This paper examines the association between poverty and food insecurity among children using the official measure of poverty and the newsupplemental poverty measure of the Census Bureau based on a more inclusive definition of family resources and needs. Our objective is to study whether the association between food insecurity and poverty improves with a more comprehensive measure of income and needs. We find a strong and statistically significant association between income-to-needs ratio based on the official poverty metric and food insecurity among children—particularly very low food security among children. A more inclusive measure of income-to-needs-ratio, based on the supplemental poverty measurestrengthens the association. These findings remain robust in models using longitudinal data with person fixed effects.
Poverty
Measuring the economic status of low-income individuals and families is a central focus of poverty scholars and is at the fore of much public policy debate. The stakes are substantial as changes in poverty (and poverty thresholds) influence the scale and scope of redistributive tax and transfer programs at all levels of government. In the United States, official poverty statistics are derived from the Annual Social and Economic Supplement to the Current Population Survey, a nationally representative survey of about 90,000 households. The main source of household income comes from labor-market earnings, but as highlighted in the work of UKCPR Affiliates Charles Hokeyem, Christopher Bollinger, and James Ziliak (DP2014-05), published in the Journal of the American Statistical Association, a challenge to the proper measurement of income is survey non-response. Using a restricted-access dataset that links the CPS ASEC to Social Security's Detailed Earnings Records, they show that survey non-response is not random and leads to a systematic downward bias in the official poverty rate of about 10% in an average year. Follow-up research that is forthcoming in 2019 at the Journal of Political Economy (DP2015-02), and conducted jointly with Barry Hirsch at Georgia State University, shows that earnings non-response affects broader measures of the income distribution, such as earnings inequality and gender wage gaps.
2012
Two can live as cheaply as one...but three's a crowd
To measure poverty, incomes must be made equivalent across households with different structures. In this paper, we use a very flexible ordered response model to analyze the relationship between income, demographic structure, and subjective assessments of financial wellbeing drawn from the 1991-2008 British Household Panel Survey. Our results suggest the existence of large-scale economies within marital/cohabiting couples, but substantial diseconomies from the addition of children or further adults. This pattern contrasts sharply with commonly-used equivalence scales and is consistent with explanations in terms of the capital requirements associated with additions to the core couple.
On persistent poverty in a rich country
We examine differences in income within the U.S., and the regions of persistent poverty that have arisen, using a newly assembled dataset of counties that links historical 19th century Census data with contemporaneous data. The data, along with an augmented human capital growth model, permit us to identify the roles of contemporaneous differences in aggregate production technologies and factor endowments, in conjunction with the historical roles of institutions, culture, geography, and human capital. We allow for possible cross-county factor mobility via a correlated random effects GMM estimator that identifies simultaneously the coefficients on time varying and time-invariant determinants of income. We find evidence of significant regional differences in production technologies, but our decompositions of the poor/non-poor income gap suggests that at least three fourths of the gap is explained by differences in productive factors. Persistently poor counties are different (and poorer) primarily because they have lower levels of factors of production, not because they use the factors they have less efficiently. While much of the income difference is explained by contemporary factors, the contribution of historical levels of human capital is surprisingly large. The combined contribution of historical and contemporary human capital is striking: together, they explain nearly 60 percent of the overall income gap between the persistently poor and non-poor counties.
2011
Recent developments in antipoverty policies in the United States
I survey recent developments in antipoverty policy in the United States over the past decade and examine how the safety net and tax system affects poverty and its correlates using data from the 2000 to 2010 waves of the Current Population Survey-Annual Social and Economic Supplement. Unlike the 1980s and 1990s, and until the health care overhaul in 2009, the first decade of the 21st Century was relatively tepid in terms of major transfer policy reforms. However, real spending on most major social program increased significantly, and in some cases doubled or tripled, in response to demographic shifts and the deep recession. In spite of the real growth in social insurance and means-tested transfer programs, the trends in after-tax and transfer poverty rates were little affected, and if anything, suggest the safety net has lost some of its antipoverty bite in terms of alleviating hardship among those living in deep poverty.
Cost of living and the supplemental poverty measurement
On April 28, 2011, the University of Kentucky Center for Poverty Research, in conjunction with the Brookings Institution and U.S. Census Bureau, sponsored a research forum titled Cost of Living and the Supplemental Poverty Measure at the Brookings Institution. Among the more than 60 attendees were representatives from the Assistant Secretary for Planning and Evaluation inthe Department of Health and Human Services, Agency for Healthcare Research and Quality, the Bureau of Economic Analysis, Bureau of Labor Statistics, Census Bureau, Congressional Research Service, Government Accountability Office, National Academy of Science, Office of Management and Budget, academia, and think tanks. This brief report provides the rationale and summary of the forum.
2010
The Appalachian Regional Development Act and economic change
The Appalachian Regional Development Act of 1965 is one of the longest serving place-based regional development programs in the U.S., and is the largest in terms of geographic scope. I use county-level data from the 1960 thru 2000 Decennial Censuses to evaluate the effect of ARDA on poverty rates and real per capita incomes in Appalachia. The intent to treat parameter is identified in a difference-in-difference-in-difference framework by comparing outcomes in Appalachia to her border counties. Additional knowledge of which counties were solely eligible for highway development funds under ARDA from those counties eligible for both highway as well as human development programs helps isolate the average treatment effect on the treated. The results suggest that the ARDA reduced Appalachian poverty between 1960 and 2000 by 4.2 percentage points relative to border counties, or about 10 percent on the baseline 1960 poverty rate, and real per capita incomes grew about 4 percent faster. Comparing grant eligible to grant ineligible counties suggests that about half of poverty reduction can be attributed to highway development programs, and the other half to human development programs. These anti-poverty gains were concentrated exclusively in the Central and Southern Appalachian regions.
The impact of U.S. family planning programs on fertility and mortality: Evidence from the war on poverty and Title X
More than 40 years ago, the U.S. government adopted a policy of funding domestic family planning services, and the effects of these programs have been debated ever since. Within an event-study framework, I exploit community-level variation in the timing of federal grants for family planning services under the Economic Opportunity Act (1965 to 1974) and Title X (1970 to 1980) to evaluate their impact. The results provide robust evidence that federal family planning grants reduced birth rates in funded communities by four percent within six years. I find no evidence that family planning grants reduced maternal or infant mortality rates.
Family change and poverty in Appalachia
The important points from our analyses are two-fold. First, the implications of family change for family poverty appeared to be larger in Appalachia than in non-Appalachian areas, independent of regional differences in employment opportunities, industrial structure, demographic variables, and unobserved state and county variables. Second, family effects, notably those associated with changing female headship, were estimated to be larger than those for conventional economic and human capital variables. Our simulations in fact suggested that family poverty would have been roughly 10 to 15 percent lower than the observed poverty rate if Appalachian families had not changed since 1990.
Notes on poverty traps in Appalachia
In these notes, I provide some general ideas on how to conceptualize poverty traps and speculate on their applicability to understanding Appalachian poverty. My goal is to stimulate thinking on Appalachia that exploits contemporary perspectives in economics on the sources of persistent poverty and inequality. To do this, I focus on both the theory of poverty traps as well as issues in the econometric assessment of their empirical salience.
What about these children? Assessing poverty among the 'hidden population' of multiracial children in single-mother families
Capturing the conditions of children of color living in single-parent families has become more complex due to the growing presence of interracial households. This analysis assesses the size and poverty status of single-female headed families housing multiracial children. Using data from the 2000 Census, we find that 9 percent of female-headed families house either children who are classified with more than one race or are classified as a single race different than their mother’s compared to only 3 percent of married couple families. Logistic regression analyses assessing the odds of poverty status for families finds that being a multiracial family does not constitute a uniform advantage or disadvantage for female headed households. Rather, these families, like most families of color, are more likely to experience poverty than white monoracial families. The two exceptions are White multiracial families who are more likely to be in poverty relative to this reference group and Asian multiracial families who have similar poverty rates as white monoracial families (and a lower rate than Asian monoracial families).