Castagnetti et al. (2015) propose two max-type statistics to test for the presence of a factor structure in a large stationary panel data model. In this contribution, we study the use of Hausman-type statistics based on the CCE estimator of Pesaran (2006) and the IE estimator developed by Bai...

This paper develops an estimation and testing framework for a stationary large panel model with observable regressors and unobservable common factors. We allow for slope heterogeneity and for correlation between the common factors and the regressors. We propose a two stage estimation procedure...

This paper considers estimation in a stationary heterogeneous panel model where common unknown factors are present. A two-stage estimator is proposed. This estimator is based on the CCE estimator (Pesaran, 2006) in the first stage and on a similar approach to the Interactive Effect estimator...

This paper develops an estimation and testing framework for a stationary large panel model with observable regressors and unobservable common factors. We allow for slope heterogeneity and for correlation between the common factors and the regressors. We propose a two stage estimation procedure...

This paper studies the asymptotic validity of sieve bootstrap for nonstationary panel factor series. Two main results are shown. Firstly, a bootstrap Invariance Principle is derived pointwise in i, obtaining an upper bound for the order of truncation of the AR polynomial that depends on n and...

Castagnetti, Rossi and Trapani (2014) propose two max-type statistics to test for the presence of a factor structure in a large stationary panel data model. We investigate the use of alternative approaches as average-type and Hausman-type statistics. We show that both approaches can not be used....