In this paper, we propose a robust approach against heteroskedasticity, error serial correlation and slope … correlation and dependence of the random coefficient with covariates. The test is of great importance, since the widely used …

estimator, we show that when T is large, a generalized least squares estimator that ignores the correlation between the … the known correlation pattern, we derive the asymptotic properties of panel least squares estimators. Simulations are used …

that standard interaction term estimation underestimates the importance of a country's income level in the relationship …

This paper considers the problem of testing cross-sectional correlation in large panel data models with serially …-correlated errors. It finds that existing tests for cross-sectional correlation encounter size distortions with serial correlation in … account for serial correlation of an unknown form in the error term. We derive the limiting distribution of this test as (N …

In this paper, we consider the estimation of a dynamic panel data model with non-stationary multi-factor error … structures. We adopted the common correlated effect (CCE) estimation and established the asymptotic properties of the CCE and … variety of data generation processes. Empirical findings suggest that the CCE estimation is widely applicable to models with …

common correlated effects (CCE) estimation technique, we propose a Stein-like combined estimator of the CCE full …-sample estimator (i.e., estimation using both the pre-break and post-break observations) and the CCE post-break estimator (i ….e., estimation using only the post-break sample observations). The proposed Stein-like combined estimator benefits from exploiting …

coefficients. Two classes of estimation procedures are proposed, one based on station averaged data the other on the full panel …