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)...

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...

We adopt a spatial econometric approach to estimate intra- and inter-industry productivity spillovers in total factor productivity transmitted through input-output relations in a sample of 13 OECD countries and 15 manufacturing industries. Both R&D spillovers as well as remainder,...

This paper assesses the strength of productivity spillovers non-parametrically in a data-set of 12 industries and 231 NUTS2 regions in 17 European Union member countries between 1992 and 2006. It devotes particular attention to measuring catching up through spillovers depending on the technology...

type="main" xml:lang="en" <title type="main">Abstract</title> <p>This paper sheds light on interdependencies in multinational activity that are brought about by (horizontal) trade in final goods and (vertical) trade in intermediate goods (within and between host countries). We use a panel data set of US foreign affiliate...</p>

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...

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)...

This paper presents a generalized moments (GM) approach to estimating an R-th order spatial regressive process in a panel data error component model. We derive moment conditions to estimate the parameters of the higher order spatial regressive process and the optimal weighting matrix required to...