We make use of predicted social and civic activities (social capital) to account for selection into "social" occupations. Individual selection accounts for more than the total difference in wages observed between social and non-social occupations. The role that individual social capital plays in selecting into these occupations and the importance of selection in explaining wage differences across occupations is similar for both men and women. We make use of restricted 2000 Decennial Census and 2000 Social Capital Community Benchmark Survey. Individual social capital is instrumented by distance weighted surrounding census tract characteristics.
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Individual Social Capital and Migration
March 2018
Working Paper Number:
CES-18-14
This paper determines how individual, relative to community social capital affects individual migration decisions. We make use of non-public data from the Social Capital Community Benchmark Survey to predict multi-dimensional social capital for observations in the Current Population Survey. We find evidence that individuals are much less likely to have moved to a community with average social capital levels lower than their own and that higher levels of community social capital act as positive pull-factor amenities. The importance of that amenity differs across urban/rural locations. We also confirm that higher individual social capital is a negative predictor of migration.
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In-migration and Dilution of Community Social Capital
June 2018
Working Paper Number:
CES-18-32
Consistent with predictions from the literature, we find that higher levels of in-migration dilute multiple dimensions of a community's level of social capital. The analysis employs a 2SLS
methodology to account for potential endogeneity of migration.
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An Evaluation of the Gender Wage Gap Using Linked Survey and Administrative Data
November 2020
Working Paper Number:
CES-20-34
The narrowing of the gender wage gap has slowed in recent decades. However, current estimates show that, among full-time year-round workers, women earn approximately 18 to 20 percent less than men at the median. Women's human capital and labor force characteristics that drive wages increasingly resemble men's, so remaining differences in these characteristics explain less of the gender wage gap now than in the past. As these factors wane in importance, studies show that others like occupational and industrial segregation explain larger portions of the gender wage gap. However, a major limitation of these studies is that the large datasets required to analyze occupation and industry effectively lack measures of labor force experience. This study combines survey and administrative data to analyze and improve estimates of the gender wage gap within detailed occupations, while also accounting for gender differences in work experience. We find a gender wage gap of 18 percent among full-time, year-round workers across 316 detailed occupation categories. We show the wage gap varies significantly by occupation: while wages are at parity in some occupations, gaps are as large as 45 percent in others. More competitive and hazardous occupations, occupations that reward longer hours of work, and those that have a larger proportion of women workers have larger gender wage gaps. The models explain less of the wage gap in occupations with these attributes. Occupational characteristics shape the conditions under which men and women work and we show these characteristics can make for environments that are more or less conducive to gender parity in earnings.
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Decennial Census Return Rates: The Role of Social Capital
January 2017
Working Paper Number:
CES-17-39
This paper explores how useful information about social and civic engagement (social capital)
might be to the U.S. Census Bureau in their efforts to improve predictions of mail return rates for the Decennial Census (DC) at the census tract level. Through construction of Hard-to-count (HRC) scores and multivariate analysis, we find that if information about social capital were available, predictions of response rates would be marginally improved.
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A Task-based Approach to Constructing Occupational Categories
with Implications for Empirical Research in Labor Economics
September 2019
Working Paper Number:
CES-19-27
Most applied research in labor economics that examines returns to worker skills or differences in earnings across subgroups of workers typically accounts for the role of occupations by controlling for occupational categories. Researchers often aggregate detailed occupations into categories based on the Standard Occupation Classification (SOC) coding scheme, which is based largely on narratives or qualitative measures of workers' tasks. Alternatively, we propose two quantitative task-based approaches to constructing occupational categories by using factor analysis with O*NET job descriptors that provide a rich set of continuous measures of job tasks across all occupations. We find that our task-based approach outperforms the SOC-based approach in terms of lower occupation distance measures. We show that our task-based approach provides an intuitive, nuanced interpretation for grouping occupations and permits quantitative assessments of similarities in task compositions across occupations. We also replicate a recent analysis and find that our task-based occupational categories explain more of the gender wage gap than the SOC-based approaches explain. Our study enhances the Federal Statistical System's understanding of the SOC codes, investigates ways to use third-party data to construct useful research variables that can potentially be added to Census Bureau data products to improve their quality and versatility, and sheds light on how the use of alternative occupational categories in economics research may lead to different empirical results and deeper understanding in the analysis of labor market outcomes.
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High Labor Force Attachment, but Few Social Ties? Life-Course Predictors of Women's Receipt of Childcare Subsidies
September 2019
Working Paper Number:
CES-19-26
The U.S. federal Child Care and Development Fund (CCDF) childcare subsidy represents the largest source of means-tested assistance for U.S. families with low incomes. The CCDF subsidy aims to help mothers with low incomes gain employment and education, with implications for women's labor force participation, and the wellbeing of their children. Because recipients of the CCDF subsidy are either already employed, or seek the subsidy with the goal of gaining employment or schooling, this group may represent the public assistance recipients who are best able to succeed in the low-wage labor market. However, existing research on the CCDF observes recipients only after they begin receiving the subsidy, thus giving an incomplete picture of whether recipients may select into subsidy receipt, and how subsidy recipiency is situated in women's broader work and family trajectories. My study links administrative records from the CCDF to the American Community Survey (ACS) to construct a longitudinal data set from 38 states that observes CCDF recipients in the 1-2 years before they first received the subsidy. I compare women who subsequently received the CCDF subsidy to other women with low incomes in the ACS who did not go on to receive the subsidy, with a total of roughly 641,000 individuals. I find that CCDF recipients are generally positively-selected on employment history and educational attainment, but appear to have lower levels of social support than non-recipients.
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Migration Decisions in Arctic Alaska: Empirical Evidence of the Stepping Stones Hypothesis
December 2010
Working Paper Number:
CES-10-41
This paper explores hypotheses of hierarchical migration using data from the Alaskan Arctic. We focus on migration of I'upiat people, who are indigenous to the region, and explore the role of income, harvests of subsistence resources, and other place characteristics in migration decisions. To test related hypotheses we use confidential micro-data from the US Census Bureau's 2000 Decennial Census of Population and Income. Using predicted earnings and subsistence along with place invariant characteristics we generate migration probabilities using a mixed multinomial and conditional logit model. Our results support stepwise migration patterns, both up and down an urban and rural hierarchy. At the same time, we also identify differences between men and women, and we find mixed effects of place amenities and predicted earnings.
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Universal Preschool Lottery Admissions and Its Effects on Long-Run Earnings and Outcomes
March 2023
Working Paper Number:
CES-23-09
We use an admissions lottery to estimate the effect of a universal (non-means tested) preschool program on students' long-run earnings, income, marital status, fertility and geographic mobility. We observe long-run outcomes by linking both admitted and non-admitted individuals to confidential administrative data including tax records. Funding for this preschool program comes from an Indigenous organization, which grants Indigenous students admissions preference and free tuition. We find treated children have between 5 to 6 percent higher earnings as young adults. The results are strongest for individuals from the lower half of the household income distribution in childhood. Likely mechanisms include high-quality teachers and curriculum.
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How Does Geography Matter in Ethnic Labor Market Segmentation Process? A Case Study of Chinese Immigrants in the San Francisco CMSA
March 2007
Working Paper Number:
CES-07-09
In the context of continuing influxes of large numbers of immigrants to the United States, urban labor market segmentation along the lines of race/ethnicity, gender, and class has drawn considerable growing attention. Using a confidential dataset extracted from the United States Decennial Long Form Data 2000 and a multilevel regression modeling strategy, this paper presents a case study of Chinese immigrants in the San Francisco metropolitan area. Correspondent with the highly segregated nature of the labor market as between Chinese immigrant men and women, different socioeconomic characteristics at the census tract level are significantly related to their occupational segregation. This suggests the social process of labor market segmentation is contingent on the immigrant geography of residence and workplace. With different direction and magnitude of the spatial contingency between men and women in the labor market, residency in Chinese immigrant concentrated areas is perpetuating the gender occupational segregation by skill level. Whereas abundant ethnic resources may exist in ethnic neighborhoods and enclaves for certain types of employment opportunities, these resources do not necessarily help Chinese immigrant workers, especially women, to move upward along the labor market hierarchy.
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Sex Segregation in U.S. Manufacturing
June 1996
Working Paper Number:
CES-96-04
This paper studies interplant sex segregation in the U.S. manufacturing industry. The study differs from previous work in that we have detailed information on the characteristics of both workers and firms, and because we measure segregation in a new and better way. We report three main findings. First, there is a substantial amount of interplant sex segregation in the U.S. manufacturing industry, although segregation is far from complete. Second, we find that female managers tend to work in the same plants as female supervisees, even once we control for other plant characteristics. And finally, we find that interplant segregation can account for a substantial fraction of the male/female wage gap in the manufacturing industry, particularly among blue-collar workers.
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