A spatial econometrics analysis for road accidents in Lisbon

Paula Simões, Silvia Shrubsall, Isabel Natario

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms, considering transformed data to meet the specificities of the application of these techniques. In all the cases no spatial autocorrelation was detected. Given the ongoing analysis and the discrete nature of data, several hierarchical log-Poisson models were further fitted, in a Bayesian setting, implementing a different approach and finding some evidences of spatial structure in data.

Original languageEnglish
Pages (from-to)152-173
Number of pages22
JournalInternational Journal of Business Intelligence and Data Mining
Issue number2
Publication statusPublished - 2015
Event14th International Conference on Computational Science and Its Applications (ICCSA) - University of Minho, Guimaraes, Portugal
Duration: 30 Jun 20143 Jul 2014


  • Conditional autoregressive priors
  • Hierarchical log-Poisson Bayesian model
  • Lagrange multipliers tests
  • Moran's I
  • Portugal
  • Road accidents
  • SAR model
  • SEM
  • Spatial autoregressive model
  • Spatial econometrics
  • Spatial error model


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