About

Ted Mouw is a Professor in the Department of Sociology at the University of North Carolina at Chapel Hill. His areas of interest include demography, social stratification, economic sociology, labor markets, social structure of labor markets, social and residential segregation in U.S. urban areas, gender occupational segregation, and demographic change in Indonesia. He earned his Ph.D. from the University of Michigan in 1999. His professional background encompasses research and teaching related to labor markets, stratification, economic sociology, and demography, with a focus on understanding social and economic inequalities and demographic processes.

Research topics

• Sociology
• Political Science
• Social Science
• Demography
• Geography
• Computer Science
• Political economy
• Telecommunications
• Psychology
• Ecology
• Economics
• Gender studies
• Clinical psychology
• Medicine
• Law
• Biology
• Demographic economics

Selected publications

• The impact of two types of COVID-19-related discrimination and contemporaneous stressors on Chinese immigrants in the US South

  UNC Libraries · 2025-05-01

  articleOpen access
  PublisherDOI

• Career types and labor market structure: Intragenerational mobility in the United States

  Social Science Research · 2025-03-10 · 2 citations

  article
  PublisherDOI

• “Stepping-Stone” versus “Dead-End” Jobs: Occupational Structure, Work Experience, and Mobility Out of Low-Wage Jobs

  UNC Libraries · 2024-09-27 · 1 citations

  articleOpen accessSenior author

  Does working in a low-wage job lead to increased opportunities for upward mobility, or is it a dead-end that traps workers? In this article, we examine whether low-wage jobs are “stepping-stones” that enable workers to move to higher-paid jobs that are linked by institutional mobility ladders and skill transferability. To identify occupational linkages, we create two measures of occupational similarity using data on occupational mobility from matched samples of the Current Population Survey (CPS) and data on multiple dimensions of job skills from the O*NET. We test whether work experience in low-wage occupations increases mobility between linked occupations that results in upward wage mobility. Our analysis uses longitudinal data on low-wage workers from the 1979 National Longitudinal Study of Youth (NLSY) and the 1996 to 2008 panels of the Survey of Income and Program Participation (SIPP). We test the stepping-stone perspective using multinomial conditional logit (MCL) models, which allow us to analyze the joint effects of work experience and occupational linkages on achieving upward wage mobility. We find evidence for stepping-stone mobility in certain areas of the low-wage occupational structure. In these occupations, low-wage workers can acquire skills through work experience that facilitate upward mobility through occupational changes to skill and institutionally linked occupations.

  PublisherDOI

• Studying Chinese immigrants’ spatial distribution in the Raleigh–Durham area by linking survey and commercial data using romanized names

  Journal of the Royal Statistical Society Series A (Statistics in Society) · 2024-10-23 · 1 citations

  articleOpen accessSenior author

  Many population surveys do not provide information on respondents' residential addresses, instead offering coarse geographies like zip code or higher aggregations. However, fine resolution geography can be beneficial for characterizing neighbourhoods, especially for relatively rare populations such as immigrants. One way to obtain such information is to link survey records to records in auxiliary databases that include residential addresses by matching on variables common to both files. We present an approach based on probabilistic record linkage that enables matching survey participants in the Chinese Immigrants in Raleigh-Durham Study to records from InfoUSA, an information provider of residential records. The two files use different Chinese name romanization practices, which we address through a novel and generalizable strategy for constructing records' pairwise comparison vectors for romanized names. Using a fully Bayesian record linkage model, we characterize the geospatial distribution of Chinese immigrants in the Raleigh-Durham area of North Carolina.

  PublisherOA PDFDOI

• The impact of the COVID‐19 pandemic on network dynamics among Chinese immigrants in the United States

  International Migration · 2024-08-22 · 2 citations

  articleOpen access1st authorCorresponding

  We use longitudinal data on the social networks of Chinese immigrants in the United States from 2018-2020 to study the impact of the COVID-19 pandemic on communication frequency and friendship formation. Understanding the pandemic's effect on social networks is important because, while individual social networks are always in flux (Schaefer and Marcum 2017; Sekara, Stopczynski, and Lehmann 2016), they tend to change slowly over time in periods of social stability (Wrzus et al. 2013). In contrast, the COVID-19 pandemic was a massive disturbance in the social environment, similar to the effect a natural disaster such as a hurricane on social networks, but on a much broader scale (Bertogg and Koos 2022). For Chinese immigrants in the U.S., the social disruption of the COVID-19 pandemic was magnified because, in addition to the social isolation caused by lockdowns and social distancing, there was a dramatic rise in anti-Chinese discrimination and hate crimes in the U.S. which affected migrants' sense of inclusion and collective identity in their host society (Li, English, and Kulich 2021; Stolte et al. 2022). By examining how migrant networks changed and adapted to this altered macro-level social environment, we can better understand how micro and macro level factors interact to affect network changes in general. The findings indicate that while stress during the pandemic affected the level of social network communication, the process of new tie formation to natives appears to be relatively unaffected.

  PublisherOA PDFDOI

• “Stepping-Stone” versus “Dead-End” Jobs: Occupational Structure, Work Experience, and Mobility Out of Low-Wage Jobs

  American Sociological Review · 2024-03-22 · 15 citations

  articleOpen access1st authorCorresponding

  Does working in a low-wage job lead to increased opportunities for upward mobility, or is it a dead-end that traps workers? In this article, we examine whether low-wage jobs are “stepping-stones” that enable workers to move to higher-paid jobs that are linked by institutional mobility ladders and skill transferability. To identify occupational linkages, we create two measures of occupational similarity using data on occupational mobility from matched samples of the Current Population Survey (CPS) and data on multiple dimensions of job skills from the O*NET. We test whether work experience in low-wage occupations increases mobility between linked occupations that results in upward wage mobility. Our analysis uses longitudinal data on low-wage workers from the 1979 National Longitudinal Study of Youth (NLSY) and the 1996 to 2008 panels of the Survey of Income and Program Participation (SIPP). We test the stepping-stone perspective using multinomial conditional logit (MCL) models, which allow us to analyze the joint effects of work experience and occupational linkages on achieving upward wage mobility. We find evidence for stepping-stone mobility in certain areas of the low-wage occupational structure. In these occupations, low-wage workers can acquire skills through work experience that facilitate upward mobility through occupational changes to skill and institutionally linked occupations.

  PublisherOA PDFDOI

• Research Note: Bayesian Record Linkage with Application to Chinese Immigrants in Raleigh-Durham (ChIRDU) Study

  arXiv (Cornell University) · 2023-10-21

  preprintOpen access

  Many population surveys do not provide information on respondents' residential addresses, instead offering coarse geographies like zip code or higher aggregations. However, fine resolution geography can be beneficial for characterizing neighborhoods, especially for relatively rare populations such as immigrants. One way to obtain such information is to link survey records to records in auxiliary databases that include residential addresses by matching on variables common to both files. In this research note, we present an approach based on probabilistic record linkage that enables matching survey participants in the Chinese Immigrants in Raleigh-Durham (ChIRDU) Study to records from InfoUSA, an information provider of residential records. The two files use different Chinese name romanization practices, which we address through a novel and generalizable strategy for constructing records' pairwise comparison vectors for romanized names. Using a fully Bayesian record linkage model, we characterize the geospatial distribution of Chinese immigrants in the Raleigh-Durham area.

  PublisherOA PDFDOI

• Using Social Networks to Sample Migrants and Study the Complexity of Contemporary Immigration: An Evaluation Study

  Demography · 2022 · 6 citations

  • Computer Science
  • Sociology
  • Political Science

  We test the effectiveness of a link-tracing sampling approach-network sampling with memory (NSM)-to recruit samples of rare immigrant populations with an application among Chinese immigrants in the Raleigh-Durham area of North Carolina. NSM uses the population network revealed by data from the survey to improve the efficiency of link-tracing sampling and has been shown to substantially reduce design effects in simulated sampling. Our goals are to (1) show that it is possible to recruit a probability sample of a locally rare immigrant group using NSM and achieve high response rates; (2) demonstrate the feasibility of the collection and benefits of new forms of network data that transcend kinship networks in existing surveys and can address unresolved questions about the role of social networks in migration decisions, the maintenance of transnationalism, and the process of social incorporation; and (3) test the accuracy of the NSM approach for recruiting immigrant samples by comparison with the American Community Survey. Our results indicate feasibility, high performance, cost-effectiveness, and accuracy of the NSM approach to sample immigrants for studies of local immigrant communities. This approach can also be extended to recruit multisite samples of immigrants at origin and destination.

  PublisherOA PDFDOI

• The impact of two types of COVID-19-related discrimination and contemporaneous stressors on Chinese immigrants in the US South

  SSM - Mental Health · 2022 · 13 citations

  • Sociology
  • Psychology
  • Demography

  The global rise of the COVID-19 pandemic has been accompanied by an increase in anti-Asian discrimination with potentially deleterious effects on individuals of Asian descent. In the present study, we examine how two types of COVID-19-related anti-Asian discrimination and other contemporaneous stressors independently contribute to perceptions of stress in a population-representative sample of Chinese immigrants in North Carolina, as well as the moderating role of ethnic identity on the association between COVID-related discrimination and stress. Analyses rely on data collected among participants ages 18+ in the Chinese Immigrants in Raleigh-Durham (ChIRDU) study who completed surveys in 2018 and during the COVID-19 pandemic (July-September 2020). We utilize ordinary least squares regressions to examine associations of two types of COVID-related discrimination (measured by changes in perceptions of being feared by others and racism-related vigilance) and contemporaneous stressors (measured by general COVID-19-related stressors and acculturative stressors) with perceptions of stress by respondents' pre-pandemic reports of ethnic identity. Controlling for sociodemographic predictors and other stressors, racism-related vigilance is significantly associated with higher perceived stress for Chinese immigrants who identify as completely Chinese. For those who identify as at least partly American, new perceptions of being feared by others during the pandemic are significantly associated with higher perceived stress. Acculturative and COVID-related stressors are independently associated with higher perceived stress for both groups. These results suggest that COVID-related anti-Asian discrimination aggravates the psychological burden of multiple stressors in Chinese immigrants' lives by uniquely contributing to perceptions of stress alongside contemporaneous stressors. The results also highlight the heterogeneous mental health needs of Chinese immigrants and hold important implications for intervention development in the community studied here as well as in other Chinese communities in the US.

  PublisherDOI

• A Century of Key Trends and Debates in Social Stratification in <i>Social Forces</i>

  Social Forces · 2022 · 3 citations

  1st authorCorresponding
  • Sociology
  • Political Science
  • Sociology
  PublisherOA PDFDOI

Recent grants

• Carolina Population Center

  NIH · $6.6M · 2005–2027

Frequent coauthors

• M. Giovanna Merli

  Duke University

  12 shared

• Ashton M. Verdery

  Pennsylvania State University

  11 shared

• Allison Stolte

  University of California, Irvine

  7 shared

• Claire Le Barbenchon

  Duke University

  6 shared

• Arne L. Kalleberg

  University of North Carolina at Chapel Hill

  5 shared

• Peter J. Mucha

  4 shared

• Sergio Jorge Chávez

  Rice University

  4 shared

• Heather Edelblute

  West Chester University

  4 shared