This paper develops a Stein-like combined estimator for large heterogeneous panel data models under common structural breaks. The model allows for cross-sectional dependence through a general multifactor error structure. By utilizing the common correlated effects (CCE) estimation technique, we...

This study proposes a regression-based estimation method in difference-in-differences settings in the presence of time-varying covariates - a scenario commonly encountered in applications. We impose only a conditional parallel trends assumption with time-varying covariates and plausible...

We consider a framework for analyzing panel data characterized by: (i) a system of regressions equations, (ii) random individual heterogeneity in both intercepts and slope coefficients, and (iii) unbalanced panel data, i.e., panel data where the individual time series have unequal length. A...

In this paper, we consider the formulation and estimation of systems of regression equations with random individual effects in the intercept terms from unbalanced panel data, i.e., panel data where the individual time series have unequal length. Generalized Least Squares (GLS) estimation and...

This paper provides a new methodology for the analysis of multiple long run relations in panel data models where the cross section dimension, n, is large relative to the time series dimension, T. For panel data models with large n researchers have focussed on panels with a single long run...

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...

In this article, we propose a new estimator of panel data models with interactive fixed effects and multiple structural breaks that is suitable when the number of time periods, T, is fixed and only the number of cross-sectional units, N, is large. This is done by viewing the determination of the...

General Method of Moments (GMM) estimation of a linear one-equation model using panel data with errors-in-variables is considered. To eliminate fixed individual heterogeneity, the equation is differenced across one or more than one periods and estimated by means of instrumental variables. With...

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...