Forecasting Innovation

Economics and finance have become more technical and mathematical over time. A mathematical mindset has really helped me think about how to solve problems and think about real-world phenomenon. Mathematics is a way of thinking and a great language. It helps us not only formalise our ideas, but is a mechanism to ensure people are precise and clear about the assumptions they make about problems and the world. I use mathematics almost daily, as do many of my colleagues in my department. As well as modelling different phenomenon, we also use modern statistical techniques to take these models to the data to test our assumptions and theories. The mathematical sciences are very important for what we do here at the RBA, and my background in mathematics and statistics has provided me with a set of tools and skills to think about a wide range of issues.

Increasingly, there is greater demand for people with strong mathematical and quantitative skills. Increased access to data means skills to analyse the data, understand patterns in the data and then model the phenomenon are extremely important. Applications include modelling credit risk, modelling asset prices, and modelling the economy. A lot of modern statistical techniques are being applied to understanding the behaviour of households and firms as well, so these quantitative skills are an advantage.

I’ve been in forecasting long enough to know that whatever I say will be wrong, almost surely. I know that trends in policy circles are increasingly for mathematical and statistical techniques to be applied to a wider range of policy matters – from monetary policy, to financial stability, to the production and distribution of bank notes. Thinking about how to model banks’ exposures to each other through network theory, modelling tail risks in finance, thinking about how to make new technologies more secure (such as the distributed ledger and other technologies that might change the way the financial system works) and a whole lot of other policy issues will require people with a mathematical background to help us make progress on these matters. While policy makers are not always doing the innovating, they are often the regulators. They need people with the backgrounds to understand issues well enough before they arise and to design policies to address these issues.

 

Dr Adam Cagliarini: Reserve Bank of Australia, Deputy Head of Research.

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