scholarly journals A New Infrastructure for Monitoring Social Mobility in the United States

Author(s):  
David B. Grusky ◽  
Timothy M. Smeeding ◽  
C. Matthew Snipp

The country’s capacity to monitor trends in social mobility has languished since the last major survey on U.S. social mobility was fielded in 1973. It is accordingly difficult to evaluate recent concerns that social mobility may be declining or to develop mobility policy that is adequately informed by evidence. This article presents a new initiative, dubbed the American Opportunity Study (AOS), that would allow the country to monitor social mobility efficiently and with great accuracy. The AOS entails developing the country’s capacity to link records across decennial censuses, the American Community Survey, and administrative sources. If an AOS of this sort were assembled, it would open up new fields of social science inquiry; increase opportunities for evidence-based policy on poverty, mobility, child development, and labor markets; and otherwise constitute a new social science resource with much reach and impact.

2014 ◽  
Vol 657 (1) ◽  
pp. 208-246
Author(s):  
John Robert Warren

In this article I define the main criteria that ought to be considered in evaluating the costs and benefits of various data resources that might be used for a new study of social and economic mobility in the United States. These criteria include population definition and coverage, sample size, topical coverage, temporal issues, spatial issues, sustainability, financial expense, and privacy and data access. I use these criteria to evaluate the strengths and weakness of several possible data resources for a new study of mobility, including existing smaller-scale surveys, the Current Population Survey, the American Community Survey, linked administrative data, and a new stand-alone survey. No option is perfect, and all involve trade-offs. I conclude by recommending five possible designs that are particularly strong on the criteria listed above.


Partner Abuse ◽  
2016 ◽  
Vol 7 (4) ◽  
pp. 355-460 ◽  
Author(s):  
Julia Babcock ◽  
Nicholas Armenti ◽  
Clare Cannon ◽  
Katie Lauve-Moon ◽  
Fred Buttell ◽  
...  

In the United States, the judicial system response to violence between intimate partners, or intimate partner violence (IPV), typically mandates that adjudicated perpetrators complete a batterer intervention program (BIP). The social science data has found that these programs, on the whole, are only minimally effective in reducing rates of IPV. The authors examined the social science literature on the characteristics and efficacy of BIPs. More than 400 studies were considered, including a sweeping, recently conducted survey of BIP directors across the United States and Canada. Results of this review indicate that the limitations of BIPs are due, in large part, to the limitations of current state standards regulating these programs and, furthermore, that these standards are not grounded in the body of empirical research evidence or best practices. The authors, all of whom have considerable expertise in the area of domestic violence perpetrator treatment, conducted an exhaustive investigation of the following key intervention areas: overall effectiveness of BIPs; length of treatment/length of group sessions; number of group participants and number of facilitators; group format and curriculum; assessment protocol and instruments; victim contact; modality of treatment; differential treatment; working with female perpetrators; working with perpetrators in racial and ethnic minority groups; working with lesbian, gay, bisexual, and transgender (LGBT) perpetrators; perpetrator treatment and practitioner–client relationships; and required practitioner education and training. Recommendations for evidence-based national BIP standards were made based on findings from this review.


2013 ◽  
Vol 2 (1) ◽  
Author(s):  
Carlos Siordia ◽  
Vi Donna Le

Detailed social data about the United States (US) population was collected as part of the US decennial Census up until 2000. Since then, the American Community Survey (ACS) has replaced the long form previously administered in decennial years. The ACS uses a sample rather than the entire US population and therefore, only estimates can be created from the data. This investigation computes disability estimates, standard error, margin of error, and a more comprehensive “range of uncertainty” measure for non-Latino-whites (NLW) and four Southeast Asian groups. Findings reveal that disability estimates for Southeast Asians have a much higher degree of imprecision than for NLW. Within Southeast Asian groups, Vietnamese have the highest level of certainty, followed by the Hmong. Cambodians and Laotians disability estimates contain high levels of uncertainty. Difficulties with self-care and vision contain the highest level of uncertainty relative to ambulatory, cognitive, independent living, and hearing difficulties.


2014 ◽  
Vol 4 (2) ◽  
pp. 494 ◽  
Author(s):  
Carlos Siordia

<p><strong>Abstract</strong></p><p><strong>BACKGROUND:  </strong>The American Community Survey (ACS) in the United States (US) collects detailed demographic information on the US population. Pressures to use year-to-year population estimates to analyze “trends” (i.e., between-year differences on the characteristics of interest) have motivated the need to explore how single- or multi-year estimates can be used to investigate changes in US population over time. <strong>OBJECTIVE: </strong>The specific aim of this manuscript is to provide empirical evidence that between-year differences in population characteristics have difference levels of uncertainty around point-estimates. <strong>METHODS:</strong> Six ACS Public Use Microdata Sample (PUMS) single year files from 2005 through 2010 are used to empirically show the heterogeneity of uncertainty in “between-year differences” on level of education, for a birth cohort born between 1960 and 1970 of non-Latino-whites and Mexican Latinos/as. <strong>RESULTS: </strong>The data show the precision of the education estimate decreases as the specificity of the population increases. For example, Mexican’s 99% confidence intervals have wider and more time-varying bandwidths than non-Latino-whites. <strong>CONCLUSIONS: </strong>Inferring meaningful population change requires the challengeable assumption that between-year differences are not the product of data artifacts. Harvesting reputable ACS data demands further research before between-year differences can be treated as “real change.”    </p><p> </p>


2019 ◽  
Author(s):  
Corey Sparks ◽  
Lloyd B. Potter

The American Community Survey (ACS) summary file data provide rolling 5-year estimates of demographic and socioeconomic indicator data for small geographiesthroughout the United States. These estimates are commonly used as indicators forregression models to measure conditions in communities. The Margins of Error (MOE) inthe ACS estimates for small geographic areas can often be very large, and without takingthem into account, regression analyses using them can be mis-specified, leading to bias inregression coefficients and model standard errors. This paper directly comparesmeasurement error model specifications to naive model specifications for a mortalityoutcome in Texas Census tracts using Bayesian model specializations. The results showthat there is bias in the naive regression model results. We urge users of the ACSsummary file data to be aware of such bias as it can potentially impact interpretation ofmodel results and hypothesis tests.


2020 ◽  
Vol 110 (8) ◽  
pp. 1228-1234
Author(s):  
Alison H. Norris ◽  
Payal Chakraborty ◽  
Kaiting Lang ◽  
Robert B. Hood ◽  
Sarah R. Hayford ◽  
...  

Objectives. To examine abortion utilization in Ohio from 2010 to 2018, a period when more than 15 abortion-related laws became effective. Methods. We evaluated changes in abortion rates and ratios examining gestation, geographic distribution, and abortion method in Ohio from 2010 to 2018. We used data from Ohio’s Office of Vital Statistics, the Centers for Disease Control and Prevention’s Abortion Surveillance Reports, the American Community Survey, and Ohio’s Public Health Data Warehouse. Results. During 2010 through 2018, abortion rates declined similarly in Ohio, the Midwest, and the United States. In Ohio, the proportion of early first trimester abortions decreased; the proportion of abortions increased in nearly every later gestation category. Abortion ratios decreased sharply in most rural counties. When clinics closed, abortion ratios dropped in nearby counties. Conclusions. More Ohioans had abortions later in the first trimester, compared with national patterns, suggesting delays to care. Steeper decreases in abortion ratios in rural versus urban counties suggest geographic inequity in abortion access. Public Health Implications. Policies restricting abortion access in Ohio co-occur with delays to care and increasing geographic inequities. Restrictive policies do not improve reproductive health.


2015 ◽  
Vol 5 (3) ◽  
pp. 86-89
Author(s):  
Robin Mejia

Using data from the United States Census 2013 American Community Survey, Robin Mejia looks at the way geography affects a person’s health, wealth, education, and prospects in life.


2020 ◽  
Vol 42 (2) ◽  
pp. 143-164
Author(s):  
Richard C. Jones

This study investigates the educational and economic attainment of Mexican Dreamers over the 4 years since DACA was implemented (2012–2016). A time-space stream of benefits and barriers is evaluated at the national, state, and individual levels. Based on assumptions linking the DACA-eligible to DACA recipients, I examine the annual American Community Survey (ACS) to glean insights not provided elsewhere. At national level, the results suggest that young Mexican Dreamers entered the workforce at higher rates, but college at lower rates, than a control group of Mexican Americans. At state level, in supportive states these Dreamers entered college at higher rates but the work force at slightly lower rates, than they did in restrictive states. At the individual level, it is revealed that DACA strongly promoted college over work for women, but just the reverse for men. These distinctions are bringing about new inequalities within the Mexican Dreamer community in the United States.


2021 ◽  
pp. 003464462110135
Author(s):  
Asia Bento

Scholars debate whether residential racial segregation associates positively, negatively, or at all with the Black self-employment rate in the United States. This study engages that debate using data from the Integrated Public Use Microdata Series (IPUMS) 1980, 1990, and 2000 5% sample and 2006–2010 American Community Survey (ACS) 5-year sample. Specifically, I investigate the county-level association between residential racial segregation and the Black self-employment rate, and whether this association varied by region in 1980, 1990, 2000, and 2010. Using fractional logit models and net of control variables, I find that residential racial segregation positively predicts Black self-employment in the South. Implications for understanding how time and region condition Black self-employment opportunities are discussed.


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