Title: Time-varying panel data models with additive factor structure
Authors: Fei Liu - Nankai University (China) [presenting]
Abstract: A nonparametric panel data model with time-varying regression coefficients and an additive factor structure is considered. This model is motivated by some explored features of real data from economics and finance. In the model, factor loadings are unknown functions of observable variables which can capture time-variant and heterogeneous covariate information. We propose a profile marginal integration (PMI) method to estimate unknown coefficient functions, factors and their loadings jointly in a single step. The asymptotic distributions for the proposed profile estimators are established. Our research fills the gap of insufficient discussions on the factors and loadings' asymptotic properties. The finite sample performance of our estimators is assessed by both simulations and empirical studies on US stock return data, which demonstrate the advantages in modelling and estimation approach in practice.