Background: Customer intercept interviews are increasingly used to characterize food purchases at retail food outlets and restaurants; however, methodological procedures, logistical issues and response rates using intercept methods are not well described in the food environment literature. The aims of this manuscript were to 1) describe the development and implementation of a customer intercept interview protocol in a large, NIH-funded study assessing food purchases in small and midsize food retailers in Minneapolis and St. Paul, Minnesota, 2) describe intercept interview response rates by store type and environmental factors (e.g., neighborhood socioeconomic status, day/time, weather), and 3) compare demographic characteristics (e.g., gender, race/ethnicity) of participants versus non-participants. Methods: After a pilot phase involving 28 stores, a total of 616 interviews were collected from customers exiting 128 stores in fall 2014. The number of eligible customers encountered per hour (a measure of store traffic), participants successfully recruited per hour, and response rates were calculated overall and by store type, neighborhood socio-economic status, day and time of data collection, and weather. Response rates by store type, neighborhood socio-economic status, time and day of data collection, and weather, and characteristics of participants and non-participants were compared using chi-square tests. Results: The overall response rate was 35 %, with significantly higher response rates at corner/small grocery stores (47%) and dollar stores (46%) compared to food-gas marts (32%) and pharmacies (26%), and for data collection between 4:00-6:00 pm on weekdays (40%) compared to weekends (32%). The distribution of race/ethnicity, but not gender, differed between participants and non-participants (p<0.01), with greater participation rates among those identified as Black versus White. Conclusions: Customer intercept interviews can be successfully used to recruit diverse samples of customers at small and midsize food retailers. Future community-based studies using customer intercept interviews should collect data sufficient to report response rates and consider potential differences between the racial/ethnic composition of the recruited sample and the target population.

Recent evidence suggests that rising immigrant diversity in cities offers economic benefits, including improved innovation, entrepreneurship and productivity. One potentially important but underexplored dimension of this relationship is how local institutional context shapes the benefits firms and workers receive from the diversity in their midst. Theory suggests that institutions can make it less costly for diverse workers to transact, thereby catalyzing the latent bene ts of heterogeneity. This paper tests the hypothesis that the effects of immigrant diversity on productivity will be stronger in locations featuring more “inclusive" institutions. It leverages comprehensive longitudinal linked employer-employee data for the U.S. and two distinct measures of inclusive institutions at the metropolitan area level: social capital and pro- or anti-immigrant ordinances. Findings confirm the importance of institutional context: in cities with low levels of inclusive institutions, the benefits of diversity are modest and in some cases statistically insignificant; in cities with high levels of inclusive institutions, the benefits of immigrant diversity are positive, significant, and substantial. Moreover, natives residing in cities that have enacted laws restricting immigrants enjoy no diversity spillovers whatsoever, while immigrants in these cities continue to receive a diversity bonus. These results confirm the economic significance of urban immigrant diversity, while suggesting the importance of local social and economic institutions.

This paper focuses on the 421-a Tax Abatement Policy by analyzing data on Brooklyn communities in New York City. The paper is motivated by my experience as an Urban Studies Major attempting to incorporate my Economics background as well as my passion for New York City and its urban development. I will use regression analysis to look at the Geographic Exclusion Area (GEA) designated by the city, which requires creation of affordable housing in order to receive important tax benefits towards the development projects. The data analysis shows that although there exists an initial positive outcome from the policy treatment, in the long term there appears to be larger negative effects that work against the goals of the 421-a Program. The variables of interest are Household Income, Minority Status, English Ability, and Citizenship. One of the major assumptions of the paper is that once a space is designated as GEA, there is an intangible change that signals to the community that the space in more affluent. This paper finds that the Geographic Exclusion Area plays an important role in its designation of a space and the fact that GEA spaces are empirically wealthier.

Women’s marital surname change was investigated as a potential marital commitment signal, and strategy for enhancing investment from in-laws and husband. Hyphenating or keeping premarital surname for all U.S. destination brides marrying in Hawai'i in 2010 was significantly correlated with a women’s income measure (r = .78, p < .000) and with the analogous statistic for men (r = .64, p < .000), by bride’s state of residence. The women’s measure, only, remained significant under regression of both predictors. The interaction of state Gini and the women’s income measure in a regression including the interaction components as predictors was positively predictive (adjusted-R2 = .57). None of several other predictors suggested by previous research or related to Gini or income were significant under regression, alongside the women’s income measure. The older the bride, from any jurisdiction, marrying . . .

This study takes advantage of a large, nationally representative dataset, the American Time Use Survey (ATUS), to examine gender differences in commute character and time. A method of calculating commuting time that accounts for stops along the journey is applied to ATUS data; analysis of gender differences in the number, type, and length of stops demonstrates the need for this commuting measure. Explanations for womens shorter commutes are reviewed and tested alongside predicted relationships from a simple labor supply model. Controlling for marital status and the presence of children, women are more likely to be accompanied by children for their commute, and women tend to make longer stops than men. Multivariate regression results support two previously proposed explanations for the gender commuting time gap, based on gender differences in wages and types of jobs held. Contrary to the previously proposed Household Responsibility Hypothesis, this analysis provides evidence that greater household responsibility does not explain womens shorter commutes.

In recent decades, the geographic origins of Americas foreign-born population have become increasingly diverse. The sending countries of the U.S. foreign-born vary substantially in levels of health and economic development, and immigrants have arrived with distinct distributions of socioeconomic status, visa type, year of immigration, and age at immigration. We use high-quality linked Social Security and Medicare records to estimate life tables for the older U.S. population over the full range of birth regions. In 20002009, the foreign-born had a 2.4-year advantage in life expectancy at age 65 relative to the U.S.-born, with Asian-born subgroups displaying exceptionally high longevity. Foreign-born individuals who migrated more recently had lower mortality compared with those who migrated earlier. Nonetheless, we also find remarkable similarities in life expectancy among many foreign-born subgroups that were born in very different geographic and socioeconomic contexts (e.g., Central America, western/eastern Europe, and Africa).

Using 2010 Brazilian Census data, this paper focuses on the relationship between family structure (be in a family with biological parents, or with one biological parent and one stepparent, or in a single parenting family) on educational achievement for young adult children between 18 to 24 years old. By education achievement we considered: 1) have finished high school; 2) be enrolled in high school or 3) neither of them. We used multinomial logit regression and the results show that young adults living with their biological parents are the ones with the highest probability of have finished or be enrolled in high school, followed by the ones living only with their mothers. The lowest probability is among children living in blended families.

This paper develops a dynamic general equilibrium model to analyze firms’ joint decisions on production offshoring and clean technology adoptions when facing different labor productivities and environmental regulations between home country and offshoring host country. During their decision processes, both workers’ wages and emission levels of related countries are endogenously determined. Later this model is calibrated to match the data on manufacturing workers’ wages in the U.S. and China’s foreign invested enterprises and both countries’ PM2.5 emissions over 1999-2013. This paper quantifies the offshoring levels which is measured by the share of total low-skilled labor-intensive manufacturing production processes shifted from U.S. to China. My paper also gives the long-run predictions . . .

Population aging is requiring a re-examination of the role of eldercare. According to the U.S. Census Bureau, nearly one in five U.S. residents will be age 65 or older in 2030 (see Denton 2012 BLS Monthly Labor Review). In particular, unpaid eldercare is an important issue, as elder care is often provided by a family member or friends. Unpaid caregivers often experience what is called caregiver strain, defined as psychological, emotional, and/or physical strain through the act of caregiving. In this paper, we examine the extent to which the relationship between providing eldercare and subjective well-being may operate through the time constraints caregivers face, hypothesizing that the act of providing care takes time away from other activities. In addition, while the majority of caregivers are women, we test for possible gender differences in the relationship between elder caregiving, time allocation and subjective well-being. Using the American Time Use Survey (ATUS) for 2012 and 2013, of 21728 respondents, 3503 (16%) reported to have provided eldercare to a person older than 65. 61% of them were women. Our findings suggest that eldercare providers report lower level of life satisfaction as well as higher proportion are not well rested. Eldercare providers also reports less time in personal care and social activities.

This article is the first careful look at the demographic makeup of law faculties compared to the larger pools of lawyers and the general public. It examines which racial, gender, religious, and political groups were the most under- and overrepresented in 1997 and in 2013 compared to persons of similar ages in larger pools, including the U.S. full-time working population and the U.S. lawyer population.

This study compared national estimates of the supply and characteristics of nine allied health occupations drawn from four publicly available national data sources, and described uses and limitations of these national data sources for health workforce planning. Design/Methods: Using the most recent data available (from 2014 to 2016) from the American Community Survey (ACS), the Current Population Survey (CPS), the Occupational Employment Statistics (OES), the National Plan and Provider Enumeration System National Provider Identifier (NPI) Registry, we compared the estimated workforce size and characteristics of nine allied health occupations: occupational therapists, physical therapists, respiratory therapists, speech-language pathologists, clinical laboratory technologists/technicians, dental hygienists, diagnostic-related technologists/technicians, medical assistants, and social workers. National supply size estimates and numbers per 100,000 population were used to compare workforce size between datasets for each occupation. Descriptive statistics were used to depict the demographic and socioeconomic characteristics of individuals in these occupations. Results: National workforce supply estimates from the ACS, CPS and OES data sources for the nine selected occupations were generally comparable. Estimates based on NPI Registry data were smaller and not available for some occupations. Social workers and medical assistants were the largest groups among the occupations studied. Occupational therapists and respiratory therapists were the smallest. Speech-language pathologist and dental hygienists were predominantly female (>96%) and respiratory therapists had the highest percentage of males (34-35%). Clinical laboratory technicians/technologists and medical assistants were the most racially diverse of the occupations studied (roughly half of those who were not Hispanic were of races other than White). These occupations, along with social workers, also had larger proportions of Hispanic individuals (10-28%). Medical assistants had the lowest annual earnings ($29,000-$32,000) and physical therapists had the highest ($60,000-$86,000), although earnings were challenging to compare.

A comprehensive agenda to address the nations legacy of mass incarceration and overcriminalization must not only remove barriers to employment for people with criminal records, but also ensure that jobs pay a fair, livable wage. A recent report from the White House Council of Economic Advisers, or CEA, demonstrated that raising the federal minimum wage would significantly reduce criminal activity and enhance public safety, saving American communities billions of dollars each year. This issue brief finds that a second policy to boost income for low-paid workersexpanding the Earned Income Tax Credit, or EITC, for workers without dependent childrenwould generate an additional $1.7 billion to $3.3 billion in societal benefit each year from reduced crime and improved public safety

Background: From 1907 to 1937, thirty-two US states authorized state institutions for the feebleminded and mentally ill to sterilize residents deemed unfit for reproduction. California carried out one third of sterilizations nationwide. Previous reports have documented the over-sterilization of Latino/Hispanic institution residents, and new individual-level data allows us to examine this ethnic bias at a granular level. Methods: We link data on 17,362 California state institution patients recommended for sterilization from 1920-1945 to U.S. Census microdata on total patient populations of each institution in 1920, 1930 and 1940. We estimate rates of sterilization by Latino/Hispanic ethnicity (Spanish surname) and compare ethnic bias in sterilization by gender, age, time, and justifications for sterilization (mental illness, “feeblemindedness”, or perceived social ills such as sexual delinquency or criminal tendency). Results: Latino/Hispanic institution residents were, on average, recommended for sterilization at 2.65 (95% CI: 2.52, 2.77) times the rate of non-Latino/Hispanic institution residents. Ethnic bias in sterilization varied significantly by sex, age group and institution, with the greatest ethnic bias in sterilization among females, among individuals younger than 15, and among individuals living in state homes for the feebleminded (relative to those living in mental hospitals). There were no consistent ethnic differences in reported degree of “feeblemindedness” or mental health diagnoses, but Latino/Hispanic sterilization recommendees were more frequently flagged for “criminal tendencies” than their nonLatino/Hispanic counterparts. Among females, Latina/Hispanic patients were more likely to be deemed “sexually delinquent”. Discussion: While eugenic sterilization laws did not explicitly encourage sterilization of racial/ethnic minorities, in practice these policies targeted patients stereotyped as overfertile and criminally inclined.

This dissertation consists of three chapters; each chapter is organized as a separate essay. All three essays focus on the effect of the military service on the civilian labor market performance of veterans. Chapter 1 examines the unemployment impact of prior military service on the veterans. In order to control for non-random selection into the military, chapter introduces new set of instrumental variables exploiting the variation in economic and military characteristics of the states when young people make their enlistment decisions. Using Integrated Public Use Microdata Series from the American Community Survey (ACS) from 2008 to 2014, I find that among those in the civilian non-institutional labor force, veterans are equally likely to be unemployed as comparable non-veterans once they are in the labor force. In 2011, the Veterans Opportunity to Work to Hire Heroes Act was established to improve the employment outcomes of veterans. Using data from the Current Population Survey from 2010 to 2013, Chapter 2 provides evidence on the impact of the Veterans Opportunity to Work Act of 2011 (VOW) on labor market performance of veterans. The effect of the legislation . . .

One of the first provisions enacted under the Patient Protection and A↵ordable Care Act (PPACA) was was the Young Adult Coverage Expansion, which took e↵ect on September 23, 2010. Under this provision, individuals up to age 26, can remain on their parent’s employer provided health insurance plan. Relatively little is known about the e↵ect of insurance coverage on the labor supply of young adults. In this paper, I ex- ploit the exogenous expansion of health insurance coverage among a segment of young adults as an instrumental variable to control for the endogeneity of health insurance status. This allows me to estimate causal labor market e↵ects of insurance coverage. I leverage a di↵erence-in-di↵erence design in the first stage of a two-stage control func- tion to estimate the e↵ect of the law on the probability of insurance coverage and use the predicted residual from this stage as my instrument in the second stage regression. The main structural equation estimates the causal e↵ect of insurance coverage on the likelihoods of working part time, full time, not working and being self-employed among 22-29 year olds. Using data from the 2006 to 2015 March Current Population Survey (CPS) I find that eligibility for the mandate is associated with a 5.2-5.7 percentage point increase in insurance rates among young adults. As a result of gaining access to insurance, 22-29 year olds are more likely to be self-employed, to not work, and to work part time. They are less likely to work full time. These results are consistent with the classical economics theory behind the role of social welfare provision and work incentives.

In this paper we study the relationship between task complexity and the occupational wage and employment structure. Complex tasks are defined as those requiring higher-order skills, such as the ability to abstract, solve problems, make decisions, or communicate effectively. We measure the task complexity of an occupation by performing Principal Component Analysis on a broad set of occupational descriptors in the Occupational Information Network (O*NET) data. We establish four main empirical facts for the U.S. over the 1980-2005 time period that are robust to the inclusion of a detailed set of controls, subsamples, and levels of aggregation: (1) There is a positive relationship across occupations between task complexity and wages and wage growth; (2) Conditional on task complexity, routine-intensity of an occupation is not a significant predictor of wage growth and wage levels; (3) Labor has reallocated from less complex to more complex occupations over time; (4) Within groups of occupations with similar task complexity labor has reallocated to non-routine occupations over time. We then formulate a model of Complex-Task Biased Technological Change with heterogeneous skills and show analytically that it can rationalize these facts. We conclude that workers in non-routine occupations with low ability of solving complex tasks are not shielded from the labor market effects of automatization.

The incidence of divorce, like the incidence of many other demographic phenomena, varies greatly across the life course. Divorce is most prevalent during young adulthood and relatively infrequent among the elderly, a pattern that has been present for at least a century. In contrast, the overall level of divorce in the U.S. has varied substantially over time, with a long-term upward trend but with notable deviations from that trend. It is not surprising then that most discussions about divorce have focused on its overall level rather than on how it varies across the life course. This is unfortunate insofar as it leads us to overlook that fact that, in the U.S. at least, recent years have seen the relationship between the prevalence of divorce and age weaken substantially.

This paper estimates intergenerational elasticities across three generations in the United States in the late 19th and early 20th centuries. We extend the methodology in Olivetti and Paserman (2015) to explore the role of maternal and paternal grandfathers for the transmission of economic status to grandsons and granddaughters. We document three main findings. First, grandfathers matter for income transmission, above and beyond their effect on fathers' income. Second, the socio-economic status of grandsons is influenced more strongly by paternal grandfathers than by maternal grandfathers. Third, maternal grandfathers are more important for granddaughters than for grandsons, while the opposite is true for paternal grandfathers. We present a model of multi-trait matching and inheritance that can rationalize these findings.