Emma Kate Henry
Ph.D. Candidate in Economics,
University of Alabama
I develop nonparametric and semiparametric methods for panel data, with a focus on correlated random effects models. These models enable researchers to work with longitudinal data without committing to a functional form for how unobserved heterogeneity relates to the covariates. My three chapters relax that commitment in progressively challenging settings: an unknown regression function, a model that is nonlinear in parameters with an unrestricted individual effect, and a model in which common shocks affect units heterogeneously through interactive fixed effects. Each chapter pairs the estimator with a specification test, and I apply the methods to questions in innovation and R&D.
Research interests
Primary: Panel data, nonparametric and semiparametric estimation, correlated random effects, interactive fixed effects.
Secondary: Innovation, R&D, and firm productivity.
Dissertation
Nonparametric and Semiparametric Correlated Random Effects Models
Three chapters, each relaxing a functional-form assumption that standard panel estimators impose on unobserved heterogeneity. The first develops nonparametric correlated random effects and is published in Advanced Studies in Theoretical and Applied Econometrics. The second carries the approach into nonlinear models, where the usual robustness of the linear case breaks down, and is under revision at Economics Letters. The third, my job market paper, adds interactive fixed effects. All three are on the research page.
Committee: Daniel J. Henderson (chair), Soroush Ghazi, Robert Hammond, Alexandra Soberón, and Emmanuel Tsyawo.
Education
Funded research
Spanish Ministry for Science and Innovation Grant (PID2024-156871NB-I00)
Host: University of Cantabria, Santander, Spain2025 – 2029