Chronic poverty and disability in Latin America: the case of Chile, Colombia and Peru

BackgroundThe use of multidimensional poverty measures is becoming more common for measuring the living standards of older people. However, the pathways into poverty are relatively unknown, nor is it known how this affects the length of time people are in poverty for.MethodsUsing Waves 1 to 12 of the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey, longitudinal analysis was undertaken to identify the order that key forms of disadvantage develop – poor health, low income and insufficient education attainment – amongst Australians aged 65 years and over in multidimensional poverty, and the relationship this has with chronic poverty. Path analysis and linear regression models were used.ResultsFor all older people with at least a Year 10 level of education attainment earlier mental health was significantly related to later household income (p = 0.001) and wealth (p = 0.017). For all older people with at less than a Year 10 level of education attainment earlier household income was significantly related to later mental health (p = 0.021).When limited to those in multidimensional poverty who were in income poverty and also had poor health, older people generally fell into income poverty first and then developed poor health.The order in which income poverty and poor health were developed had a significant influence on the length of time older people with less than a Year 10 level of education attainment were in multidimensional poverty for. Those who developed poor health first then fell into income poverty spend significantly less time in multidimensional poverty (−4.90, p < .0001) than those who fell into income poverty then developed poor health.ConclusionKnowing the order that different forms of disadvantage develop, and the influence this has on poverty entrenchment, is of use to policy makers wishing to provide interventions to prevent older people being in long-term multidimensional poverty.

In this paper, we use a multidimensional framework to characterise child poverty in the UK. We examine the interdependencies amongst the different dimensions of multidimensional poverty and the relationship between multidimensional poverty and income poverty. We also explore the links between multidimensional poverty, income poverty and children's cognitive and non‐cognitive development. Our findings suggest that multidimensional poverty identifies many but not all of the same children classified using standard income poverty measures. Approximately 20 per cent of children are classified as poor on one measure but not the other. Children in workless households and ethnic minority children face the highest odds of growing up in both multidimensional poverty and income poverty. We find similar levels of persistence in multidimensional poverty and income poverty, with 17 per cent (18 per cent) of children experiencing persistent multidimensional (income) poverty and 10 per cent of children experiencing both persistent multidimensional poverty and persistent income poverty. Multidimensional poverty (both episodic and persistent) also has a detrimental impact on children's development over and above the negative impact of income poverty.

The 2030 Agenda has provided new impetus to two facets of the struggle for poverty alleviation, which is a central goal of the international development community. First, poverty is no longer viewed strictly in monetary terms, but rather as a multidimensional phenomenon. Second, the need to reduce poverty for different social groups and not just at the aggregate, national level is explicitly recognised. Against this background, this paper has three objectives: (1) to analyse the trends in multidimensional poverty in low- and middle-income countries, (2) to explore rural-urban differences in poverty over time, and (3) to assess the validity of the claim that there has been a feminisation of poverty. The analysis relies on a new indicator of multidimensional poverty, the Global Correlation Sensitive Poverty Index (G-CSPI), that incorporates three key components: education, employment and health. The G-CSPI has several methodological advantages over existing measures, including that it is an individual rather than a household-level measure of poverty, which is crucial for gender-disaggregated analysis. Regarding aggregate trends, this paper shows that both income poverty and multidimensional poverty fell between 2000 and 2012. However, the decline in (extreme) income poverty in percentage terms was twice as large as the decline in multidimensional poverty. There is significant heterogeneity in the results across regions. Multidimensional poverty declined the most in Asia, converging towards the relatively low levels of Latin America and Europe, while sub-Saharan Africa’s slow progress further distanced it from other regions. These findings point to the existence of poverty traps and indicate that more efforts are needed to eradicate poverty. Regarding the urban-rural comparison, our analysis shows that poverty is predominantly a rural phenomenon: the rural G-CSPI was more than four times the urban G-CSPI. This difference remained nearly constant over time. As for the third objective, we find no gender bias in 2000 at the global level. This contrasts with the claim made in 1995 in Beijing that 70 per cent of the poor were women. However, we find that multidimensional poverty declined more among men (-18.5 per cent from 2000) than women (-15 per cent), indicating a process of feminisation of poverty. This was triggered by the decline in employment poverty, which was much slower among women. As most existing studies conclude that there was no evidence of the feminisation of poverty, this finding is new to the literature.

Impact of poverty alleviation through relocation: From the perspectives of income and multidimensional poverty

Effect of asthma on falling into poverty: the overlooked costs of illness

BackgroundThose with a low income are known to have a higher risk of developing heart disease. However, the inverse relationship – falling into income poverty after developing heart disease has not been explored with longitudinal data. This paper aims to determine if those with heart disease have an elevated risk of falling into poverty.MethodsSurvival analysis was conducted using the longitudinal Household Income and Labour Dynamics in Australia survey, between the years 2007 and 2012. The study focused on the Australian population aged 21 years and over in 2007 who were not already in poverty and did not already have heart disease, who were followed from 2007 to 2012. Cox regression models adjusting for age, sex and time-varying co-variates (marital status, home ownership and remoteness of area of residence) were constructed to assess the risk of falling into poverty.ResultsFor those aged 20 who developed heart disease, the hazard ratio for falling into income poverty was 9.24 (95 % CI: 8.97–9.51) and for falling into multidimensional poverty the hazard ratio was 14.21 (95 % CI: 13.76–14.68); for those aged 40 the hazard ratio for falling into income poverty was 3.45 (95 % CI: 3.39–3.51) and for multidimensional poverty, 5.20 (95 % CI: 5.11–5.29); and for those aged 60 the hazard ratio for falling into income poverty was 1.29 (95 % CI: 1.28–1.30) and for multidimensional poverty, 1.52 (95 % CI: 1.51–1.54), relative those who never developed heart disease. The risk for both income and multidimensional poverty decreases with age up to the age of 70, over which, those who developed heart disease had a reduced risk of poverty.ConclusionFor those under the age of 70, developing heart disease is associated with an increased risk of falling into both income poverty and multidimensional poverty.

The influence of contextual and household factors on multidimensional poverty in rural Vietnam: A multilevel regression analysis

In order to investigate the Asian Development Bank’s (ADB) finding of increasing trend in income poverty in China since 2000, this paper studies income and multidimensional poverty in China between 2000 and 2011 using China Health and Nutrition Survey data. It is observed the ADB proposed approach, adjusted for vulnerability, demonstrates an upward trend in income poverty. Income poverty is decreasing, however, for the World Bank’s poverty cut-offs ($1.25 or $1.90). To measure multidimensional poverty, along with income (with ADB’s adjusted Asian poverty line and World Bank’s poverty lines), other indicators such as health, education and living standards are considered in this paper. The evident disparities and diversities in rural and urban multidimensional poverty are further examined. Per capita net income, highest level of education and flush toilet are found to be major contributors to both rural and urban poverty. The rural–urban disparity in terms of mild and moderate poverty appears to have decreased in the period before 2009, however, there have been increases since then, and the gap in terms of severe poverty remained quite high in this decade. We find that food insecurity does not play a major role in the rural–urban disparity in poverty. In the recent period, health insurance has become more prominent in explaining urban destitution, while the rural population is found to be more vulnerable to income fluctuations. Our results also show long-term poverty to be highly influenced by health. Our findings raise questions about the adequacies in the provision of health insurance and the quality of education, particularly in rural China.

Poverty is no longer a problem of income alone. Healthy poverty and capacity poverty have become key factors affecting the poverty reduction effectiveness. Based on “double cut-offs” multidimensional poverty identification method of Alkire and Foster (J Public Econ 95(7–8): 476–487, 2011), this paper proposes a “triple cut-offs” identification method of multidimensional poverty reduction effectiveness, and construct the chronic multidimensional poverty reduction index combined with chronic thinking of Foster (in: Addison T, Hulme D, Kanbur R (eds) Poverty dynamics: interdisciplinary perspectives. Oxford University Press, Oxford, pp 59–76, 2009). And this index can comprehensively and systematically measure the China’s multidimensional poverty reduction effectiveness in terms of both poverty alleviation and poverty returning. In this paper, we find that China's chronic multidimensional poverty alleviation index is greater than the country’s chronic poverty returning index, and the chronic multidimensional poverty alleviation/returning index in rural and western regions is greater than that in its cities and other regions in China. The chronic poverty alleviation of per capita net income and medical insurance have contributed a lot to the overall chronic multidimensional poverty alleviation of China’s rural residents, while poverty returning caused by health and housing difficulties has contributed a lot (48.14%) to the chronic multidimensional poverty alleviation of the country’s urban residents. These findings can provide more targeted guidance for poverty governance.

BackgroundThis paper aimed to identify whether high psychological distress is associated with an increased risk of income and multidimensional poverty amongst older adults in Australia.MethodsWe undertook longitudinal analysis of the nationally representative Household Income and Labour Dynamics in Australian (HILDA) survey using modified Poisson regression models to estimate the relative risk of falling into income poverty and multidimensional poverty between 2010 and 2012 for males and females, adjusting for age, employment status, place of residence, marital status and housing tenure; and Population Attributable Risk methodology to estimate the proportion of poverty directly attributable to psychological distress, measured by the Kessler 10 scale.ResultsFor males, having high psychological distress increased the risk of falling into income poverty by 1.68 (95% CI: 1.02 to 2.75) and the risk of falling into multidimensional poverty by 3.40 (95% CI: 1.91 to 6.04). For females, there was no significant difference in the risk of falling into income poverty between those with high and low psychological distress (p = 0.1008), however having high psychological distress increased the risk of falling into multidimensional poverty by 2.15 (95% CI: 1.30 to 3.55). Between 2009 and 2012, 8.0% of income poverty cases for people aged 65 and over (95% CI: 7.8% to 8.4%), and 19.5% of multidimensional poverty cases for people aged 65 and over (95% CI: 19.2% to 19.9%) can be attributed to high psychological distress.ConclusionsThe elevated risk of falling into income and multidimensional poverty has been an overlooked cost of poor mental health.

The reality of disability: Multidimensional poverty of people with disability and their families in Latin America

Multidimensional poverty as opposed to one-dimensional or income poverty, relying on capabilities, it measures deprivation in the dimensions needed by households. Alkier and Foster calculated multidimensional poverty in three dimensions: education, health, and living standards, and then, inspired by this approach, researchers have considered dimensions commensurate with their most important needs and deprivations. Following the Alkier and Foster method, the present study has used the dimensions of health, education, dwelling, employment and living standards with the aim of measuring the multidimensional poverty index in Khuzestan province for 1390 and 1395. Findings indicate that the size of multidimensional poverty in Khuzestan province in the two years under study is 25 and 28 percent respectively, which is higher than the national average and the severity of poverty is 34/4 and 34/7 percent. The most deprivation is in the dimensions of employment, health, dwelling, living standards, respectively. Multidimensional poverty as opposed to one-dimensional or income poverty, relying on capabilities, it measures deprivation in the dimensions needed by households. Alkier and Foster calculated multidimensional poverty in three dimensions: education, health, and living standards, and then, inspired by this approach, researchers have considered dimensions commensurate with their most important needs and deprivations. Following the Alkier and Foster method, the present study has used the dimensions of health, education, dwelling, employment and living standards with the aim of measuring the multidimensional poverty index in Khuzestan province for 1390 and 1395. Findings indicate that the size of multidimensional poverty in Khuzestan province in the two years under study is 25 and 28 percent respectively, which is higher than the national average and the severity of poverty is 34/4 and 34/7 percent. The most deprivation is in the dimensions of employment, health, dwelling, living standards, respectively. Multidimensional poverty as opposed to one-dimensional or income poverty, relying on capabilities, it measures deprivation in the dimensions needed by households. Alkier and Foster calculated multidimensional poverty in three dimensions: education, health, and living standards, and then, inspired by this approach, researchers have considered dimensions commensurate with their most important needs and deprivations. Following the Alkier and Foster method, the present study has used the dimensions of health, education, dwelling, employment and living standards with the aim of measuring the multidimensional poverty index in Khuzestan province for 1390 and 1395. Findings indicate that the size of multidimensional poverty in Khuzestan province in the two years under study is 25 and 28 percent respectively, which is higher than the national average and the severity of poverty is 34/4 and 34/7 percent. The most deprivation is in the dimensions of employment, health, dwelling, living standards, respectively. Multidimensional poverty as opposed to one-dimensional or income poverty, relying on capabilities, it measures deprivation in the dimensions needed by households. Alkier and Foster calculated multidimensional poverty in three dimensions: education, health, and living standards, and then, inspired by this approach, researchers have considered dimensions commensurate with their most important needs and deprivations. Following the Alkier and Foster method, the present study has used the dimensions of health, education, dwelling, employment and living standards with the aim of measuring the multidimensional poverty index in Khuzestan province for 1390 and 1395. Findings indicate that the size of multidimensional poverty in Khuzestan province in the two years under study is 25 and 28 percent respectively, which is higher than the national average and the severity of poverty is 34/4 and 34/7 percent. The most deprivation is in the dimensions of employment, health, dwelling, living standards, respectively.

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage.

Intensity of Time and Income Interdependent Multidimensional Poverty: Well-Being and Minimum 2DGAP – German Evidence

Dynamics of Multidimensional Poverty and Uni‐dimensional Income Poverty: An Evidence of Stability Analysis from China