This paper considers a first-order autoregressive panel data model with individual-specific effects and a heterogeneous … autoregressive coefficient. It proposes estimators for the moments of the cross-sectional distribution of the autoregressive coefficients …, with a focus on the first two moments, assuming a random coefficient model for the autoregressive coefficients without imposing …

This paper generalizes the approach to estimating a first-order spatial autoregressive model with spatial … autoregressive disturbances (SARAR(1,1)) in a cross-section with heteroskedastic innovations by Kelejian and Prucha (2008) to the … case of spatial autoregressive models with spatial autoregressive disturbances of arbitrary (finite) order (SARAR(R,S)). We …

Kelejian and Prucha (1998, 1999) for the spatial autoregressive parameter in the disturbance process. We prove the consistency …

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial … autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional … assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance …

dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the … number of endogenous variables tends to infinity. It is shown that under such restrictions, an infinite-dimensional VAR (or … IVAR) can be arbitrarily well characterized by a large number of finite-dimensional models in the spirit of the global VAR …

. While we concede that typical VAR models put forward in the literature fail to identify oil price shocks that significantly … VAR based search on these periods, we are able to identify an oil price shock that affects the German production even on …