specification of a spatial dynamic panel data probit (SDPDprobit) model, which allows to deal with cross-sectional dependence, time … dependence and individual (spatial) or time fixed effects in a nonlinear setting. The first ML-based estimator is a panel version …

This paper revisits the panel autoregressive model, with a primary emphasis on the unit-root case. We study a class of …

Unconditional quantile treatment effects are difficult to estimate in the presence of fixed effects. Panel data are … effects or differencing of data, however, redefines the quantiles. This paper introduces a quantile estimator for panel data …

Fixed effects estimators in nonlinear panel models with fixed T usually suffer from inconsistency because of the …

This paper introduces a panel GMM framework for identifying and estimating demand elasticities via heteroscedasticity …. While existing panel estimators address the simultaneity problem, the state-ofthe-art Feenstra/Soderbery (F/S) estimator …

This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure …

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross …

coefficients in the case of panel data models when the time dimension (T) is fixed while the cross section dimension (N) is allowed … effects in the panel. It is shown that the pooled estimator remains consistent so long as delta < 1, and is asymptotically …

compared to the cross-section dimension. -- Panel cointegration ; FM-OLS ; FM-SUR ; DOLS ; DSUR …

-IV) estimators for estimation and inference in the case of time-invariant effects in static panel data models when N is large and T … robust to error variance heteroskedasticity and residual serial correlation. …