Income Poverty Measures Research Articles

Multidimensional Poverty and Risk of Atherosclerotic Cardiovascular Disease: A U.S. National Study

BackgroundPoverty is associated with atherosclerotic cardiovascular disease (ASCVD). While poverty can be evaluated using income, a unidimensional poverty metric inadequately captures socioeconomic adversity. ObjectivesThe aim of the study was to examine the association between a multidimensional poverty measure and ASCVD. MethodsSurvey data from the National Health Interview Survey was analyzed. Four poverty dimensions were used: income, education, self-reported health, and health insurance status. A weighted deprivation score (ci) was calculated for each person. The multidimensional poverty index was computed for various cutoffs, k, for total population, and by ASCVD status. The association between multidimensional poverty and ASCVD was examined using Poisson regression. Area under receiver operator characteristics curve analysis was performed to compare the multidimensional poverty measure with the income poverty measure as a classification tool for ASCVD. ResultsAmong the 328,164 participants, 55.0% were females, the mean age was 46.3 years, 63.1% were non-Hispanic Whites, and 14.1% were non-Hispanic Blacks. Participants with ASCVD (7.95%) experienced greater deprivation at each multidimensional poverty cutoff, k, compared to those without ASCVD. In adjusted models, higher burden of multidimensional poverty was associated with up to 2.4-fold increased prevalence of ASCVD (ci = 0.25, adjusted prevalence ratio [aPR] = 1.66, P < 0.001; ci = 0.50, aPR = 1.99; ci = 0.75, aPR = 2.29; P < 0.001; ci = 1.00, aPR = 2.38, P < 0.001). Multidimensional poverty exhibited modestly higher discriminant validity, compared to income poverty (area under receiver operator characteristics = 0.62 vs 0.58). ConclusionsThere is an association between the multidimensional poverty and ASCVD. Multidimensional poverty index demonstrates slightly better discriminatory power than income alone. Future validation studies are warranted to redefine poverty's role in health outcomes.

Estimating shadow prices in economies with multiple market failures

Approaches to the estimation of shadow prices generally assume that all but one market function correctly. However, multiple market failures are common in developing countries. We present a theoretical model and an empirical strategy to estimate the shadow price of a subsistence good in an economy where labor markets fail. Our results show that: 1) among subsistence producers, the shadow price of this good must be greater than or equal to the market price, and equal to it for surplus growers; and 2) current methods create biases when the otherwise-perfect-markets assumption is violated. The propositions are tested using a representative survey for rural Mexico. We find that the shadow wage is below that of the market (MXN $93.2/day vs. MXN $132.3/day), and that the shadow price for subsistence corn is over ten times greater than its market price (MXN $32.37/kg vs. MXN $3.19/kg). Unbiased shadow price estimates for subsistence goods help to overcome the limitations of current income poverty measures: their overestimation of the purchasing power of subsistence households and their underestimation of the value of subsistence goods. In rural Mexico, current practice underestimates the population in food poverty by 2%; an additional 9% has income above the poverty line yet fail to meet the utilization dimension of food security.

Time and Income Poverty Measurement. An Ongoing Debate on the Inclusion of Time in Poverty Assessment

Time and Income Poverty Measurement. An Ongoing Debate on the Inclusion of Time in Poverty Assessment

Global Income Poverty Measurement with Preference Heterogeneity: Theory and Application

Global Income Poverty Measurement with Preference Heterogeneity: Theory and Application

Poverty and gender in Latin America: How far can income‐based measures go?

AbstractAssumptions of the traditional income poverty measure have strong implications not confirmed by the evidence, but this measure is still widely used in gender poverty analysis. We explore the boundaries of the gender analysis of monetary poverty based on the currently available information (household surveys for 16 Latin American countries). Our results indicate that departing from the conventional methodology has more influence on women than men, worsening female indicators. Households emerge as crucial venues for income support for low income partnered women and for women with no access to any income, whose autonomy is seriously compromised due to this fact.

Economic Growth, Income Inequality and Poverty Trends in Pasture Area’s Householder in SujanagarUpazila, Pabna, Bangladesh: Implications for Development strategy

The study is based on primary household level data obtained from a survey on income expenditure and poverty measures for 2020-21. The perceptual data were collected through field survey which was based on semi structural questionnaire. Total 162 selected samples were considered and simple random sampling techniques have been adopted during data collection. These factual data were collected from various secondary sources like books, journals, magazines, nationally and internationally published data etc. Human development indicators for 1996 have been compared with the study area (pasture area in SujanagarUpazila, Pabna district, Bangladesh). The empirical result shows the analysis of poverty, income inequality, economic growth &amp; development scenario of pasture area’s in Sujanagarupazila, Pabna district, Bangladesh. The research found that 55% respondents live under the poverty line. The study also examines that these householders play an important contribution to the national GDP but their living level is below than standard one. If these areas’ householders’ development access were more available, they would return a great introduction to the society. This paper advises using anti-poverty policy, the concept of poverty minimizing inequality that the society should be tolerant ofattaining the goal of minimizing poverty. It is useful to differentiate between structural and transient causes of poverty. The provision of public goods plays an imperative role in fighting poverty. The government’s proper planning and initiatives, NGOs and Community based organization’s collaboration help build the study area as a socio-economic and environmentally friendly area in Bangladesh.

The impact of investing in social care on employment generation, time-, income-poverty by gender: A macro-micro policy simulation for Turkey

This paper uses applied macro–micro policy modeling and simulation to explore the gendered impact of increased public expenditures on Early Childhood Education and Care (ECEC) on employment and income generation, time allocation to paid versus unpaid work, and poverty. We use a statistically matched dataset from the 2015 Time Use Survey and the Survey on Income and Living Conditions in Turkey to assess the poverty impact not only in terms of official income poverty but also in terms of time-poverty and a combined time- and income poverty measure. We find that increased spending on expansion of ECEC services in the order of 1.8 percent of GDP, generates over a million new jobs, and provides employment for previously non-employed persons, in particular, women. Many job recipient households are lifted above the income poverty threshold reducing the official poverty rate. However, employment into a new job creates a substantial time-poverty effect for women with small children, increasing their time- and income-poverty measure by 50 percent. The positive consumption effects of higher purchasing power (through new jobs and earnings) are dominated by the negative consumption effects of higher time deficits in household production. When newly employed women with small children are also given access to childcare services, their required time for household production decreases by more than one-third, effectively addressing the gendered time poverty. With simultaneous access to ECEC, the time-poverty rates of newly employed women with small children is reduced almost by half and their combined time- and income-poverty rate is reduced by 67 percent. These findings show that employment creation through increased social care spending does not only have the potential to generate a substantial number of jobs in a gender balanced manner, but it also helps to alleviate time- and income poverty and improve gender equality.

Hardship Among Immigrants and the Native-born in the United States.

This study examines the prevalence of several types of hardship (e.g., bill paying and housing hardships) among immigrants by race and ethnicity in the United States using data from the 2008 and 2014 panels of the Survey of Income and Program Participation and logistic regressions. I find that Blacks, and to some extent Hispanics, are more likely to report hardships than Whites and Asians, who are about equally likely to report hardships. Exploring results by nativity and citizenship status, I find that immigrants who became U.S. citizens are less likely than the native-born population to report some kinds of hardship. Undocumented immigrants, however, are more likely to report some kinds of hardships, particularly in the 2008 panel conducted at the time of the Great Recession, which hit immigrants especially hard; this relationship, however, is explained by the lower incomes of undocumented immigrant households in the 2008 panel. Results within racial and ethnic groups are generally in the same direction but are less frequently statistically significant. Overall, these findings suggest that immigrants are not particularly prone to hardship, especially when other characteristics are controlled for. In fact, the lower likelihood of some hardships among foreign-born citizens suggests that they are positively selected: they may have unobserved characteristics that are protective, such as better health, stronger social networks, or money management skills. Because the foreign-born are less likely to be disadvantaged vis-à-vis the native-born when hardship rather than the official income poverty measure is used, this study highlights the importance of using multiple measures when assessing the well-being of immigrants.

The multidimensionality of poverty: Time poverty in Spain

In the last few years the concept of poverty has evolved from simply being a measure of income poverty to a multidimensional measure that takes into consideration essential aspects for the attainment of certain levels of wellbeing. This paper assesses how the incorporation of time can contribute to the measurement of poverty. To this end, we reviewed the time poverty literature and focused on the Spanish case. We use the Spanish Time-Use Survey 2009-2010 to analyse time poverty in Spain, and estimate a probit model to assess the probability of being time poor in Spain and identify key factors associated with time poverty in Spain.

How Poor Are the Poor? Looking beyond the Binary Measure of Income Poverty

This paper contributes to the literature by analysing how poor the income poor are in European countries. Using data from the European Union Statistics on Income and Living Conditions, I go beyond average estimates of the intensity of poverty and analyse the distribution of individual-level poverty gaps in each country of interest. As a next step, I identify which personal and household characteristics predict how far away incomes of the poor fall from the poverty line. The results indicate that, in most European countries, half of the poor have income shortfalls not exceeding 30% of the poverty line whereas only a few percent of the poor have income deficits of 80% and more. The results also suggest that traditional poverty correlates (e.g. age, gender, educational background) are not always significantly associated with the size of normalised poverty gaps at the individual level, or the nature of these associations differs as compared to when the same characteristics are linked to the probability of being poor.

Quality of Statistical Match Used in the Estimation of the Levy Institute Measure of Time and Income Poverty (LIMTIP) for Italy 2008 and 2014 and Preliminary Results

This paper assesses the quality of the statistical matching used in the LIMTIP estimates for Italy for 2008 and 2014. The match combines the 2008–9 and 2013–14 Italian Time Use Survey (IT-TUS) with the Italian data collected for the European Survey on Income and Living Conditions (IT-SILC) in 2009 and 2015. After the matching, the analysis of the joint distributions of the variables shows that the quality is good. The preliminary results of the LIMTIP estimates in Italy display widespread time poverty, which translates into significant hidden poverty. The LIMTIP also reveals that the increase in the poverty rate between 2008 and 2014 was even higher that what standard poverty measures report.

Combining absolute and relative poverty: income poverty measurement with two poverty lines.

I study income poverty indices in a framework considering two poverty lines: one absolute line capturing subsistence and one relative line capturing social exclusion. In this framework, a set of basic axioms a la Foster and Shorrocks (Econometrica 59(3): 687–709, 1991) characterizes the class of hierarchical indices. This is a class of additive indices for which the poverty contribution of any individual depends on both her income and the income standard in her society. The key feature of hierarchical indices is to grant some form of precedence to absolutely poor individuals. These indices always consider that an absolutely poor individual is poorer than an individual who is only relatively poor, regardless of the income standard in their respective societies. Classical indices are not hierarchical, except in trivial cases. As a result, they yield debatable poverty comparisons of societies having different income standards.

Multiple Dimensions of Impoverishment in Iran

Concerning the demands of Sen’s (1984) Capability Approach to the assessment of human well-being, we estimate multidimensional poverty and compare the results with traditional measures of income poverty in Iran. We detect poverty in urban and rural Iran over 1999-2007, a period with relatively high GDP growth. The results reveal that the pace of income poverty reduction is much faster than the pace of multidimensional poverty alleviation. The pace of poverty reduction is much slower in rural areas than in urban areas and the capital city, Tehran. Hence, inequality between rural and urban areas increased over the time. We also show how policymakers may benefit from applying the multidimensional approach in targeting the subgroups by the most deprived aspects.

Income poverty measurement in India: defining group-specific poverty lines or taking preferences into account?

We study absolute income poverty measurement when households differ in preferences and face different prices. The difficulty arising from price heterogeneity is typically solved using equivalent income, but the choice of the reference price vector remains arbitrary. We provide a way to solve this arbitrariness problem by making the poverty measure consistent with preferences: a household qualifies as poor if and only if she prefers the poverty line bundle to her current consumption bundle. We then prove that defining group/region specific poverty lines is another way of recovering consistency with preferences, provided one uses the headcount ratio. Comparing the resulting three approaches using Indian data, we show that the different approaches lead to different poverty conclusions. We find that not taking preferences into account leads to severely underestimating urban poverty.

Childhood poverty and deprivation at the starting gate in France. Examples using Elfe survey

Income has been increasingly criticized as an indicator of childhood living conditions, especially at young ages. In this paper, we present a picture of poverty and multi-dimensional deprivation of children in France, around the time of their birth and during the first year of life. To do so, we use both an income poverty measure as well as a multiple deprivation approach, applied to a nationally representative survey of over 18,000 children born in France in 2011 (the Elfe cohort). We examine four dimensions of children's daily lives : material conditions ; parenting ; housing conditions ; and extreme housing conditions. Our results show that income poverty does not always overlap with deprivation : some children live in income-poor households without being deprived in the dimensions we study, and vice versa. Notably, we find only a small overlap between extreme housing deprivation or parental involvement and income poverty. Furthermore, we show that the population groups most at risk of deprivation in early life vary according to the dimension considered, and are distinct from the determinants of income poverty. For example, while single motherhood is the main driver of income poverty, it is not associated with an increased risk of housing deprivation nor with low parental involvement, when other socio-demographic characteristics are controlled for. This approach therefore adds more precision and nuance to our understanding of child poverty at very young ages in France.

Community-based welfare targeting and political elite capture: Evidence from rural China

Abstract Using nationally representative rural household survey data from the 2013 China Household Income Project (CHIP) and decomposable targeting differential measures, this article systematically evaluates rural Dibao’s targeting performance based on both income and multidimensional poverty measures, and investigates the effects of political elite capture in its community-based targeting (CBT) implementation. We found that rural Dibao’s targeting performance was quite poor based on income poverty standards. When based on multidimensional poverty, Dibao’s targeting performance was better than based on income poverty. Dibao’s intra-village targeting accounted for more of its targeting performance than inter-village targeting. We also found political elite capture effects to exist for both Dibao participation and transfer value received. Moreover, the political elite capture effect from close relatives was larger in magnitude than that from household members. Having a household member being a village leader in the village of residence had no significant elite capture effect, whereas having members with a political leader position outside the village of residence or being a non-leader political party member was associated with a greater chance of welfare participation. These findings suggest that targeting errors in developing countries’ CBT welfare programs such as China’s rural Dibao is still substantial and political elite capture may be one important reason for them.

Identifying People in Poverty: A Multidimensional Deprivation Measure for the EU

In this article, I propose a multidimensional deprivation measure of poverty for the EU with the aim of improving the measurement performance of existing deprivation scales. The paper stands on the claim that a deprivation measure can be adequate, both conceptually and empirically, to capture poverty in the EU defined in Townsendian terms. Yet existing deprivation scales have three conceptual problems such as data-driven specification, neglected dimensionality and missing dimensions, and four data problems such as limited extent, cross-cultural equivalization, behavioral choices and reporting error. To address conceptual problems, I offer a concept-led methodology to construct a multidimensional measure. To address data problems, I apply a post-hoc adjustment strategy using dual criteria of income poverty and financial strain. The proposed measure has four dimensions, namely needs for basic goods, health, education, leisure and social relationships, where each dimension is evaluated separately with relevant scales. When compared to the formal EU 2020 poverty target measure, the proposed measure is more likely to capture people with needs and lower resources as well as those in less affluent countries than those in more affluent countries. The (adjusted) proposed measure can be used as a stand-alone indicator to identify a target population for policy; or the unadjusted proposed measure can be combined with an income poverty measure to identify a worst-off group within that target population.

Inequidad en el acceso a salud en Chile: estudio multifactorial basado en la Encuesta CASEN del año 2013

Objetivo: El estudio busca describir la inequidad en el acceso a salud entre los Servicios de Salud de Chile, evidenciando posibles estructuras de inequidad a nivel territorial mediante análisis multifactoriales. Método: Corresponde a un estudio descriptivo de corte cuantitativo. Se emplea una estrategia estadística exploratoria basada en Análisis de Correspondencias Múltiples (ACM) con los datos de la Encuesta CASEN del año 2013. La unidad de información del estudio es el servicio de salud. El análisis de la inequidad se hizo empleando los indicadores de acceso al sistema de salud y a prestaciones de salud incluidos en la medida multidimensional de pobreza, incorporada en esta versión de la encuesta CASEN. Como indicadores de desigualdad social, se utilizó el quintil de ingreso de la población y la medida de pobreza por ingresos. Resultados: Si bien hay diferencias estadísticamente significativas en las características demográficas y socioculturales de la población que habita las áreas de cobertura de los servicios de salud a lo largo del país, existe poca claridad en la conformación de estructuras de inequidad, lo que se aleja de lo buscado inicialmente. Lo anterior se confirma en los Análisis de Correspondencias Múltiples. Conclusiones: Los datos sectoriales de salud, provenientes de la CASEN 2013, no permiten establecer la existencia de inequidad en acceso a salud a nivel de los servicios de salud del país.

Income Inequality and Chronic Health Conditions: A Multilevel Analysis of the U.S. States

ABSTRACTRecently, scholarly work has examined the effect of rising income inequality on health outcomes. However, this work is somewhat inconclusive. The mechanisms that could produce such an association are still being sorted out. Much of this work focuses on mortality outcomes with little attention to how this process operates for actual health conditions, including chronic health problems—arguably the main public health concerns of the developed world. In a series of multilevel binary logistic regression models using data from the 2005 and 2007 Behavioral Risk Factor Surveillance System, we examine the association between state-level income inequality, poverty, and social welfare measures on spending and policy to examine the association between these factors for three chronic health outcomes: diabetes, hypertension, and coronary heart disease. We find that income inequality is conditionally positively related only to the diagnosis of diabetes and hypertension, and only in 2007. However, absolute poverty is related to the outcome across all three dependent variables. Certain social welfare measures attenuate the effects of both income inequality and absolute poverty, suggesting that some policies reduce this association.

A new formulation of the Dagum distribution in terms of income inequality and poverty measures

We provide new formulations of the Dagum family (Dagum, 1977), widely appreciated to model the income distribution, by making its parameters directly interpretable in terms of income median, inequality and poverty measures. The novelty is that the new distributions still belong to the class of Dagum distributions and enjoy its properties, but more the new parameters have a clear economic meaning. So the effects of determinants can be evaluated, directly and simultaneously, on measures of strategic relevance. This may be attractive since it helps policy makers to determine the appropriate response to the determinants of inequality and poverty. The peculiarities of three special cases are discussed and exemplified on real data from the Survey on Household Income and Wealth provided by the Bank of Italy.