2020 Paul Bourke Award Lecture:
On the Use and History of Monte Carlo Methods

In this talk, I give a gentle (non-technical) introduction to the topic of modern (computer-based) Monte Carlo (MC) methods, their origins, and current uses. Monte Carlo methods constitute an extremely powerful set of tools to model and understand reality, as well as methods to understand the uncertainty associated with random events. A brief history of MC methods and their initial realm of application is covered. Several examples are given to illustrate the ability of MC methods to answer difficult questions. The talk ends by briefly discussing how MC methods have been used to tackle some of the most pressing problems of our time, such as in forecasting active cases of COVID-19.

The talk is kept largely free of the technical mathematics that underlay MC methods, so as to accommodate a broad audience.

David Frazier is a Senior Lecturer in Econometrics and Business Statistics at Monash University, working in the dual disciplines of econometrics and statistics. Frazier’s research interests are broad, but his primary focus has been on the area of simulation-based inference. Notably, he is one of only a handful of researchers to have made significant contributions to this field, which straddles the Bayesian and frequentist statistical paradigms.

The Paul Bourke Lectures are named in honour of the late Paul Francis Bourke (1938–1999), President of the Academy of the Social Sciences in Australia from 1993–1997. These lectures are presented each year by the recipients of the previous year’s Paul Bourke Awards for Early Career Research.

This lecture is jointly hosted by the Academy of the Social Sciences in Australia and the Monash Business School.