Jing Liu Ph.D.

My research uses rigorous quantitative evidence to evaluate and inform education policies at the national, state, and local levels, with the goal of improving learning opportunities for historically marginalized students in urban areas. My work broadly engages with critical policy issues including student absenteeism, exclusionary discipline, educator’s labor market, and school reform. Grounded in economic theory and policy analysis, I use both quasi-experimental designs and data science methods such as computational linguistic analysis to analyze large administrative data and unstructured information. I am also working closely with research / practice partnerships, such as the Maryland Longitudinal Data Center, San Francisco Unified School district, and the newly established DC Education Research Collaborative, to answer pressing questions to policymakers and translate research to practice.