Panel data models with cross-sectionally heteroskedastic data often suffer from the well-known incidental parameters problem. Some recent studies have proposed that the structural parameters (common parameters to all of the cross-sectional entities) can be consistently estimated if they are...

This paper considers a general multi-level group factor model in which there are R different cross-sectional groups of entities, and latent factors may influence all or only a subset of the R groups. There are r^G global factors that affect all R groups; r^{H(k)} intermediate-level regional...

We consider Partial Least Squares (PLS) estimation of a time-series forecasting model with the data containing a large number (T) of time series observations on each of a large number (N) of predictor variables. In the model, a subset or a whole set of the latent common factors in predictors are...

Under the APT framework and the assumption that the market portfolio is well-diversified, if not mean-variance efficient, the common factors in raw-returns are the market return plus the common factors in the space of excess-returns over the market return. This explains why the market betas fail...

We consider the estimation methods for the rank of a beta matrix corresponding to a multifactor model and study which method would be appropriate for data with a large number of assets. Our simulation results indicate that a restricted version of Cragg and Donald's (1997) Bayesian Information...

This paper proposes two new estimators for determining the number of factors (r) in static approximate factor models. We exploit the well-known fact that the r largest eigenvalues of the variance matrix of N response variables grow unboundedly as N increases, while the other eigenvalues remain...

This paper examines the asymptotic properties of the popular within, GLS estimators and the Hausman test for panel data models with both large numbers of cross-section (N) and time-series (T) observations. The model we consider includes the regressors with deterministic trends in mean as well as...