Gael Martin

Transforming the field of forecasting

How do you provide accurate predictions when the predictive model is wrong? It’s one of many things Professor Gael Martin from the Department of Econometrics and Business Statistics is working on.

Professor Martin is winner of the Monash Business School’s 2020 Dean's Award for Excellence in Research.

With an interest in exploring statistical methods for complex dynamic models in economics and finance; the development, application and validation of Bayesian methods of inference, computation and prediction are central to Professor Martin’s research.

Her most recent work has the potential to transform the field of forecasting by proposing a new paradigm for Bayesian prediction that delivers accurate predictions when the predictive model is wrong.

“My current work provides a new way of producing accurate predictions when the predictive model does not match reality,” says Professor Martin.

“This is most pertinent to the social and economic sciences, where statistical data arise through human activities and interactions that one cannot hope to adequately capture with a mathematical model.”

Most of Professor Martin’s research is co-authored and she acknowledges the significant contributions of collaborators, both in Australia and overseas, including PhD students and postdoctoral fellows.

Her research has been funded by multiple ARC Discovery grants, an ARC Future Fellowship and the Australian Centre of Excellence in Mathematics and Statistics (ACEMS). She was elected as a Fellow of the Academy of Social Sciences in Australia in 2020.

Professor Martin is currently Associate Editor for Journal of Applied Econometrics, International Journal of Forecasting (IJF) and Econometrics and Statistics, and was a guest editor for a special issue of IJF on Bayesian Forecasting in Economics. She has also recently presented an ACEMS podcast entitled ‘Bayes' Theorem: The Past & the Future.’