In this paper we consider the estimation of a dynamic panel autoregressive (AR) process of possibly infinite order in the presence of individual effects. We employ double asymptotics under which both the cross-sectional sample size and the length of time series tend to infinity and utilize the...

We consider instrumental variables estimation of a possibly infinite order dynamic panel autoregressive (AR) process with individual effects. The estimation is based on the sieve AR approximation with its lag order increasing with sample size. Transforming the variable to eliminate individual...

This paper proposes the analysis of panel data whose dynamic structure is heterogeneous across individuals. Our aim is to estimate the cross-sectional distributions and/or some distributional features of the heterogeneous mean and autocovariances. We do not assume any specific model for the...

This paper studies the asymptotic efficiency in factor models with serially correlated errors and dynamic panel data models with interactive effects. We derive the efficiency bound for the estimation of factors, factor loadings and common parameters that describe the dynamic structure. We use...

We propose a nonparametric test for Granger-type causality. A conceptually similar work will be Hidalgo (2000), who introduced a nonparametric Granger causality test in the frequency domain for weakly stationary linear processes. He is mainly concerned with the test under long range dependent...

This paper proposes a method of averaging generalized least squares (GLS) estimators for linear regression models with heteroskedastic errors. We derive two kinds of Mallows' Cp criteria, calculated from the estimates of the mean of the squared errors of the tted value based on the averaged GLS...

The most popular econometric models in the panel data literature are the class of linear panel data models with unobserved individual- and/or time-specific effects. The consistency of parameter estimators and the validity of their economic interpretations as marginal effects depend crucially on...

We propose a new class of specification tests for Autoregressive Conditional Duration (ACD) models. Both linear and nonlinear ACD models are covered, and standardized innovations can have time-varying conditional dispersion and higher order conditional moments of unknown form. No specific...