Showing 1 - 10 of 13,917
-Bond GMM estimation techniques for single dynamic panel data models with possibly endogenous regressors and cross …
Persistent link: https://www.econbiz.de/10010476668
panel data models are growing exponentially in number. However, for researchers it is hard to make a reasoned choice between …
Persistent link: https://www.econbiz.de/10011654182
This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial …
Persistent link: https://www.econbiz.de/10003808637
We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel …
Persistent link: https://www.econbiz.de/10011447728
This paper develops an instrumental variable (IV) estimator for consistent estimation of dynamic panel data models with … estimators in dynamic panel data models. The finite sample performance of the proposed estimator is investigated using simulated …
Persistent link: https://www.econbiz.de/10011804740
This paper develops a method for testing for the presence of a single structural break in panel data models with …
Persistent link: https://www.econbiz.de/10013014830
This paper studies panel data models with interactive fixed effects where the regressors are allowed to be correlated …
Persistent link: https://www.econbiz.de/10014077905
We examine the asymptotic properties of IV, GMM or MLE to estimate dynamic panel data models when either N or T or both …
Persistent link: https://www.econbiz.de/10013028926
panel data model, do not separately identify the autoregressive parameter when its true value is close to one and the …
Persistent link: https://www.econbiz.de/10013227367
This paper proposes estimating linear dynamic panels by explicitly exploiting the endogeneity of lagged dependent variables and expressing the crossmoments between the endogenous lagged dependent variables and disturbances in terms of model parameters. These moments, when recentered, form the...
Persistent link: https://www.econbiz.de/10014636394