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Capturing More Than Poverty: School Free and Reduced-Price Lunch Data and Household Income
December 2017
Working Paper Number:
carra-2017-09
Educational researchers often use National School Lunch Program (NSLP) data as a proxy for student poverty. Under NSLP policy, students whose household income is less than 130 percent of the poverty line qualify for free lunch and students whose household income is between 130 percent and 185 percent of the poverty line qualify for reduced-price lunch. Linking school administrative records for all 8th graders in a California public school district to household-level IRS income tax data, we examine how well NSLP data capture student disadvantage. We find both that there is substantial disadvantage in household income not captured by NSLP category data, and that NSLP categories capture disadvantage on test scores above and beyond household income.
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Is Subsidized Childcare Associated with Lower Risk of Grade Retention for Low-Income Children? Evidence from Child Care and Development Fund Administrative Records Linked to the American Community Survey
June 2017
Working Paper Number:
carra-2017-06
This study investigates whether low-income young children's experience of Child Care and Development Fund (CCDF)-subsidized childcare is associated with a lower subsequent likelihood of being held back in grades K-12. High-quality childcare has been shown to improve low-income children's school readiness. However, no previous study has examined the link specifically between subsidized care and grade retention. I do so here by matching information on children from CCDF administrative records to later observations of the same children in the American Community Survey (ACS). I use logistic regression to compare the likelihood of grade retention between CCDF-recipient children and non-recipient children who also appear in the ACS in the years 2008-2014 (N=2,284,857). I find strong evidence for an association between CCDF-subsidized care and lower risk of grade retention, especially among non-Hispanic Black children and Hispanic children. I also find evidence that receiving CCDF-subsidized center-based care in particular is associated with a lower risk of being held back than CCDF-subsidized family daycare, babysitter care, or relative care, again with the largest apparent benefit to non-Hispanic Black children and Hispanic children.
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DOES PARENTS' ACCESS TO FAMILY PLANNING INCREASE CHILDREN'S OPPORTUNITIES? EVIDENCE FROM THE WAR ON POVERTY AND THE EARLY YEARS OF TITLE X
January 2017
Working Paper Number:
CES-17-67
This paper examines the relationship between parents' access to family planning and the economic resources of their children. Using the county-level introduction of U.S. family planning programs between 1964 and 1973, we find that children born after programs began had 2.8% higher household incomes. They were also 7% less likely to live in poverty and 12% less likely to live in households receiving public assistance. After accounting for selection, the direct effects of family planning programs on parents' incomes account for roughly two thirds of these gains.
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Planning Parenthood: The Affordable Care Act Young Adult Provision and Pathways to Fertility
January 2017
Working Paper Number:
CES-17-65
This paper investigates the effect of the Affordable Care Act young adult provision on fertility and related outcomes. The expected effect of the provision on fertility is not clear ex ante. By expanding insurance coverage to young adults, the provision may affect fertility directly through expanded options for obtaining contraceptives as well as through expanded options for obtaining pregnancy-, birth-, and infant-related care, and these may lead to decreased or increased fertility, respectively. In addition, the provision may also affect fertility indirectly through marriage or labor markets, and the direction and magnitude of these effects is difficult to determine. This paper considers the effect of the provision on fertility as well as the contributing channels by applying difference-in-differences-type methods using the 2008-2010 and 2012-2013 American Community Survey, 2006-2009 and 2012-2013 Centers for Disease Control and Prevention abortion surveillance data, and 2006-2010 and 2011-2013 National Survey of Family Growth. Results suggest that the provision is associated with decreases in the likelihood of having given birth and abortion rates and an increase in the likelihood of using long-term hormonal contraceptives.
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Considering the Use of Stock and Flow Outcomes in Empirical Analyses: An Examination of Marriage Data
January 2017
Working Paper Number:
CES-17-64
This paper fills an important void assessing how the use of stock outcomes as compared to flow outcomes may yield disparate results in empirical analyses, despite often being used interchangeably. We compare analyses using a stock outcome, marital status, to those using a flow
outcome, entry into marriage, from the same dataset, the American Community Survey. This paper considers two different questions and econometric approaches using these alternative measures: the effect of the Affordable Care Act young adult provision on marriage using a difference-indifferences
approach and the relationship between aggregate unemployment rates and marriage rates using a simpler ordinary least squares regression approach. Results from both analyses show stock and flow data yield divergent results in terms of sign and significance. Additional analyses suggest prior-period temporary shocks and migration may contribute to this discrepancy. These results suggest using caution when conducting analyses using stock data as they may produce false negative results or spurious false positive results, which could in turn give rise to misleading policy implications.
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Who Files for Personal Bankruptcy in the United States?
January 2017
Working Paper Number:
CES-17-54
Who files for bankruptcy in the United States is not well understood. Previous research relied on small samples from national surveys or a small number of states from administrative records. I use over 10 million administrative bankruptcy records linked to the 2000 Decennial Census and the 2001-2009 American Community Surveys to understand who files for personal bankruptcy. Bankruptcy filers are middle income, more likely to be divorced, more likely to be black, more likely to have terminal high school degree or some college, and more likely to be middle-aged. Bankruptcy filers are more likely to be employed than the U.S. as a whole, and they are more likely to be employed 50-52 weeks. The bankruptcy population is aging faster than the U.S. population as a whole. Lastly, using the pseudo-panels I study what happens in the years around bankruptcy. Individuals are likely to get divorced in the years before bankruptcy and then remarry. Income falls before bankruptcy and then rises after bankruptcy.
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Developing a Residence Candidate File for Use With Employer-Employee Matched Data
January 2017
Working Paper Number:
CES-17-40
This paper describes the Longitudinal Employer-Household Dynamics (LEHD) program's ongoing efforts to use administrative records in a predictive model that describes residence locations for workers. This project was motivated by the discontinuation of a residence file produced elsewhere at the U.S. Census Bureau. The goal of the Residence Candidate File (RCF) process is to provide the LEHD Infrastructure Files with residence information that maintains currency with the changing state of administrative sources and represents uncertainty in location as a probability distribution. The discontinued file provided only a single residence per person/year, even when contributing administrative data may have contained multiple residences. This paper describes the motivation for the project, our methodology, the administrative data sources, the model estimation and validation results, and the file specifications. We find that the best prediction of the person-place model provides similar, but superior, accuracy compared with previous methods and performs well for workers in the LEHD jobs frame. We outline possibilities for further improvement in sources and modeling as well as recommendations on how to use the preference weights in downstream processing.
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Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data
January 2017
Working Paper Number:
CES-17-25
This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005 2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the United States Multi-Level Suicide Data Set (US-MSDS), the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
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Medicare Coverage and Reporting
December 2016
Working Paper Number:
carra-2016-12
Medicare coverage of the older population in the United States is widely recognized as being nearly universal. Recent statistics from the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) indicate that 93 percent of individuals aged 65 and older were covered by Medicare in 2013. Those without Medicare include those who are not eligible for the public health program, though the CPS ASEC estimate may also be impacted by misreporting. Using linked data from the CPS ASEC and Medicare Enrollment Database (i.e., the Medicare administrative data), we estimate the extent to which individuals misreport their Medicare coverage. We focus on those who report having Medicare but are not enrolled (false positives) and those who do not report having Medicare but are enrolled (false negatives). We use regression analyses to evaluate factors associated with both types of misreporting including socioeconomic, demographic, and household characteristics. We then provide estimates of the implied Medicare-covered, insured, and uninsured older population, taking into account misreporting in the CPS ASEC. We find an undercount in the CPS ASEC estimates of the Medicare covered population of 4.5 percent. This misreporting is not random - characteristics associated with misreporting include citizenship status, year of entry, labor force participation, Medicare coverage of others in the household, disability status, and imputation of Medicare responses. When we adjust the CPS ASEC estimates to account for misreporting, Medicare coverage of the population aged 65 and older increases from 93.4 percent to 95.6 percent while the uninsured rate decreases from 1.4 percent to 1.3 percent.
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State and Local Determinants of Employment Outcomes among Individuals with Disabilities
March 2016
Working Paper Number:
CES-16-21
In the United States, employment rates among individuals with disabilities are persistently low but vary substantially. In this study, we examine the relationship between employment outcomes and features of the state and county physical, economic, and policy environment among a national sample of individuals with disabilities. To do so, we merge a set of state- and county-level environmental variables with data from the 2009'2011 American Community Survey accessed in a U.S. Census Research Data Center. We estimate regression models of employment, work hours, and earnings as a function of health conditions, personal characteristics, and these environmental features. We find that certain environmental variables are significantly associated with employment outcomes. Although the estimated importance of environmental variables is small relative to individual health and personal characteristics, our results suggest that these variables may present barriers or facilitators to employment that can explain some geographic variation in employment outcomes across the United States.
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