Bayesian Inference for Flexible Parametric Multivariate Econometric Modelling

Grant number: DP0985505 | Funding period: 2009 - 2011

Completed

Abstract

The anticipated outcomes include the development of enhanced multivariate econometric models and innovative computationally intensive methods for their estimation. These models are used in numerous and diverse applications which are data-intensive and where more complete models will greatly enhance data-based decision-making. Results include improved information use in the wholesale electricity markets, in financial market investment decision-making and for the assessment of the impact of internet advertising.

Related publications (4)

Estimation of copula models with discrete margins via Bayesian data augmentation

MS Smith, MA Khaled

2012-07-02

Estimation of copula models with discrete margins can be difficult beyond the bivariate case. We show how this can be achieved by ..

Bicycle commuting in Melbourne during the 2000s energy crisis: A semiparametric analysis of intraday volumes

MS Smith, G Kauermann

2011-01-01

Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are po..

Modeling longitudinal data using a pair-copula decomposition of serial dependence

M Smith, A Min, C Almeida, C Czado

2010-12-01

Copulas have proven to be very successful tools for the flexible modeling of cross-sectional dependence. In this paper we express ..

Bayesian skew selection for multivariate models

A Panagiotelis, M Smith

2010-07-01

We develop a Bayesian approach for the selection of skew in multivariate skew t distributions constructed through hidden condition..

University of Melbourne Researchers

Michael Smith