Many panel data methods, while allowing for general dependence between covariates and time-invariant agent … panel data models and present constructive methods to derive feasible moment-based estimators for specific models. We also …

. -- panel cointegration ; fully modified ordinary least squares ; fully modified seemingly unrelated regression ; dynamic …

This paper provides a new methodology for the analysis of multiple long run relations in panel data models where the … cross section dimension, n, is large relative to the time series dimension, T. For panel data models with large n … approach is illustrated with an application to key financial variables using an unbalanced panel of US firms from merged CRSP …

it is not, practitioners need to run the so-called panel factor augmented regression instead. There are two pretesting …

In the presence of selection bias the traditional estimators for pseudo panel data models are inconsistent. This paper … finite samples. As a "side effect" the authors utilize the enlarged pseudo panel to provide a GMM consistent estimation of … the pseudo panel parameters under rejection of the null and apply the procedure to estimate the rate of return to …

The paper introduces two estimators for the linear random effects panel data model with known heteroskedasticity …. Examples where heteroskedasticity can be treated as given include panel regressions with averaged data, meta regressions and …

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a …

general equilibrium model, they back out the weight for leisure for an unbalanced panel of 52 countries over the period from … 1950 to 2009. Then, the authors perform several panel data regressions using the backed-out values of the preference for …

panel data. These models incorporate unobserved, time-varying, individual heterogeneity, which may be correlated with the …