Mundlak (1978) proposed the addition of time averages to the usual panel equation in order to remove the fixed effects bias. We extend this Mundlak equation further by replacing the time-varying explanatory variables by the corresponding deviations from the averages over time, while keeping the...

Mundlak (1978) proposed the addition of time averages to the usual panel equation in order to remove the fixed effects bias. We extend this Mundlak equation further by replacing the time-varying explanatory variables by the corresponding deviations from the averages over time, while keeping the...

Identification of equations explaining a continuous variable, e.g., the length of sickness absence spells, by age, cohort and time (ACT), subject to their definitional identity is reconsidered. Various extensions of a linear equation to polynomials are explored. If no interactions between the...

An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. However, this strategy does not yield a genuine within estimator. Instead, an estimator is produced that reflects unit-level differences of interacted variables whose moderators vary within...

Unconditional quantile treatment effects are difficult to estimate in the presence of fixed effects. Panel data are frequently used because fixed effects or differences are necessary to identify the parameters of interest. The inclusion of fixed effects or differencing of data, however,...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

This paper considers estimation of panel data models with fixed effects. First, we will show that a consistent "unrestricted fixed effects" estimator does not exist for autoregressive panel data models with initial conditions. We will derive necessary and sufficient conditions for the...

Computational aspects concerning a model for clustered binary panel data are analysed. The model is based on the representation of the behavior of a subject (individual panel member) in a given cluster by means of a latent process that is decomposed into a cluster-specific component, which...

This paper proposes a semiparametric estimator for spatial autoregressive (SAR) binary choice models in the context of panel data with fixed effects. The estimation procedure is based on the observational equivalence between distribution free models with a conditional median restriction and...