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Contenido archivado el 2024-06-11

A critical assessment of bayesian modelling assumptions and their application to econometrics and environmental science

Objetivo



The aim of the methodological work is to broaden the scope of Bayesian modelling, so as to provided a more useful and realistic treatment for applied problems. We can categorize this work in three main groups: 1. Inference robustness: it consists in assessing the influence of modelling assumptions on the actual inference.
2. Modelling and inference through non-standard distributions: I introduce new classes of distributions that can be more adequate for modelling certain data sets (displaying e. g. skewness and/or fat tails). 3. Reference priors: it deals with finding a prior distribution which adequately captures a lack of prior information. I would like to find this reference prior for stochastic frontier models.
In terms of econometric applications, I would like to investigate theoretical and practical aspects of stochastic frontier models, as well as to treat financial data using nonstandard distributions as mentioned above. In environmental science, I am trying to develop a statistical model for estimating fish captures.

Ámbito científico (EuroSciVoc)

Programa(s)

Tema(s)

Convocatoria de propuestas

Datos no disponibles

Régimen de financiación

RGI - Research grants (individual fellowships)

Coordinador

TILBURG UNIVERSITY
Aportación de la UE
Sin datos
Dirección
Warandelaan 2
5037 AB TILBURG
Países Bajos
Coste total
Sin datos

Participantes (1)