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EXACT LIKELIHOOD INFERENCE IN GROUP INTERACTION NETWORK MODELS

Published online by Cambridge University Press:  19 December 2016

Grant Hillier  and
Federico Martellosio
Grant Hillier*
Affiliation:
University of Southampton
Federico Martellosio
Affiliation:
University of Surrey
*
*Address correspondence to Grant Hillier, CeMMAP and Department of Economics, University of Southampton, Highfield, Southampton SO17 1BJ, UK; e-mail: [email protected].
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Abstract

The paper studies spatial autoregressive models with group interaction structure, focussing on estimation and inference for the spatial autoregressive parameter λ. The quasi-maximum likelihood estimator for λ usually cannot be written in closed form, but using an exact result obtained earlier by the authors for its distribution function, we are able to provide a complete analysis of the properties of the estimator, and exact inference that can be based on it, in models that are balanced. This is presented first for the so-called pure model, with no regression component, but is also extended to some special cases of the more general model. We then study the much more difficult case of unbalanced models, giving analogues of some, but by no means all, of the results obtained for the balanced case earlier. In both balanced and unbalanced models, results obtained for the pure model generalize immediately to the model with group-specific regression components.

Type
ARTICLES
Information
Econometric Theory , Volume 34 , Issue 2 , April 2018 , pp. 383 - 415
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

We thank the co-editor, Rob Taylor, the three referees, and Peter Phillips for comments on the first version of the paper that improved its presentation considerably.

References

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