BA (Melbourne), A.Mus.A. (Piano, AMEB), BEc (Hons), MEc, PhD (Monash)
Econometric and statistical methods
My primary interest is in exploring statistical methods for complex dynamic models in economics and finance. The development, application and validation of Bayesian simulation-based methods is central to my research, with recent contributions made to the burgeoning field of approximate Bayesian computation. This includes a publication entitled ‘Asymptotic Properties of Approximate Bayesian Computation’ - the first paper to provide complete theoretical validation of this important practical tool for applied researchers. A historical review of Bayesian computation, ‘Computing Bayes: Bayesian Computation from 1763 to the 21st Century’ - written for empirical researchers keen on adopting the Bayesian paradigm - is a current arXiv pre-print.
My interest is not just in methods of inference and computation, but also prediction, including the impact of inferential technique, and modelling assumptions, on predictive accuracy. A recent publication, ‘Focused Bayesian Prediction’, explores the effect of making predictions with a model that does not accord with reality, and proposes a new paradigm for producing accurate predictions in this case. The principle we adopt here is an appealing one. In the social and economic sciences statistical data arise through human activities and interactions that we can never hope to adequately capture with a mathematical model. Hence, discard this hope and, instead, design predictions to perform well in the way that matters for the empirical problem at hand; i.e. focus only on what is important.
Most of my research is co-authored. I acknowledge the significant contributions of my wonderful collaborators, both in Australia and overseas, including PhD students and postdoctoral fellows. The research has been funded by multiple ARC Discovery grants, an ARC Future Fellowship and the Australian Centre of Excellence in Mathematics and Statistics.
I am 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.
Professor of Econometrics and Departmental PhD Director;
Associate Editor: Journal of Applied Econometrics; International Journal of Forecasting; Econometrics and Statistics.
Associate Investigator: Australian Research Council Centre of Excellence in Mathematical and Statistical Frontiers (ACEMS);
Australian Research Council Future Fellow: 2010-2013
1. Loaiza-Maya, R., Martin, G.M. and Frazier, D.T., 2020, "Focused Bayesian Prediction", In Press, Journal of Applied Econometrics.
2. Martin, G.M., Nadarajah, K. and Poskitt, D.S., 2019,"Issues in the Estimation of Mis-specified Models of Fractionally Integrated Processes", Journal of Econometrics.
3. Martin, G.M., McCabe, B.P.M., Frazier, D.T., Maneesoonthorn, W. and Robert, C.P., 2019, "Auxiliary Likelihood-based Approximate Bayesian Computation in State Space Models", Journal of Computational and Graphical Statistics, 28, 508-522.
4. Frazier, D.T., Martin, G.M., Robert, C.P. and Rousseau, J., 2018, "Asymptotic Properties of Approximate Bayesian Computation", Biometrika, 105, 593–607.
5. McCabe, B.P.M., G.M. Martin and Harris, D.G., 2011, "Efficient Probabilistic Forecasts for Counts". Journal of the Royal Statistical Society (Series B), 73, 253-272.