A Bayesian Spatial Autoregressive Logit Model With An Empirical Application to European Regional FDI Flows

Tamás Krisztin and Philipp Piribauer ()

No 586, WIFO Working Papers from WIFO

Abstract: In this paper we propose a Bayesian estimation approach for a spatial autoregressive logit specification. Our approach relies on recent advances in Bayesian computing, making use of Pólya-Gamma sampling for Bayesian Markov-chain Monte Carlo algorithms. The proposed specification assumes that the involved log-odds of the model follow a spatial autoregressive process. Pólya-Gamma sampling involves a computationally efficient treatment of the spatial autoregressive logit model, allowing for extensions to the existing baseline specification in an elegant and straightforward way. In a Monte Carlo study we demonstrate that our proposed approach significantly outperforms existing spatial autoregressive probit specifications both in terms of parameter precision and computational time. The paper moreover illustrates the performance of the proposed spatial autoregressive logit specification using pan-European regional data on foreign direct investments. Our empirical results highlight the importance of accounting for spatial dependence when modelling European regional FDI flows.

Keywords: Spatial autoregressive logit; Bayesian MCMC estimation; FDI flows; European regions (search for similar items in EconPapers)
Pages: 26 pages
Date: 2019-08
New Economics Papers: this item is included in nep-ecm, nep-eff, nep-geo, nep-ore and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.wifo.ac.at/wwa/pubid/61925 abstract (text/html)

Related works:
Journal Article: A Bayesian spatial autoregressive logit model with an empirical application to European regional FDI flows (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wfo:wpaper:y:2019:i:586

Access Statistics for this paper

More papers in WIFO Working Papers from WIFO Contact information at EDIRC.
Bibliographic data for series maintained by Florian Mayr ().