A0735
Title: Identification of dynamic panel logit models with fixed effects
Authors: Christopher Dobronyi - Google (United States)
Jiaying Gu - University of Toronto (Canada)
Kyoo il Kim - Michigan State University (United States)
Thomas Russell - Carleton University (Canada) [presenting]
Abstract: It is shown that identification in a general class of dynamic panel logit models with fixed effects is related to the truncated moment problem from the mathematics literature. This connection is used to show that the identified set for structural parameters and functionals of the distribution of latent individual effects can be characterized by a finite set of conditional moment equalities subject to a certain set of shape constraints on the model parameters. In addition to providing a general approach to identification, the new characterization can deliver informative bounds in cases where competing methods deliver no identifying restrictions, and can deliver point identification in cases where competing methods deliver partial identification. An estimation and inference procedure is then presented that uses semidefinite programming methods, is applicable with continuous or discrete covariates, and can be used for models that are either point- or partially-identified. Finally, the identification result is illustrated with a number of examples, and an empirical application is provided to employment dynamics using data from the National Longitudinal Survey of Youth.
