The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data
This paper analyzes a growing group of fixed T dynamic panel data estimators with a multi-factor err...
This paper develops a break detection procedure for the well-known AR(p) linear panel data model wit...
We examine which methods are appropriate for estimating dynamic panel data models in empirical corpo...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulati...
This paper examines analytically and experimentally why the system GMM estimator in dynamic panel da...
This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects w...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
†I am deeply grateful to Taku Yamamoto for his helpful and constructive comments. I also would like ...
This paper provides a new econometric framework to make inference about structural breaks in panel d...
Endogeneity bias can lead to inconsistent estimates and incorrect inferences, which may provide misl...
The “difference ” and “system ” generalized method of moments (GMM) estimators for dynamic panel mod...
2015-06-18Dynamic panel models has very wide economic application in labor economics, health economi...
This paper analyzes a growing group of fixed T dynamic panel data estimators with a multi-factor err...
This paper develops a break detection procedure for the well-known AR(p) linear panel data model wit...
We examine which methods are appropriate for estimating dynamic panel data models in empirical corpo...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
The effects of structural breaks in dynamic panels are more complicated than in time series models a...
We assess the performance of widely-used dynamic panel data estimators based on Monte Carlo simulati...
This paper examines analytically and experimentally why the system GMM estimator in dynamic panel da...
This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects w...
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in ...
†I am deeply grateful to Taku Yamamoto for his helpful and constructive comments. I also would like ...
This paper provides a new econometric framework to make inference about structural breaks in panel d...
Endogeneity bias can lead to inconsistent estimates and incorrect inferences, which may provide misl...
The “difference ” and “system ” generalized method of moments (GMM) estimators for dynamic panel mod...
2015-06-18Dynamic panel models has very wide economic application in labor economics, health economi...
This paper analyzes a growing group of fixed T dynamic panel data estimators with a multi-factor err...
This paper develops a break detection procedure for the well-known AR(p) linear panel data model wit...
We examine which methods are appropriate for estimating dynamic panel data models in empirical corpo...