 2016 we extend knowledge on the relationship between the welfare state and private wealth accumulation. Specifically, we study household asset poverty defined as financial asset levels that fall below three‐month adjusted income poverty threshold. Asset poverty rates varied over time in the two countries and were higher in the less generous US welfare state. Further, income transfer share was positively related to asset poverty in Canada but not in the US. Counterfactual estimates offered evidence of the substitution effect in Canada, where higher levels of transfers may crowd out private asset accumulation. Results invite further consideration of the concept of asset poverty and its relationship to welfare state characteristics. [ABSTRACT FROM AUTHOR]

Deprivation scales are becoming increasingly familiar in research and official statistics on poverty. Taking advantage of the basis of these scales in Item Response Theory, this paper proposes a more efficient approach to implementation using adaptive testing. This maximises information collected for a given amount of survey time by screening respondents on the basis of initial answers, and halting questioning where it is very unlikely any further information will be gathered. The paper illustrates various implementations using data from eight years of the UK's Family Resources Survey (FRS). Results show that an adaptive approach collects more than 99% of the information from the UK's official deprivation measure in half the survey time. In addition, the paper suggests improvements in the design of the UK's official deprivation scale as well as lessons for the development of future deprivation scales more generally. [ABSTRACT FROM AUTHOR]

South Africa is a paradox; on the one hand, it is one of the most unequal countries in the world. Half of all South Africans continue to live in poverty, economic growth has stagnated and inflation remains high, while the unemployment rate continues to climb towards 30%. On the other hand, it has one of the most progressive constitutions in the world, with a bill of rights that foregrounds expanded socioeconomic rights. We provide an overview of the latest statistics on poverty and inequality in light of overarching economic policies, and the socioeconomic guarantees of the Constitution. We argue that South Africa's inability to meaningfully address the high levels of inequality is due to insufficient attention to the way power reproduces inequality. We present a definition of power that includes social and market power, and emphasise the importance of a theory of power in understanding the reproduction of inequality. [ABSTRACT FROM AUTHOR]

Copyright of Dilemas Contemporáneos: Educación, Política y Valores is the property of Dilemas Contemporaneos: Educacion, Politica y Valores and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In 1997, Mexico replaced its main old‐age pension system with an individual capitalization system. In 2021, the first people subject to the new system will retire. Using a model that projects demographic and labour variables and using Monte Carlo simulations, the findings of this study show that in 2051 the percentage of men not having a pension will increase from 38 per cent to 59 per cent, and that of women from 44 per cent to 66 per cent. The replacement rate for the average Mexican worker will fall from 70 per cent to 30 per cent. The numbers of people in extreme poverty will increase by almost 2.8 million, representing 9.44 per cent of the population. Alternative scenarios are proposed that involve increasing the contribution rate and raising the retirement age. [ABSTRACT FROM AUTHOR]

This article is an examination of the (re)‐production of poverty and marginality among former manorial servants and their descendants in a Hungarian manorial village. Manorial servants were a large subgroup of the agrarian proletariat in interwar Hungary; their long‐term, rural poverty – sometimes conceptualised as 'traditional' – has been aggravated by territorial stigmatisation and represents a specific case even within the context of rural poverty. However, the manorial settlement examined here (now the village of 'Longfield') is an extreme case given that a highly successful large‐scale farm has remained in the locality despite a long series of social, political, and economic changes. The presence of this farm influenced both this locality's developmental path and its room for economic manoeuvring, as well as local people's living strategies and life chances. The empirical basis for this analysis is a collection of 34 family‐history interviews conducted in 'Longfield'. This article encompasses the continuities and discontinuities both in people's narratives and in social and economic structures, and is thus an investigation of the dynamic relationships between and among lived poverty, perceptions of territorial stigmatisation which shape local living strategies, and intra‐ and intergenerational patterns of social and spatial (im)mobility. [ABSTRACT FROM AUTHOR]

This article contributes to explanations of rural poverty and deprivation by focusing on the rural–urban poverty and deprivation gap in European countries. Using European Union Statistics on Income and Living Conditions data, it confirms, convincingly, the limited validity of the argument for universally increased poverty and deprivation levels in rural areas in Europe, and demonstrates that the disparities are related to four theoretically elaborated factors: increased rural poverty can be observed in countries with lower rural population densities, in countries with a higher proportion of farmers, in post‐socialist transition countries, and in countries with generally lower economic development levels and decreased living standards. In particular, national economic development appears to be the essential factor behind rural disadvantage. Three interrelated negative processes have been revealed in the countryside of poor European countries: an increased concentration of low‐resource households, a higher poverty risk to these households, and additional poverty‐enhancing effects that operate independently of household resources. These direct rural effects are strongly conditioned by the national economic advancement and related urbanisation processes. [ABSTRACT FROM AUTHOR]

Many Swiss farming families face socioeconomic disadvantage despite Switzerland being a wealthy country with instruments of agricultural policy financially supporting almost all farmers. However, official poverty statistics exclude Swiss farmers and scientific knowledge is rare about how such situations are experienced. This article scrutinises the situation of Swiss farming families living in poverty or material deprivation by intertwining qualitative and quantitative methods to enrich both types of data and interpretations. By statistically comparing farmers with the self‐employed in other economic sectors, it uses a novel way of comparing the farming with the non‐farming population. The article shows that the poverty among farmers resembles that of the self‐employed with no or few employees in other economic sectors and describes the lived experiences of poverty and material deprivation. It concludes that adaptive preferences make farming families resilient to socioeconomic disadvantage, while possibly leading to a loss of their livelihood in the long run. [ABSTRACT FROM AUTHOR]