Resource title

GM estimation of higher order spatial autoregressive processes in panel data error component models

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Resource description

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 achieve asymptotic efficiency. We prove consistency of the proposed GM estimator and provide Monte Carlo evidence that it performs well also in reasonably small samples.

Resource author

Harald Badinger, Peter Egger

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Resource publish date

Resource language

eng

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text/html

Resource resource URL

http://hdl.handle.net/10419/26346

Resource license

Adapt according to the presented license agreement and reference the original author.