Work Changes,
Who Moves Up And Who Gets Left Behind?
Occupation Lab studies how work changes, and how those changes shape workers' careers opportunities and social mobility. Using administrative data and survey records, we examine how occupations, industries, technologies, and labor market disruptions reshape the U.S. workforce.
Learn moreThe Occupation Lab
We conduct research on how the changing structure of work, from job displacement and automation to the rise of entirely new occupations, reshapes opportunity across generations.
Drawing on decades of federal administrative and survey data, we build new measures of occupational standing and mobility, and translate that evidence into tools that broaden economic mobility.
Read moreResearch Areas
We study how occupational change shapes economic opportunity and mobility across careers and generations.
Job Displacement and Occupational Downward Mobility
How involuntary job loss reshapes workers’ occupational trajectories, with a focus on differences in mobility outcomes across workers, occupations, and local labor markets.
Industry Context and Intergenerational Mobility
How long-term changes in U.S. industrial structure have reshaped intergenerational mobility, examining whether industry remains an important dimension of status inheritance.
New Occupations, New Pathways? Intergenerational Mobility in a Restructuring Labor Market
How the emergence of new occupational titles since 1980 reshapes the destinations available to the next generation, tested with a data-driven approach to conventional log-linear models.
The Quiet Transformation: AI Exposure and Occupational Mobility in the Pre-LLM Era
Drawing on the NLSY97 and the AI Occupational Exposure (AIOE) index, this study estimates discrete-time event history models to examine how AI predicted occupational mobility in the pre-LLM decade (2010–2019).
Recent Publications
- March 6, 2026Trapped in Declining Occupations: Barriers to Worker Mobility in a Changing EconomyXi Song, Jennie E. Brand, Sukie Xiuqi Yang, Michael Lachanski · Science Advances, 12(10): eadx3471.
- May 2026AI-Accelerated Occupational Decline and the Mobility TrapXi Song, Jennie E. Brand, Sukie Yang, Michael Lachanski · American Economic Association Papers and Proceedings, 116: 246–250.
- 2026Causal Machine Learning: A Deductive-Inductive Framework for Sociological ResearchNanum Jeon, Jennie E. Brand · Kölner Zeitschrift für Soziologie & Sozialpsychologie (Cologne Journal of Sociology & Social Psychology), 78(3): 1089–1123. (Special Issue on Explanation and Causality in Sociology)