Current Population Survey Data Research Articles

Labor shortages and agricultural trucking rates

AbstractIn the United States, truck rates for perishable food, the per‐mile rate charged for trucking services to move perishable food from farms to stores, rose substantially in the post‐COVID‐19 pandemic era. We argue that rising truck rates is a signal of a broader shortage of truckers, but the connection between labor shortages, rising truck rates, and a lack of trucking services has yet to be established empirically. In this paper, we develop an empirical examination based on an equilibrium job search, matching, and bargaining framework in which we estimate the role of labor shortages in accelerating driver‐wage growth, and truck rates for agricultural products. We estimate the model by combining US Bureau of Census Current Population Survey data on truck driver wages with USDA‐Agricultural Marketing Service Service data on truck rates to establish the linkage between trucker supply and the demand for trucking services. We find that the COVID‐19 pandemic was responsible for a rise in for‐hire trucker wages of some , a rise in average truck rates of nearly and that the gap between trucker‐job openings and successful matches explains a significant, but small, rise in truck rates.

Self‐Employment, the COVID‐19 Pandemic, and the Rural–Urban Divide in the United States☆

AbstractSelf‐employed individuals faced numerous challenges amid the global health and economic crisis that was the COVID‐19 pandemic. Similarly, rural and urban workers faced different challenges during the pandemic. This rural–urban disparity further complicates the impacts of self‐employment and exacerbates inequalities resulting from gender, race, ethnicity, or immigration status. This study examines the economic consequences of the COVID‐19 pandemic across these categories in the United States using Current Population Survey data from May 2020 to May 2022. Comparing the wage and self‐employment sectors across rural and urban areas, I examine the effects of individual, business, and geographic characteristics on the probability of work stoppages due to the health crisis. The analysis reveals that recovery from the pandemic was delayed among the self‐employed, while additional education and full‐time employment status can reduce work interruptions for these workers, as does working in select industries. Findings suggest that rural and urban minorities are more likely to face pandemic‐related work disruptions, with key differences between formal and informal self‐employment sectors. Specifically, self‐employed Asians/Pacific Islanders and Native Americans were more adversely affected in rural areas. The study concludes with several policy and program recommendations to assist vulnerable workers, especially in the rural self‐employment sector.

Examining the impact of topcodes adjustment on studies of gender earnings inequality in the US: evidence from March CPS data

ABSTRACT Topcoded survey data has been widely used for studies of gender earnings inequality. How robust are these studies to the choice of topcode adjustment methods? We examine this issue using the public-use March Current Population Survey data from 1979 to 2018 in the United States. In general, using more informative data and more sophisticated parametric procedure implies greater gender earnings inequality. Regression and mean decomposition analyses of gender earnings gap are quite robust to the choice of topcode correction methods. Nevertheless, topcode correction methods do matter significantly for studies of the relationship between gender earnings gap and some covariates (education) but not others (occupational characteristics). For researchers lacking access to internal data, the recommended topcode correction approach is SW/PC method. This method combines the benefits of using public data with replacement values that replicate the less topcoded internal data distribution while integrating parametric correction for the remaining topcoding bias.

EFFECTS OF COVID-19 PANDEMIC ON OLDER WORKERS’ LABOR MARKET AND RETIREMENT DECISIONS

Abstract Several studies have documented the increase in retirement since the onset of the Covid-19 pandemic. I contribute to this literature by answering two key questions that show the pandemic excess retirement is caused primarily by demand-side factors: first, using the monthly Current Population Survey (CPS) data on employment and retirement of older workers and CPS’s panel structure, I explore if older workers left their jobs and the labor force voluntarily as a part of “the great resignation”. I find that very few workers quit their jobs voluntarily, and most retirements were preceded by involuntary job loss and unemployment. Second, using the Health and Retirement Study (HRS) with its rich data on wealth, employment, and the special Covid-19 related questions included in 2020 HRS (Wave 15), I examine if older workers who experienced job loss during the pandemic retired because they were financially prepared for retirement. I find that among the small group of older workers who quit their jobs because of the pandemic, the majority did not have adequate retirement assets and their decision is more likely to be based on their health status and vulnerability during the pandemic.

PREVALENCE AND DISPARITIES OF VERY LOW-INCOME OLDER ADULT RENTERS IN US METROPOLITAN AREAS

Abstract Income eligibility for federal housing subsidies is based on HUD calculations of area median income (AMI) and family size. Frequently used measures of poverty and income do not reflect the geographic economic variations on which HUD eligibility is based. By integrating Current Population Survey (CPS) data for metropolitan-dwelling people in 2000, 2010, and 2020 with HUD yearly 50% AMI thresholds (very low-income (VLI)), this study aims to provide a novel estimate of the number of metropolitan older adult (OA) (62+) VLI renters and to compare their growth rate, rental assistance use, race, and health with other population groups. Sample weights are used to produce national estimates of four metropolitan OA subgroups: VLI renters, VLI owners, non-VLI renters, and non-VLI owners. Results show that between 2000 and 2020, the total number of metropolitan OAs increased by an estimated 84%, OA VLI renters increased by an estimated 74%, and OA VLI renters without rental assistance increased by an estimated 71%. Across all years, metropolitan VLI OA renters were more likely to be non-white, disabled, report poorer health, and receive rental and utility assistance. Approximately two-thirds of metropolitan VLI OA renters did not receive any form of rental assistance across time points. VLI OA renters without rental assistance face significant affordability challenges as metropolitan rental prices rise faster than most retirement incomes. Communities should proactively link their growing OA VLI renter populations with financial assistance and supportive services to reduce their risk of housing precarity in late life.

The effect of Medicaid expansion on the take-up of disability benefits by race and ethnicity.

Public disability programs provide financial support to 12 million working-age individuals per year, though not all eligible individuals take up these programs. Mixed evidence exists regarding the impact of Medicaid eligibility expansion on program take-up, and even less is known about the relationship between Medicaid expansion and racial and ethnic disparities in take-up. Using 2009-2020 Current Population Survey data, we compare changes in Supplemental Security Income (SSI) and Social Security Disability Insurance (SSDI) take-up among respondents with disabilities living in Medicaid expansion states to respondents with disabilities living in non-expansion states, before and after Medicaid expansion. We further explore heterogeneity by race/ethnicity. We find that Medicaid expansion reduced SSI take-up by 10% overall, particularly among White and Hispanic respondents (10% and 21%, respectively). Medicaid expansion increased SSDI take-up by 8% overall, particularly among White and Black respondents (9% and 11%, respectively). Moreover, we find that Medicaid expansion reduced the probability that respondents with disabilities had employer-sponsored health insurance by approximately 8%, suggesting that expansion may have reduced job-lock among the SSDI-eligible, contributing to the observed increase in SSDI take-up.

Understanding food insecurity risk in the United States: A longitudinal analysis

BackgroundFood insecurity, lack of consistent access to the food needed for an active, healthy life, harms population health. Although substantial biomedical evidence examines the connections between food insecurity and health, fewer studies examine why food insecurity occurs. MethodsWe propose a conceptual understanding of food insecurity risk based on institutions that distribute income—the factor payment system (income distribution stemming from paid labor and asset ownership), transfers within households, and the government tax-and-transfer system. A key feature of our understanding is 'roles' individuals inhabit in relation to the factor payment system: child, older adult, disabled working-age adult, student, unemployed individual, caregiver, or paid laborer. A second feature is that the roles of others in an individual's household also affect an individual's food insecurity risk. We tested hypotheses implied by this understanding, particularly hypotheses relating to role, household composition, and income support programs, using nationally-representative, longitudinal U.S. Current Population Survey data (2016–2019). ResultsThere were 16,884 participants (year 1 food insecurity prevalence: 10.0%). Inhabiting roles of child (Relative Risk [RR] 1.79, 95% Confidence Interval [95%CI] 1.67 to 1.93), disabled working age-adult (RR 3.74, 95%CI 3.25 to 4.31), or unemployed individual (RR 3.29, 95%CI 2.51 to 4.33) were associated with a greater risk of food insecurity than being a paid laborer. Most food insecure households, 74.8%, had members inhabiting roles of child or disabled working age-adult, and/or contained individuals who experienced job loss. Similar associations held when examining those transitioning from food insecurity to food security in year 2. ConclusionsThe proposed understanding accords with the pattern of food insecurity risk observed in the U.S. An implication is that transfer income programs for individuals inhabiting roles, such as childhood and disability, that limit factor payment system participation may reduce food insecurity risk for both those individuals and those in their household.

The impacts of U.S. right‐to‐work laws on free riding, unionization, and compensation

AbstractRight‐to‐work (RTW) laws are theorized to precipitate union decline by inducing free riding among union‐covered workers; however, this relationship has not been empirically explored. This paper uses recent policy variation and Current Population Survey (CPS) data to identify the impact of state RTW laws on union status (free riding, membership, and coverage), wages, and benefits among private and public sector workers. Doubly robust difference‐in‐difference estimates suggest RTW laws are associated with substantial increases in free riding, decreases in union membership, and decreases in union coverage. Thus, RTW laws weaken unions through combinations of increased free riding and decreased coverage, though effects vary by state and sector. While RTW laws are not associated with changes in wage differentials, state fixed effects estimates suggest that unions provide some excludable advantages to members in the face of RTW legislation, through higher earnings (union wage premium) and fringe benefits (union benefit premium).

Did pandemic unemployment benefits increase unemployment? Evidence from early state‐level expirations

AbstractDuring the 2021 pandemic year, the generosity of Unemployment Insurance benefits was expanded (Federal Pandemic Unemployment Compensation [FPUC]) and eligibility for benefits was broadened (Pandemic Unemployment Assistance [PUA]). These two programs were set to expire in September 2021. In June 2021, 18 states exited both FPUC and PUA and three states exited FPUC (but not PUA). Using Current Population Survey data and a wide range of estimation methods, we find that the flow of unemployed workers into employment increased by around two‐thirds following early exit among prime‐age workers. We also find evidence of reductions in state‐level unemployment rates, increases in employment‐populations ratios, and reductions in the share of households that had no difficulty meeting expenses.

Food stamps and America's poorest

AbstractThis paper assesses the extent to which Supplemental Nutrition Assistance Program (SNAP)—one of America's largest antipoverty programs—has reached the poorest. We compute a novel measure of the floor of income, an estimated income level of the poorest individuals in society. We measure the floor with and without SNAP benefits included in family income using 29 years of Current Population Survey (CPS) data. We correct for underreporting of SNAP participation and benefits for a subset of years and examine alternative data to assess the robustness of our findings. The analysis reveals a long‐term decline in the income floor, whereas adding SNAP to income and correcting for underreporting has reversed this decline and lifted the income floor by more than 75% on average between 2011 and 2016. The declining floor and the remarkable increase in income for the poorest Americans from SNAP are not revealed by poverty headcounts, which focus on changes at the poverty threshold.

Instrumental variable estimation for functional concurrent regression models

In this work we propose a functional concurrent regression model to estimate labor supply elasticities over the years 1988 through 2014 using Current Population Survey data. Assuming, as is common, that individuals' wages are endogenous, we introduce instrumental variables in a two-stage least squares approach to estimate the desired labor supply elasticities. Furthermore, we tailor our estimation method to sparse functional data. Though recent work has incorporated instrumental variables into other functional regression models, to our knowledge this has not yet been done in the functional concurrent regression model, and most existing literature is not suited for sparse functional data. We show through simulations that this two-stage least squares approach greatly eliminates the bias introduced by a naive model (i.e. one that does not acknowledge endogeneity) and produces accurate coefficient estimates for moderate sample sizes.

COVID‐19 job loss and re‐employment among partnered parents: Gender and educational variations

AbstractObjectiveThis study examines the re‐employment prospects and short‐term career consequences for mothers and fathers who lost their jobs during the COVID‐19 pandemic.BackgroundThe pandemic recession has been dubbed a “shecession,” but few studies have explored whether mothers paid a higher or lower price upon labor market re‐entry than fathers.MethodThis study draws on March 2020–December 2022 Current Population Survey data and focuses on partnered parents with children under age 13 in the household. Exploiting four‐month panels, we use multi‐level discrete‐time event history models to predict re‐employment and linear regression models to predict job‐level wage upon re‐employment, while controlling for a wide array of factors.ResultsPartnered fathers were more likely than partnered mothers to find re‐employment during the pandemic. The gender gap in re‐employment was concentrated only among parents without a bachelor's degree and persisted when all controls were held constant. Moreover, upon re‐employment, fathers had higher job‐level wages than mothers, which was consistent across educational levels. Even with the same job‐level wage before labor market exit, mothers were penalized on re‐entry relative to fathers and this penalty was rooted in gendered job segregation.ConclusionThis study extends previous research by analyzing re‐employment and a critical material outcome for parents (i.e., job‐level wage upon re‐employment) during the entire pandemic, including the “new normal” (late 2022). The results reveal the intersectional inequalities in family and work: Compared to fathers, mothers, particularly less‐educated mothers, paid a higher price for their time out of work during the pandemic.

AN INDIVIDUAL LEVEL INVESTIGATION ON THE RELATIONSHIP BETWEEN BEING A SINGLE PARENT AND POVERTY

Single parenting has been a growing type of family structure both in Western countries and Eastern ones. Changing economic and social conditions have contributed to this growth. Poverty or worsening welfare is also a growing concern in society. This study, therefore, investigates whether being a single parent is associated with a poverty risk. To do so, The Current Population Survey (CPS) which is a commonly used data source applied in social science from Integrated Public Use Microdata Series (IPUMS) database were utilised. Being a reliable source with large sample sizes and various subjects covered in the U.S. population makes IPUMS widely preferable data source with micro level data on individuals and household. This empirical investigation, therefore, relies on IPUMS CPS data to explain poverty risk of single parents. Findings reveal that being a single parent is significantly associated with being below the poverty line. Additionally, sex, age, employment status, education level, race, and citizenship status were found to be significant to explain poverty.

Potential gaps in income support policies for those in poor health: The case of the earned income tax credit—A cross sectional analysis

BackgroundThe federal Earned Income Tax Credit (EITC) is the primary income support program for low-income workers in the U.S., but its design may hinder its effectiveness when poor health limits, but does not preclude, work. MethodsCross-sectional analysis of nationally-representative U.S. Census Current Population Survey (CPS) data covering 2019. Working-age adults eligible to receive federal EITC were included in this study. Poor health, as indicated by self-report of at least one problem with hearing, vision, cognitive function, mobility, dressing and bathing, or independence, was the exposure. The main outcome was federal EITC benefit category, categorized as no benefit, phase-in (income too low for the maximum benefit), plateau (maximum benefit), phase-out (income above threshold for maximum benefit), or earnings too high to receive any benefit. We estimated EITC benefit category probabilities by health status using multinomial logistic regression. We further examined whether other government benefits provided additional income support to those in poor health. Results41,659 participants (representing 87.1 million individuals) were included. 2,724 participants (representing 5.6 million individuals) reported poor health. In analyses standardized over age, gender, race, and ethnicity, those in poor health, compared with those not in poor health, were more likely to be in the no benefit (2.40% vs. 0.30%, risk difference 2.10 percentage points [95%CI 1.75 to 2.46 percentage points]), and phase-in (9.28% vs. 2.74%, risk difference 6.54 percentage points [95%CI 5.82 to 7.26 percentage points]) categories. Differences in resources by health status persisted even after accounting for other government benefits. ConclusionsEITC program design creates an important gap in income support for those for whom poor health limits work, which is not closed by other programs. Filling this gap is an important public health goal.

Tax reforms and elasticity of taxable income: estimation using the current population survey

ABSTRACT Changes in taxable income can capture many of the behavioural responses to changes in tax policies. In this paper, using the publicly available Current Population Survey (CPS) data and analysing two of the most recent tax reforms (Tax Cuts and Jobs Act of 2017 and the American Taxpayer Relief Act of 2012), we provide a new estimate for the elasticity of taxable income with respect to marginal tax rates. As is common in the literature, the paper conducts a panel data analysis and compares taxable income from before and after tax reforms to estimate the elasticity. Using an instrumental variable approach, we find an elasticity of 0.81, a value that is within the range of estimates found in previous studies.

Gaps in the welfare state: A role-based model of poverty risk in the U.S.

Research clearly demonstrates that income matters greatly to health. However, income distribution and its relationship to poverty risk is often misunderstood. We provide a structural account of income distribution and poverty risk in the U.S., rooted in the 'roles' that individuals inhabit with relation to the 'factor payment system' (market distribution of income to individuals through wages and asset ownership). Principal roles are child, older adult, and, among working-age adults, disabled individual, student, unemployed individual, caregiver, or paid laborer. Moreover, the roles of other members of an individual's household also influence an individual's income level. This account implies that 1) roles other than paid laborer will be associated with greater poverty risk, 2) household composition will be associated with poverty risk, and 3) income support policies for those not able to engage in paid labor are critical for avoiding poverty. We test hypotheses implied by this account using 2019 and 2022 U.S. Census Current Population Survey data. The exposure variables in our analyses relate to roles and household composition. The outcomes relate to income and poverty risk. In 2019, 40.1 million individuals (12.7% of the population) experienced poverty under the U.S. Census' Supplemental Poverty Measure. All roles other than paid laborer were associated with greater poverty risk (p < .001 for all comparisons). Household composition, particularly more children and disabled working-age adults, and fewer paid laborers, was also associated with greater poverty risk (p < .001 for all comparisons). Five key policy areas-child benefits, older-age pensions, disability and sickness insurance, unemployment insurance, and out-of-pocket healthcare spending-represented gaps in the welfare state strongly associated with poverty risk. The role one inhabits and household composition are associated with poverty risk. This understanding of income distribution and poverty risk may be useful for social policy.

Older workers’ employment and Social Security spillovers through the second year of the COVID-19 pandemic

AbstractThe COVID-19 pandemic triggered a large and immediate drop in employment among U.S. workers, along with major expansions of unemployment insurance (UI) and work from home. We use Current Population Survey and Social Security application data to study employment among older adults and their participation in disability and retirement insurance programs through the second year of the pandemic. We find ongoing improvements in employment outcomes among older workers in the labor force, along with sustained higher levels in the share no longer in the labor force during this period. Applications for Social Security disability benefits remain depressed, particularly for Supplemental Security Income. In models accounting for the expiration of expanded UI, we find some evidence that the loss of these additional financial supports resulted in an increase in disability claiming. Social Security retirement benefit claiming is approximately 3% higher during the second year of the pandemic.

Age and Hourly Wage: How Aging affect Earning

In an aging society, people need to focus on the consequence of aging in the labor market. This paper aims to uncover the effect of aging on employees wages. To excluded the impact of the COVID-19 and inflation started at the beginning of 2020, the study is based on Current Population Survey (CPS) data collected in 2019. The author explored the issue by adopting the change in peoples age and their hourly wage in the US labor market. The study introduced several regression models, and the analysis of the data shows a positive relationship between peoples age and hourly wage. The findings also suggest that, overall, there is a tendency to raise hourly wage when peoples age increase. In addition, the condition of being White, Asian, or married has a positive effect on people's hourly wage, while being Black, female, or disabled tend to have adverse effects on their hourly wage.

National Policies on Parental Leave and Breastfeeding Breaks: Racial, Ethnic, Gender, and Age Disparities in Access and Implications for Infant and Child Health.

Parental leave and breastfeeding breaks influence the ability to initiate and continue breastfeeding. We investigated how eligibility criteria in the Family and Medical Leave Act (FMLA) and Affordable Care Act (ACA) affect access to unpaid parental leave and breastfeeding breaks and assessed affordability and alternative policy models. We used family income data to assess the affordability of unpaid leave by race and ethnicity. We used 2017-2018 US Current Population Survey data to determine the percentage of private sector workers aged 18-44 years who met the minimum hour (1250 hours of work during a 12-month period), tenure (12 months), and firm size (≥50 employees) requirements of FMLA and ACA. We analyzed eligibility by gender, race and ethnicity, and age. We also examined parental leave and breastfeeding break policies in 193 countries. Most Latinx (66.9%), Black (60.2%), and White (55.3%) workers were ineligible and/or unlikely to be able to afford to take unpaid FMLA leave. Of 69 534 workers, more women (16.9%) than men (10.3%) did not meet the minimum hour requirement. Minimum tenure excluded 23.7% of all workers and 42.2% of women aged 18-24 years. Minimum firm size excluded 30.3% of all workers and 37.7% of Latinx workers. Of 27 520 women, 28.8% (including 32.9% of Latina women) were excluded from ACA breastfeeding breaks because of firm size. Nearly all other countries guaranteed mothers paid leave regardless of firm size or minimum hours and guaranteed ≥6 months of paid leave or breastfeeding breaks. Adopting a comprehensive, inclusive paid parental leave policy and closing gaps in breastfeeding break legislation would remove work-related barriers to breastfeeding; reduce racial, ethnic, and gender inequities; and align US national policies with global norms.

Working yet Poor: A Quantitative Analysis for the United States

ABSTRACT This study uses Current Population Survey data and econometric techniques to examine whether working poor households improve their economic wellbeing by working more hours. For working households overall, full-time work puts them in a 49–78% better position than part-time work (as measured by resources-to-need and depending on methodology). For poor families, however, full-time work makes them 1.3–2.7% better off than part-time work. The latter finding reflects that the higher earnings of full-time work come at considerable cost: lower public assistance benefits and higher medical, work, and childcare expenditures. We discuss policies that may reduce these tradeoffs for poor working households.