Official Poverty Measure Research Articles

Multidimensional child poverty in South Korea: developing measures to assess progress towards the sustainable development goals

This article presents the development of a measure to assess the prevalence and patterning of multidimensional child poverty in South Korea. The first goal of UN’s Sustainable Development Goals (SDGs) is to reduce poverty in all its dimensions, and countries are increasingly developing their own measures of multidimensional poverty. This flourishing of different measures presents challenges for international comparisons. The article applies an internationally-validated method of assessing multidimensional poverty to demonstrate its suitability for use in a high-income Asian economy. Multidimensional child poverty is assessed by combining data on child material deprivation with their household income. Using data from the 2018 Korean National Children Survey, we show that child material deprivation is higher (15%) than income poverty (12%). When measured using a combined measure of material deprivation and income, around one in every three children in Korea were found to be either poor or vulnerable to poverty. These findings show that the official monetary poverty measure on its own may understate the percentage of children unable to afford necessities in Korea, as envisioned by international targets like the SDGs. In terms of policy, analysis of individual deprivations suggests that a combination of in-kind benefits such as vouchers for leisure activities or education and asset-building programmes as well as cash transfers are needed for tackling child poverty.

The Effect of Elevating the Supplemental Poverty Measure on Government Program Eligibility and Spending

Abstract A recent National Academy of Sciences report recommends elevating the Supplemental Poverty Measure (SPM) to the “nation’s headline poverty statistic.” I project how making the SPM the official poverty measure would affect eligibility for government assistance programs whose eligibility thresholds are tied to the official poverty line. Making the SPM the official poverty measure would increase the poverty line for a family of four by 20 percent in 2024. The eligibility threshold for a family of four would consequentially increase by $8320 for the Supplemental Nutrition Assistance Program (SNAP), $8512 for Medicaid adults, and by larger amounts for Medicare Part D Low Income Subsidies, the National School Lunch Program, and Affordable Care Act premium subsidies (once temporarily relaxed eligibility rules are restored in 2026). Effects on eligibility thresholds would grow over time because the SPM thresholds grow faster over time than the current official thresholds. As a result of the higher eligibility thresholds, I estimate that in 2024 SNAP would cover 2.0 million additional households with spending rising by $2.6 billion, and that Medicaid would cover 1.3 million additional recipients with spending rising by $5.6 billion.

Patterns of Multidimensional Poverty in the United States

The accurate accounting of where and for whom deprivations occur is fundamental to addressing poverty. In the United States, the official poverty measure considers only a person’s income, although poverty is increasingly understood internationally as a set of multiple, interlinked deprivations. This article introduces a decomposable multidimensional poverty (MDP) measure that addresses these shortcomings by using thirteen American Community Survey microdata indicators to identify education, health, housing, and economic security deprivations for individuals. In 2017, the national poverty rate was 13.7 percent when measured using MDP and 13.1 percent using official poverty. Although similar at the national scale, Hispanic, Asian, and older persons had higher poverty rates using the multidimensional measure, whereas Black and young persons had higher rates when using official poverty. MDP tended to be higher than official poverty in dense urban areas, whereas official poverty tended to be higher in rural areas. Further, MDP was a stronger correlate with COVID-19 death rates than official poverty through the first three waves of the pandemic. The design of MDP recognizes that individuals can experience poverty in different ways and provides a more holistic view of people and places.

Work Hours Volatility and Child Poverty: The Potential Mitigating Role of Safety Net Programs

Abstract Despite established links among persistent unemployment, low wages, and children’s economic well-being, social scientists have yet to document how variability in work hours is linked to child poverty. Our knowledge of the safety net’s heterogeneous responses to work-hour instability is also limited. This is of critical importance for scholars and policymakers. Using nationally representative data collected every 4 months, this paper examines how intra-year work-hour volatility is related to child poverty, measured through both the official poverty measure (OPM) and the supplemental poverty measure (SPM). It further assesses varying degrees of buffering effects of cash, in-kind benefits, and tax transfers on income in the context of work-hour volatility. Results indicate that more than one in four households (26%) facing the greatest volatility lived under the poverty line. Black and Hispanic children, as well as those living with unpartnered single mothers, faced substantially higher variability in household market hours worked. Hispanic children experienced not only greater volatility in their caregivers’ work hours but also higher poverty level, even after taking government programs into account. In-kind benefits are more effective in buffering household income declines resulting from unstable work hours, followed by tax transfers and cash benefits. The effectiveness of near-cash benefits is particularly salient among Black children and children of single mothers. These results provide new evidence to inform policy discussions surrounding the best ways to help socioeconomically disadvantaged families to retain benefits and smooth their income in the face of frequent variation in work hours and, thus, earnings.

The dynamic nature of poverty and food insecurity among older adults: Evidence from the Health and Retirement Study

AbstractUsing data from the Health and Retirement Study, this paper examines the dynamics of food insecurity for older adults over the past two decades and how it relates to different poverty measures. The results show that the Supplemental Poverty Measure predicts the likelihood of food insecurity better than the official poverty measure. Although there is no evidence that the impact of poverty on food insecurity declines with age, we find that the discrepancy between food insecurity and poverty is greater for more recent cohorts. Beyond poverty, various demographic, economic, and health characteristics also determine food insecurity among older adults.

Estimating Monthly Poverty Rates in the United States

AbstractOfficial poverty estimates for the United States are presented annually, based on a family unit's annual resources, and reported with a considerable lag. This study introduces a framework to produce monthly estimates of the Supplemental Poverty Measure and official poverty measure, based on a family unit's monthly income, and with a two‐week lag. We argue that a shorter accounting period and more timely estimates of poverty better account for intra‐year income volatility and better inform the public of current economic conditions. Our framework uses two versions of the Current Population Survey to estimate monthly poverty while accounting for changes in policy, demographic composition, and labor market characteristics. Validation tests demonstrate that our monthly poverty estimates closely align with observed trends in the Survey of Income & Program Participation from 2004 to 2016 and trends in hardship during the COVID‐19 pandemic. We apply the framework to measure trends in monthly poverty from January 1994 through September 2021. Monthly poverty rates generally declined in the 1990s, increased throughout the 2000s, and declined after the Great Recession through the onset of the COVID‐19 pandemic. Within‐year variation in monthly poverty rates, however, has generally increased. Among families with children, within‐year variation in monthly poverty rates is comparable to between‐year variation, largely due to the average family with children receiving 37 percent of its annual income transfers in a single month through one‐time tax credit payments. Moving forward, researchers can apply our framework to produce monthly poverty rates whenever more timely estimates are desired.

Does it matter which poverty measure we use to identify those left behind? Investigating poverty mismatch and overlap for Botswana

This study offers the first attempt in Botswana and adds to the limited literature on poverty mismatch and overlaps in Sub-Saharan Africa. Using the 2015/16 Botswana multi-topic household survey data, the study compares the country’s current official monetary poverty measure with an individual-level multidimensional poverty measure. The results show that multidimensional poverty levels are higher than monetary poverty levels. The results also reveal that significant mismatches and overlaps exist, suggesting that individuals experiencing monetary and multidimensional poverty are not the same. However, the mismatch size and overlaps vary across different subgroups of the populations and place of residence. The econometric estimation results show that age, household size, household head’s education status, household head’s employment status, and location (place of residence) influence poverty mismatch and overlap in Botswana. The findings suggest the need to go beyond traditional monetary poverty measure and complement it with multidimensional poverty measure to identify those left behind. The results are critical for policy interventions, especially for monitoring the trends, understanding poverty dynamics, and targeting social assistance programmes.

Fixing Errors in a SNAP: Addressing SNAP Underreporting to Evaluate Poverty

Since 1969, the official poverty measure has remained largely unchanged, despite substantial changes in the social safety net. This paper proposes a methodology for creating a buildable replacement to the official poverty measure, starting with market-based income, incorporating social insurance income, and building toward the Supplemental Poverty Measure (SPM). While all components would not be available for the full time series, this approach would keep the unit of analysis constant, allow thresholds to vary by geography, and allow full understanding of the role of government taxes and transfers on poverty rates over time.

Disability Considerations for Measuring Poverty in Canada Using the Market Basket Measure

Persons with disability (PWD) in Canada experience disproportionately high poverty rates. Poverty measures are often used to benchmark income assistance levels and social policies across Canada. The Market Basket Measure (MBM) is the official poverty measure in Canada that accounts for differences in family composition and geography. It does not, however, account for cost-incurring factors like disabilities, despite the evidence of differences in daily living costs. PWD experiencing poverty have additional needs to reduce barriers to full participation in society that can translate to higher basic costs for daily living. Given that poverty measures like the MBM may assess eligibility for income support or eligibility for public housing, these measures need to reflect how the cost of living differs for PWD. To critically analyze disability-specific considerations for the Canadian poverty line, we assess the MBM within the context of persons with disabilities. To identify differences in consumption patterns and family composition for PWD, a population based cross-sectional analysis was conducted using data from the 2017 Canadian Survey on Disability. Analysis assessed for bias within the MBM based on the basket contents, family composition and disability severity. PWD experience two times higher poverty rates, worse housing outcomes and incur higher and additional expenses for basic needs of daily living than persons without disability. The MBM underestimates the true poverty rate for persons with disabilities as it does not account for all their additional costs and does not represent their average family composition.

Cost of Living Variation, Nonmetropolitan America, and Implications for the Supplemental Poverty Measure.

Poverty scholarship in the United States is increasingly reliant upon the Supplemental Poverty Measure (SPM) as opposed to the Official Poverty Measure of the United States for research and policy analysis. However, the SPM still faces several critiques from scholars focused on poverty in nonmetropolitan areas. Key among these critiques is the geographic adjustment for cost of living employed in the SPM, which is based solely upon median rental costs and pools together all nonmetropolitan counties within each state. Here, we evaluate the current geographic adjustment of the SPM using both microdata and aggregate data from the American Community Survey for 2014–2018. By comparing housing costs, tenure, and commuting, we determine that median rent is likely an appropriate basis for geographic adjustment. However, by demonstrating the wide variability between median rents of nonmetropolitan counties within the same state, we show that the current operationalization of this geographic adjustment could be improved through the use of more-specific categories such as metropolitan adjacency or Rural Urban Continuum Codes.

Ending Child Poverty by Investing in Children and Families.

Ending Child Poverty by Investing in Children and Families.

The Extra Costs Associated With Living With a Disability in the United States

People with disabilities encounter many financial expenses that those without disabilities do not incur. In this article, we provide estimates of the extra costs associated with living with a disability in the United States. Drawing on four nationally representative surveys, we estimate that a household containing an adult with a work disability requires, on average, 29% more income (or an additional $18,322 a year for a household at the median income level) to obtain the same standard of living as a comparable household without a member with a disability. Single adults with disabilities are estimated to have higher costs than those with disabilities who are married, and adults with cognitive impairments are estimated to have higher costs compared to those with other kinds of impairments. We further calculate the federal poverty rate for households that include adults with disabilities adjusted for the direct additional costs of disability. The rate rises from 24% to 35% after adjusting for the extra costs of disability, which would result in an estimated 2.2 million more people with disabilities counted as poor. This suggests that the official poverty measure in the United States substantially underestimates the degree of deprivation experienced by people with disabilities.

Children and Multidimensional Poverty: Four Measurement Strategies

Empirically, official multidimensional measures of poverty often show children to be the poorest age group. Such poverty measures and their analysis can be used to directly inform policies to reduce children’s multiple deprivations. This paper introduces methods to produce official national statistics on multidimensional poverty that inform child-focused anti-poverty policies. In doing so, it recognises the importance of parsimonious, consistent measures, given practical constraints such as policy makers’ time. The paper does not recommend constructing several disjoint poverty measures which cannot be straightforwardly interpreted and used alongside one another, as these may create confusion or dilute policy attention. To create a compact and high-information measurement platform, the paper introduces four measurement strategies that have been used to directly uncover policy-relevant data on children’s experience of multidimensional poverty, and that are consistent with official population-level statistics. The four are as follows: (1) Include children’s deprivations as indicators of multidimensional poverty in national measures. (2) Disaggregate multidimensional poverty indices and their associated information platform to compare children and adults. (3) Analyse individual child deprivations and explore gendered and intra-household inequalities. (4) Construct an individual measure of child multidimensional poverty that is directly linked to the official national measure, but contains additional indicators across the life course of children. The paper illustrates these four strategies and the child-relevant statistics they yield, using examples from official poverty measures and previous research. It discusses the strengths and challenges of each method from conceptual, policy, and technical perspectives, and examines how they can be used for descriptive and prescriptive purposes in line with the Sustainable Development Goals.

Family and household sources of poverty for Black, Hispanic, and White newborns

AbstractObjectiveTo understand the importance of family and household structure, including cohabiting partners and nonkin adults, in explaining Black‐White versus Hispanic‐White newborn poverty disparities in the United States.BackgroundThe official poverty measure (OPM) has typically been used in scholarly studies of newborn and childhood poverty, but this measure excludes cohabitors' and nonkin household members' presence and income. Both are likely to have poverty‐preventing roles when a birth is nonmarital.MethodA household poverty measure inclusive of all household members is compared to the OPM, using data on households of White, Black, and Hispanic newborns from the 2005–2017 American Community Survey (N = 342,048). Regression decompositions are used to investigate the roles of mother's education and partner and other coresident adult presence and resources.ResultsLower maternal educational attainment explains most of the Hispanic‐White poverty disparity at birth. The prevalence and poverty‐alleviating effectiveness of cohabitation and living with other adults, however, is greater for Hispanic than for Black unmarried mothers, and is greater for foreign‐born than for US‐born Hispanics.ConclusionBlack mothers' lesser access to the resources of a partner or other adults in the year of the newborn's arrival is critical in producing a remarkably high Black‐White newborn poverty disparity. Official poverty obscures the greater benefits of cohabitation and living with other adults for newborns of Hispanic mothers overall, and of foreign‐born Hispanic mothers in particular.

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.

Poverty and the Incidence of Material Hardship, Revisited.

We examine trends in seven types of material hardship, such as food and housing hardships, and how their incidence by poverty status changed over the 1992 to 2011 period. We use data from multiple panels of the Survey of Income and Program Participation and logistic regressions to examine these relationships. We find declines in four of the seven hardships, with little change or moderate increases for the others. Declines were larger for hardships more dependent on longer-term income flows, while those more sensitive to short-term income fluctuations declined by less (or increased). Notably, declines in hardship were most evident among the lowest-income groups over the period. That short-term hardships did not decline suggests that income volatility poses an important challenge for many households. Larger declines in hardship among the lowest income groups suggest a greater under-reporting of income over time and the presence of family resources not comprehensively counted in the official poverty measure.

Energy poverty. How can you fight it, if you can’t measure it?

Energy poverty is a complex and multidimensional problem, lying at the intersection between household income, energy costs and the energy efficiency of the housing stock. Despite a growing interest and several new initiatives to contrast energy poverty, there are still relevant problems regarding its definition and measurement. In this work, we review the existing definitions, measures and policies with a specific focus on Italy. We present an indicator developed in a èr Faiella and Lavecchia (2015) and recently adopted by the Government as the official measure of energy poverty for Italy. According to this indicator, in 2016 there were over 2.2 million energy-poor households or 8.6% of the total. We also introduce a new indicator of energy poverty, independent from households’ preferences, derived from the heating expenditure needed to achieve a minimum comfort level. According to this new measure, there were around 3 million fuel poor households in 2014–16 (11.7% of all households).

Income-Based and Consumption-Based Measurement of Absolute Poverty: Insights from Italy

Despite the debate about the introduction of an official absolute poverty line is growing in the EU, at the moment Italy is the only EU country providing an official measure of absolute poverty. Absolute poverty is estimated in Italy with reference to household consumption using the Household Budget Survey (HBS), but it can be estimated also relying on incomes. Focusing on the Italian experience, this article contributes to the literature and to the national and European policy debate about poverty measurement in three ways. First, a detailed review of the methodology adopted in Italy to compute absolute poverty is presented. Second, the article investigates what changes when absolute poverty is assessed relying on income (using EU-SILC data) instead than on consumption (using HBS). Third, a comparison between income-based absolute poverty and the two main indicators of poverty and social exclusion used at the EU level—at risk of poverty rate, AROP, and severe material deprivation index, SMD—is shown. Main findings are: (1) the level and the characteristics of the poor change when absolute poverty is measured with reference to income rather than to consumption; (2) the incidence of income-based absolute poverty has risen more steeply than the incidence of the AROP since the upsurge of the economic crisis in 2008; (3) a very low correlation at the individual level between the income-based absolute poverty status and the SMD status emerges, thus strongly questioning the idea of using SMD as a proxy of absolute poverty.

Small-Area Multidimensional Poverty Estimates for Tonga 2016: Drawn from a Hierarchical Bayesian Estimator

Tonga has recently adopted the consensual approach to produce its official multidimensional poverty measure. This index is computed using data from the Household’s Income and Expenditure Survey (HIES). The population of Tonga is scattered across 5 main groups of islands and high-quality spatial data is vital to inform policies. One limitation is that HIES data originate from a nationally representative survey that cannot produce reliable estimates for small areas such as constituencies, villages or blocks, and governments require highly disaggregated data to better inform policies, for example, with regard to natural disasters. This paper produces small-area estimates of poverty based on a hybrid hierarchical Bayesian (HHB) estimator, which draws on the standard hierarchical Bayes (HB) approach but uses a more efficient computation process – Hamiltonian (hybrid) Monte Carlo (HMC) – to produce the posterior distributions. The HHB estimator is then applied to Tonga’s National Population Census (2016) to present estimates down to island, constituency and block level. The results suggest that the extent of poverty is lower in Tongatapu than in Eua, Vava’u, Ha’apai and Niuas, while its prevalence is very similar (around 35%) in Eua, Vava’u and Ha’apai. Constituencies in Tongatapu show lower poverty rates than in the rest of the islands, and block-level data show a clear spatial pattern of poverty distribution in the capital Tongatapu. These are the first small-area indirect poverty estimates based on a hierarchical Bayesian model and drawn from the consensual approach (CA).

Accounting for the Impact of Medicaid on Child Poverty

US Census Bureau poverty measures do not include an explicit need for health care or insurance nor do they consider health insurance benefits to be resources. Consequently, they cannot measure the direct impact of health insurance benefits on poverty. This paper reviews conceptual and practical considerations in incorporating health benefits and needs into poverty measures. We analyze the advantages and disadvantages of various approaches including variants of the Official Poverty Measure (OPM); the Supplemental Poverty Measure (SPM); using a threshold with medical out-of-pocket (MOOP) expenditures; a Medical Care Expenditure Risk (MCER) Index; willingness to pay (WTP) for Medicaid; and the Health-Inclusive Poverty Measure (HIPM; Korenman and Remler 2016). We present estimates of Medicaid’s impacts on child poverty, based on the HIPM. This paper was prepared as a background paper for the Committee on Building an Agenda to Reduce the Number of Children in Poverty by Half in 10 Years, of the Board of Children, Youth and Families of the National Academy of Sciences. The paper was submitted in October 2017 and embargoed until the release of the Committee’s report, A Roadmap to Reducing Child Poverty, in March of 2019.