Mozharovskyi, Pavlo and Vogler, Jan (2016). Composite marginal likelihood estimation of spatial autoregressive probit models feasible in very large samples. Econ. Lett., 148. S. 87 - 91. LAUSANNE: ELSEVIER SCIENCE SA. ISSN 1873-7374
Full text not available from this repository.Abstract
Composite Marginal Likelihood (CML) has become a popular approach for estimating spatial probit models. However, for spatial autoregressive specifications the existing brute-force implementations are infeasible in large samples as they rely on inverting the high-dimensional precision matrix of the latent state variable. The contribution of this paper is to provide a CML implementation that circumvents inversion of that matrix and therefore can also be applied to very large sample sizes. (C) 2016 Elsevier B.V. All rights reserved.
Item Type: | Journal Article | ||||||||||||
Creators: |
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URN: | urn:nbn:de:hbz:38-256845 | ||||||||||||
DOI: | 10.1016/j.econlet.2016.09.022 | ||||||||||||
Journal or Publication Title: | Econ. Lett. | ||||||||||||
Volume: | 148 | ||||||||||||
Page Range: | S. 87 - 91 | ||||||||||||
Date: | 2016 | ||||||||||||
Publisher: | ELSEVIER SCIENCE SA | ||||||||||||
Place of Publication: | LAUSANNE | ||||||||||||
ISSN: | 1873-7374 | ||||||||||||
Language: | English | ||||||||||||
Faculty: | Unspecified | ||||||||||||
Divisions: | Unspecified | ||||||||||||
Subjects: | no entry | ||||||||||||
Uncontrolled Keywords: |
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Refereed: | Yes | ||||||||||||
URI: | http://kups.ub.uni-koeln.de/id/eprint/25684 |
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