Citation
Dadashova, Bahar and Arenas Ramírez, Blanca del Valle and Mira McWilliams, José Manuel and Aparicio Izquierdo, Francisco
(2014).
Bayesian model selection methodology for road safety.
In: "8th International Conference on Computational and Financial Econometrics and 7th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics", 06/12/2014 - 08/12/2014, Pisa, Italy. ISBN 978-84-937822-4-5. p. 65.
Abstract
Road accidents are a very relevant issue in many countries and macroeconomic models are very frequently applied by
academia and administrations to reduce their frequency and consequences. The selection of explanatory variables and
response transformation parameter within the Bayesian framework for the selection of the set of explanatory variables a TIM and 3IM (two input and three input models) procedures are proposed. The procedure also uses the DIC and
pseudo -R2 goodness of fit criteria. The model to which the methodology is applied is a dynamic regression model with
Box-Cox transformation (BCT) for the explanatory variables and autorgressive (AR) structure for the response. The
initial set of 22 explanatory variables are identified. The effects of these factors on the fatal accident frequency in Spain, during 2000-2012, are estimated. The dependent variable is constructed considering the stochastic trend component.
