This Paper proposes a new forecasting method that exploits information from a large panel of time series. The method is based on the generalized dynamic factor model proposed in Forni, Hallin, Lippi, and Reichlin (2000), and takes advantage of the information on the dynamic covariance structure...

This paper shows how to bootstrap hypothesis tests in the context of the Parks (Efficient estimation of a system of regression equations when disturbances are both serially and contemporaneously correlated 1967) estimator. It then demonstrates that the bootstrap outperforms Parks's top...

This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the group mean estimator and the generalized...

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common...

This paper shows how to bootstrap hypothesis tests in the context of the Parks's (1967) Feasible Generalized Least Squares estimator. It then demonstrates that the bootstrap outperforms FGLS(Parks)'s top competitor. The FGLS(Parks) estimator has been a workhorse for the analysis of panel data...

This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the group mean estimator and the generalized...

This paper shows how to bootstrap hypothesis tests in the context of the Parks (Efficient estimation of a system of regression equations when disturbances are both serially and contemporaneously correlated 1967) estimator. It then demonstrates that the bootstrap outperforms Parks's top...

This paper shows how to bootstrap hypothesis tests in the context of the Parks’s (1967) Feasible Generalized Least Squares estimator. It then demonstrates that the bootstrap outperforms FGLS(Parks)’s top competitor. The FGLS(Parks) estimator has been a workhorse for the analysis of panel...

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common...

We highlight the fact that the Sargan-Hansen test for GMM estimators applied to panel data is a joint test of valid orthogonality conditions and coefficient stability over time. A possible reason why the null hypothesis of valid orthogonality conditions is rejected is therefore that the slope...