In this paper we suggest panel data unit root tests which allow for a structural breaks in the individual effects or linear trends of panel data models. This is done under the assumption that the disturbance terms of the panel are heterogeneous and serially correlated. The limiting distributions...

Analytical asymptotic local power functions are employed to study the effects of general form short term serial correlation on �fixed-T panel data unit root tests. Two models are considered, one that has only individual intercepts and one that has both individual intercepts and individual...

The asymptotic local power of least squares based fixed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. These tests correct the least squares estimator of the autoregressive coefficient of this...

Missing data or missing values are a common phenomenon in applied panel data research and of great interest for panel data unit root testing. The standard approach in the literature is to balance the panel by removing units and/or trimming a common time period for all units. However, this...

This paper develops a new method for testing for Granger non-causality in panel data models with large cross-sectional (N) and time series (T) dimensions. The method is valid in models with homogeneous or heterogeneous coefficients. The novelty of the proposed approach lies on the fact that...

Standard banking theory suggests that there exists an optimal level of credit risk that yields maximum bank profit. We identify the optimal level of risk-weighted assets that maximizes banks’ returns in the full sample of US banks over the period 1996–2011. We find that this optimal level is...