This paper proposes a new panel unit root test based on the generalized method of moments approach for panels with a small number of time periods and a large number of cross-section units, N. In the model that we consider the deterministic trend function is essentially unrestricted and the...

This paper proposes a partially heterogeneous framework for the analysis of panel data with fixed T , based on the concept of "partitional clustering". In particular, the population of cross-sectional units is grouped into clusters, such that parameter homogeneity is maintained only within...

This paper provides an overview of the existing literature on panel data models with error cross-sectional dependence. We distinguish between spatial dependence and factor structure dependence and we analyse the implications of weak and strong cross-sectional dependence on the properties of the...

This paper develops an instrumental variable (IV) estimator for consistent estimation of dynamic panel data models with error cross-sectional dependence when both N and T, the cross-section and time series dimensions respectively, are large. Our approach asymptotically projects out the common...

This paper considers the issue of GMM estimation of a short dynamic panel data model when the errors are correlated across individuals. We focus particularly on the conditions required in the cross-sectional dimension of the error process for the dynamic panel GMM estimator to remain consistent....

This paper considers panel data regression models with weakly exogenous or endogenous regressors and residuals generated by a multi-factor error structure. In this case, the standard dynamic panel estimators fail to provide consistent estimates of the parameters. We propose a new estimation...

This paper analyzes a growing group of fixed T dynamic panel data estimators with a multi-factor error structure. We use a unified notational approach to describe these estimators and discuss their properties in terms of deviations from an underlying set of basic assumptions. Furthermore, we...

We propose a new methodology for estimating the demand and cost functions of differentiated products models when demand and cost data are available. The method deals with the endogeneity of prices to demand shocks and the endogeneity of outputs to cost shocks, but does not require instruments...