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 | ||||||||||||
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| Refereed: | Yes | ||||||||||||
| URI: | http://kups.ub.uni-koeln.de/id/eprint/25684 |
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