Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

Estimating spatial models with endogenous variables, a spatial lag and spatially dependent distrurbances: Finite sample properties

Fingleton, B. and Le Gallo, J. (2008) Estimating spatial models with endogenous variables, a spatial lag and spatially dependent distrurbances: Finite sample properties. Papers in Regional Science, 87 (3). pp. 319-339. ISSN 1056-8190

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

This paper discusses estimation methods for models including an endogenous spatial lag, additional endogenous variables due to system feedback and an autoregressive or a moving average error process. It extends Kelejian and Prucha's, and Fingleton and Le Gallo's feasible generalized spatial two-stage least squares estimators and also considers HAC estimation in a spatial framework as suggested by Kelejian and Prucha. An empirical example using real estate data illustrating the different estimators is proposed. The finite sample properties of the estimators are finally investigated by means of Monte Carlo simulation.