My research examines the causes and mechanisms of inequality in child development, education, income, consumption, wealth, and health among individuals and families in the United States and China. To address the complexity of social inequality and interactive nature of the factors affecting it at the interpersonal, community and societal levels, my research emphasizes the influence of multiple domains including biology, behavior, physical environment, family, school, and workplace. I test theory-derived hypotheses applying advanced quantitative and computational methods to large-scale, nationally representative panel survey data as well as administrative and big data. Below, I describe my current projects.

1. Understand the Life Course Process of Wealth Inequality

Building on my previous work on wealth inequality (1996 Social Forces; 2004 International Migration Review, 2007 book Color Lines, Country Lines), my research focuses on the life course process of wealth inequality. A current project examines the long arm of student debt for the black-white wealth gap in the United States. The combination of unlimited non-subsidized student loans and the soaring costs of postsecondary education have led to a national student debt crisis. Student debt, rooted in low parental wealth and the need to borrow for human capital investment, may create pathways of uneven wealth mobility leading to wealth inequality throughout the life course. I analyze individual wealth mobility in response to student debt accruement based on large-scale, nationally representative panel data 2014-2019. My estimates suggest that the harm caused by student debt on wealth mobility is much larger than the harm from credit card debt or loss of earnings. Furthermore, the harm is stronger for blacks than for whites.

2. Identify the Latent Structure of Employment Relations

Expanding my previous research on employment inequality (1997 American Journal of Sociology; 2004 Journal of Policy Analysis and Management; 2013 Journal of Ethnic and Migration Studies), I am a co-Principal Investigator of a current NSF project to identify the latent structure of employment relations in which employees and employers are embedded. The multidisciplinary team of sociologists, economists and applied mathematicians is developing inferential network models for dynamic employment relations observed in panel survey and administrative data with computational efficiency. We ask: What are the network communities of employment relations? How do these communities differentially shape the precarity of work? Do immigrants displace native-born workers via job mobility? Our data sources include large-scale panel surveys such as Current Population Survey (CPS) over 12 months, Survey of Income and Program Participation (SIPP) over 48 months, and the administrative-based population-wide data, the Longitudinal Employer-Household Dynamics (LEHD) over 80 quarters.

3. Social Inequality and COVID-19 Outcomes

My previous studies on population health (2000 Research on Aging; 2009 International Migration Review paper; and 2018-2021 publications based on collaborative research on health) prepared me to engage in research on social inequality and COVID-19 outcomes. There has been an increasing awareness that social factors may drive racial disparities in pandemic outcomes and exacerbate the pandemic in the United States. One project examines whether residential racial segregation may be constraining capacities for social distancing thus leaving African Americans potentially more exposed to contracting COVID-19. The paper (published in 2021) suggests that African Americans may face structural limitations to effective social distancing as evidenced by higher rates of mobility after reopening policies go into effect.

4. Social Factors and Consequences of Accelerometry Physical Activity

Objective measures of health behaviors such as physical activity via wearable devices are a significant advancement in the study of social factors and consequences of physical activities. I have been working with biostatisticians to apply data science methods to social science studies of wearable device data. Our team’s first publication (forthcoming) asks: How do occupations determine physical activity among regular daytime workers in the United States? How large a share of physical activity difference between two occupations is attributable to differences in occupational tasks, relative to workers’ demographic, health preconditions, and socioeconomic attributes? We provide answers and evidence using wearable accelerometry data on a nationally representative sample of regular day-time full-time working-age adults during work hours. Our decomposition analysis yields insights into the occupational determinant of the volume and bouts of physical activity at work.

Current and Previous Grants within 5 years

Hao, Lingxin (Principle Investigator). 2022-2026. “Hopkins Population Center.” National Institute of Health (NIH).

Hao, Lingxin (Co-Principle Investigator). 2020-2023. “Methods and Applications for Massive One-mode and Bipartite Social Networks.” National Science Foundation (NSF). (PI: Angelo Mele).

Hao, Lingxin (Principle Investigator). 2014-2020. “Research Infrastructure for the Hopkins Population Center.” National Institute of Health (NIH).

Hao, Lingxin (Principle Investigator). 2015-2017. “Agent-Based Modeling of Internal Migration.” National Institute of Health (NIH) R21.

Hao, Lingxin (Principle Investigator). 2013-2016. “Student Migration and Education Segregation.” National Science Foundation (NSF).

• 230.202 Research Methods for the Social Sciences (undergraduate)
• 230.317 Sociology of Immigration (undergraduate)
• 230.322 Quantitative Research Practicum (undergraduate)
• 230.362 Migration & Development (undergraduate; co-taught with Prof Agarwala)
• 230.605 Categorical Data Analysis (graduate)
• 230.609 Dissertation Seminar
• 230.615 Panel Data Analysis (graduate)
• 230.617 Seminar on Immigration (graduate)
• 230.618 Introduction to Computational Social Science (graduate)

Selected Articles in Referred Journals

Yu, Xiao, Lingxin Hao, Ciprian Crainiceanu, Andrew Leroux. Forthcoming 2022. “Occupational Determinants of Physical Activity at Work: Evidence from Wearable Accelerometer in 2005-2006 NHANES.” SSM – Population Health, doi: https://doi.org/10.1016/j.ssmph.2021.100989.

White, Alexandre Ilani Rein, Lingxin Hao, Xiao Yu, and Roland Thorpe. 2021. “Residential Racial Segregation and Social Distancing in the United States During the COVID-19 Pandemic.” EClinicalMedicine, Lancet. https://authors.elsevier.com/sd/article/S2589537021001206

Hao, Lingxin and Zhang, Dong. 2020. “China’s College Expansion and the Timing of College-to-Work Transition: A Natural Experiment.” The ANNALS of the American Academy of Political and Social Science, 688, 93-114.

Fu, Zhaohao and Hao, Lingxin. 2018. “Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.” Physica A, 490, 1067-1075.

Hao, Lingxin and Wei-Jun Jean Yeung. 2015. “Parental Spending on School-Age Children: The Role of SES, Race, and Parental Expectation.” Demography 52(3):835-860. (DOI) 10.1007/s13524-015-0386-1.

Hao, Lingxin, Alfred Hu, and Jamie Lo. 2014. “Two Aspects of the Rural-Urban Divide and Educational Stratification in: A Trajectory Analysis.” Comparative Education Review 58(3):509-536.

Hao, Lingxin. 2013. “Admission-Group Salary Differentials in the United States: The Significance of Labor Market Institutional Selection of High-Skilled Workers.” Journal of Ethnic and Migration Studies 1337-1360.

Hao, Lingxin and Han Soo Woo. 2012. “Distinct Trajectories in the Transition to Adulthood: Are Children of Immigrants Advantaged?” Child Development 83(5):1623-1639.

Hao & Zhang, 2020, supplementary table and figures

Hao & Naiman, 2007, Quantile Regression, Stata code and data files