Gallant is interested in fitting models from the sciences to data for the purpose of statistical inference. Typically these models will involve a nonlinear parametric component that describes features of the model where the underlying scientific theory is explicit and a nonparametric component that accounts for features where the scientific theory is vague. Appropriate statistical methods for these problems are usually computationally intensive. Methodological interests are in developing statistical methods and numerical algorithms for fitting these models. Theoretical interests are in deriving the statistical properties of proposed methods, particularly the asymptotic properties of estimators of functionals of the nonparametric component.
Applied interests are primarily within economics and finance.
David Guilkey David Guilkey, Professor and Chair of Economics, is an econometrician interested in statistical problems associated with large survey data sets. His current work involves the development of estimation methods to predict outcomes such as contraceptive choice and recent fertility. His primary measurement focus is on correctly estimating the effects of external factors such as resource inputs on ultimate outcomes. He is working with Thomas Mroz and Gustavo Angeles to extend economic structural models for use in the study of the determinants of fertility when government program placement is targeted. They are applying their methods to data sets from Peru and Tanzania and presented a paper on this topic at the 1998 PAA meeting.