Del 20 al 22 de Junio de 2018 tendrá lugar en Las Palmas de Gran Canaria la XXXVIII edición de las Jornadas de la Asociación de Economía de la Salud bajo el lema "Compartiendo decsiones: ¿Qué cambios se requieren?

Comité Organizador:


Laura Vallejo-Torres

Vocales: Ignacio Abásolo, Patricia Barber, Sara González, Beatriz González, Christian González, Cristina Hernández-Quevedo, Miguel A. Negrín, Jaime Pinilla, Alejandro Rodríguez




Likelihood-based inference for power distributions
Ponente/Speaker: Héctor W. Gómez (Universidad de Antofagasta (Chile)).
Fecha/Date: 20-04-2018.
Lugar/Venue: Aula de informática D3.6.
Hora/Time: 12:00.


This paper considers likelihood-based inference for the family of power distributions. Widely applicable
results are presented which can be used to conduct inference for all three parameters of the general
location-scale extension of the family. More speci c results are given for the special case of the power
normal model. The analysis of a large data set, formed from density measurements for a certain type of
pollen, illustrates the application of the family and the results for likelihood-based inference. Through-
out, comparisons are made with analogous results for the direct parametrisation of the skew-normal

Key Contact: E. Gómez-Déniz.



Las Profesoras Beatriz González y Dolores R. Santos participan en el evento "Mujer, Cultura y Ciencia en la ULPGC".


Con motivo del Día Mundial de la Creatividad y la Innovación, el pasado día 21 de abril se celebró en el Museo Elder de la Ciencia y la Tecnología la Jornada ULPGC Cultura Creativa y Divulgación de la Cultura Científica, con una exposición fotográfica titulada: Mujer, Cultura y Ciencia en la ULPGC.


mujer cultura ciencia

Título/Title: Model Averaging techniques with economic applications: a Bayesian perspective
Ponente/Speaker: Gonzalo García-Donato (Universidad de Castilla-La Mancha).
Fecha/Date: 16-03-2018.
Lugar/Venue: Aula de Informática D3.6.
Hora/Time: 12:00.

Abstract: A common situation in applied disciplines is that there is no a universally accepted theory leading to the construction of a single statistical model. More on the contrary, several different statistical models may be built based on the consideration of alternative sensible theories about the problem under study. This context is normally handled choosing one of these competing models then producing inferences conditionally on this (now fixed) model. Nevertheless, this approach obviates the uncertainty regarding which is the true model leading to an underevaluation of the variability and potentially to incorrect inferences. The statistical techniques that explicitly consider this source of extra variability through weighting inferences over the different models are called Model Averaging (MA). These procedures have received great interest in social sciences and in economics in particular and will be the subject of this talk. We will review the basic aspects about the usage of MA with special focus on the Bayesian approach, which arguably is the natural way to approach the problem. The emphasis is placed on applicability and examples of applications in economics will be given jointly with a review of the software that can be used to approach a MA problem.