Consistent Estimation of Panel Data Models with a Multifactor Error Structure when the Cross Section Dimension is Large

The paper studies a panel data models with a multifactor structure in both the errors and the regressors in a microeconometric setting in which the time dimension is fixed and possibly very small. An estimator is proposed that is consistent for fixed T as N tends to infinity and that does not impose restrictive conditions on the number of factors or the number of regressors or the time series properties of the panel. A small Monte Carlo simulation shows that this estimator is very accurate for very small values of T. Two empirical cases are provided to demonstrate performances of our estimator in practice.