The well-known problem of too many instruments in dynamic panel data GMM is dealt with in detail in Roodman (2009 … replaced by a data-driven statistical decision. -- Dynamic Panel Data ; Generalised Method of Moments ; Instrument …

The well-known problem of too many instruments in dynamic panel data GMM is dealt with in detail in Roodman (2009 …

spatially correlated errors in static panel data models, is extended by introducing fixed effects, a spatial lag, and a one …-period lag of the dependent variable as additional explanatory variables. Combining this approach with the dynamic panel-data GMM …, spatial lags, and sets of exogenous variables yields new spatial dynamic panel data estimators. The proposed spatially …

corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the … the dynamic panel data model GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) and supplementing the … dynamic panel data estimators. The performance of these spatial dynamic panel data estimators is investigated by means of …

-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross …

The well-known problem of too many instruments in dynamic panel data GMM is dealt with in detail in Roodman (2009 … replaced by a data-driven statistical decision. -- Dynamic panel data ; generalised method of moments ; instrument …

-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross …

panel data models are growing exponentially in number. However, for researchers it is hard to make a reasoned choice between …

that the bootstrap outperforms Parks's top competitor. The Parks estimator has been a workhorse for the analysis of panel …-section data 1995) developed an approach that uses the Prais-Winsten estimator together with "panel corrected standard errors … demonstrate its effectiveness using an innovative experimental approach that creates artificial panel datasets modelled after …