I present a microeconometric model to analyse residential water demand using panel data. Pricing has an increasing-block structure. Database contains individual consumptions from water meters and lacks further information. Permanent income is treated as an unobservable individual effect...

We develop likelihood-based estimators for autoregressive panel data models that are consistent in the presence of time series heteroskedasticity. Bias corrected conditional score estimators, random effects maximum likelihood (RML) in levels and first differences, and estimators that impose mean...

In this paper I consider a model for the heterogeneity and dynamics of the conditional mean and the conditional variance of standarized individual wages. In particular, I propose a dynamic panel data model with individual effects both in the mean and in a conditional ARCH type variance function....

We discuss a modified objective function strategy to obtain estimators without bias to order 1/T in nonlinear dynamic panel models with multiple effects. Estimation proceeds from a bias corrected objective function relative to some target infeasible criterion. We consider a determinant based...

This paper introduces time-varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unspecified. We estimate the model’s parameters using a “grouped fixed-effects” estimator that minimizes a least-squares...

The purpose of this paper is to review recently development methods of estimation of nonlinear fixed effects panel data models with reduced bias properties. We begin by describing fixed effects estimators and the incidental parameters problem. Next the explain how to construct analytical bias...