Applying Data Science Approaches to Understand Residential Mobility Patterns

Berkeley Computational Social Science Forum

CSS Training Program

February 22, 2022
4:00pm to 5:00pm
Virtual Participation


Berkeley Computational Social Science Forum
Date: Tuesday, February 22, 2022
Time: 4:00-5:00 PM Pacific Time
Location: Virtual Participation – Register to attend via Zoom

Applying Data Science Approaches to Understand Residential Mobility Patterns Before and After Seattle’s $15 Minimum Wage

Mahader TameneBerkeley Computational Social Science Fellow, BIDS and Berkeley School of Public Health; with colleagues from the Seattle $15 Minimum Wage Project, part of the Data Science for Social Good (DSSG) summer program at the University of Washington: Jennie Romich, Professor of Social Welfare, and Faculty Director of the West Coast Poverty Center; Jose Hernandez, Senior Data Scientist, eScience Institute; Valentina Staneva, Senior Data Scientist, eScience Institute; James Lamar Foster, PhD Candidate, College of Education; Delaney Glass, PhD Student, Biological Anthropology; and Christopher Salazar, PhD Student, Industrial and Systems Engineering

Abstract: Using unique longitudinal administrative data of close to 6 million workers’ records, we examine how residential mobility within a high-cost housing market may have impacted the effect of Seattle's $15 minimum wage ordinance on low-wage workers. Specifically, we document residential patterns of low-wage Seattle workers and their impacts on commute times over the period 2013 - 2016.  We find the ratio of low-wage workers living within the city decreased while the proportion of those living in the outskirts increased. Displacement appears to play a role in these residential mobility patterns, with low-wage Seattle workers being more likely to move than their non-low wage counterparts. Additionally, higher earners’ commutes times shortened relative to commute times of lower-paid workers.  Our results indicate that the $15 minimum wage increase appears to be helpful for some but insufficient for many. Comprehensive measures, such as public investment in more affordable housing and expanded social programs for health insurance and housing, in conjunction with raising renters’ income, should be considered to sufficiently address the dual crises of housing and income inequity.

The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. This Forum is organized as part of the Computational Social Science Training Program, and weekly meetings are hosted by researchers from BIDS and D-Lab. The group welcomes social scientists and researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. Interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact for more information or if you are interested in presenting current research for an upcoming session.


Mahader Tamene

PhD Student, Epidemiology, Berkeley School of Public Health, UC Berkeley

Mahader Tamene is a PhD student in the Division of Epidemiology at UC Berkeley's School of Public Health. A public health scholar dedicated to facilitating health and justice for underserved populations globally, her research focuses on maternal and child mental health disparities, particularly community-based interventions that address the structural forces driving these disparities. Tamene has worked in community health education, health research, program implementation and evaluation both domestically and abroad. She holds an MSc in global health and population from Harvard T.H. Chan School of Public Health and a BA in public policy and African/African-American studies from the University of Chicago.

Jennie Romich

Professor of Social Welfare, University of Washington; and Faculty Director, West Coast Poverty Center

Jennie Romich is a Professor of Social Welfare at the UW School of Social Work and Faculty Director of the West Coast Poverty Center. Romich’s research focuses on poverty, low-paid workers, and families’ interactions with public policy. Her recent projects include mixed-method evaluations of the Seattle Paid Safe and Sick Time Ordinance and $15 minimum wage. She co-leads the national effort on “Reducing Extreme Economic Inequality” for the American Academy of Social Work & Social Welfare’s Grand Challenges Initiative and co-chairs a national research network on “Poverty, Employment, and Self-Sufficiency” through the U.S. Collaborative of Poverty Centers. As the principal investigator of the Washington Merged Longitudinal Administrative Data, Romich is excited to work with the DSSG summer project as a way of learning about data science techniques applicable to large-scale administrative data set. She looks forward to answering some heretofore unanswerable questions about residential mobility and poverty policy.


Jose Hernandez

Senior Data Scientist, eScience Institute, University of Washington

Jose Hernandez is a senior data scientist at the University of Washington’s eScience Institute. He received his BA from the University of California, Irvine in Social Ecology (2001-2006) and his Ph.D. in Educational Measurement and Statistics from the University of Washington where he studied the application of causal inference methodology in the absence of randomization on complex data structures (2010-2015). Hernandez has worked most of his career in the social science/education data science research space. His current work focuses on applying machine learning methods to extract novel data sources from large administrative data sets that are used to inform policy making in education and housing. Hernandez' research and data science project interests are informed by his lived experiences as a first generation high school graduate raised in a Latinx immigrant community in South Central Los Angeles and Santa Ana, CA. He is excited for the opportunity to participate in DSSG and learn about the impacts of minimum wage policies locally, as well as the opportunity to collaborate with this year’s fellows.

Valentina Staneva

Senior Data Scientist, eScience Institute, University of Washington

Valentina Staneva is a Senior Data Scientist at University of Washington’s eScience Institute. As part of her role she collaborates with researchers from a wide range of domains on extracting information from large datasets such as images and time series. She regularly teaches data science skills and best practices for reproducible research to diverse audiences. Staneva holds a Ph.D. in Applied Mathematics & Statistics from Johns Hopkins University with a focus on computer vision, and previously worked at Los Alamos National Laboratory on problems in imaging, optimization and compressed sensing.

James Lamar Foster

Ph.D. Candidate, College of Education, University of Washington

James Lamar Foster is a Ph.D. Candidate at The University of Washington’s Education Policy, Organizations, and Leadership program in the College of Education. His work investigates questions at the intersections of race, place, policy, and practice. His current research uses analytical approaches from critical and organizational theory in concert with computational methods to understand how school leaders create conditions to foster marginalized students’ social-emotional development. Foster has been interested in the work of DSSG fellows since arriving at the University of Washington. Their focus on computational methods and social good piqued his interest, which prompted him to apply. He is particularly excited to work on the Geography, Equity, and the Seattle $15 minimum wage ordinance project, which explicitly focuses on equity, policy, and place. 

Delaney Glass

Ph.D. Student, Biological Anthropology, University of Washington

Delaney Glass is a 3rd year Ph.D. student in Biological Anthropology at the University of Washington. As a human biologist and anthropologist, her work probes the effects of and variation in biologically measured and perceived stress among children and adolescents. She utilizes mixed methods and interdisciplinary approaches from evolutionary biology, cultural anthropology, and social epidemiology. Her current research utilizes previously collected and archived biological samples from the Chaco Area Reproductive Ecology Program to understand neuroendocrine variation across early to mid-puberty among indigenous Qom girls living in Argentina. Additionally, her proposed research in Amman, Jordan, will focus on how global-local dynamics, intra-individual variation in cultural consensus, and adolescent stress interact with the timing, tempo, and hormonal variation in early to mid-adolescence. She is passionate about transparent and reproducible research and utilizing qualitative and quantitative data.

Christopher Salazar

PhD Student, Industrial and Systems Engineering, University of Washington

Chris is an incoming PhD student in Industrial and Systems Engineering at the University of Washington. Prior to returning to academia, Salazar worked as a structural engineer where he primarily worked on disaster response work upon the aftermath of catastrophic events such as Hurricane Harvey, Hurricane Maria, earthquakes in Mexico/Alaska, and other similar events. This type of work has carried into working in the Disaster Data Science Lab (UW), where he developed an algorithm to estimate distance in images between pedestrians for adjudicating social distance compliance. He is excited and humbled by the prospect of working with other DSSG fellows, data scientists and project leads on the “Geography, equity, and the Seattle $15 minimum wage ordinance” project.