Optimising disease surveillance to support decision-making. COVID-19 has demonstrated the critical role of epidemic data and analytics in guiding government response to pandemic threats, reducing disease and saving lives. The demand for epidemic analytics for response to threats of national significance will only grow. The goals of this project are to 1) determine the combination(s) of surveillance methods that provide the most useful data for epidemic analysis and 2) translate these findings in ....Optimising disease surveillance to support decision-making. COVID-19 has demonstrated the critical role of epidemic data and analytics in guiding government response to pandemic threats, reducing disease and saving lives. The demand for epidemic analytics for response to threats of national significance will only grow. The goals of this project are to 1) determine the combination(s) of surveillance methods that provide the most useful data for epidemic analysis and 2) translate these findings into the blueprint for a next-generation infectious disease surveillance system for Australia. We will use a simulation-evaluation approach, coupling methods from infectious disease modelling with those from information theory optimal design. Outcomes will enable more tailored and effective pandemic response.Read moreRead less
Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate eco ....Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate economic and climate forecasts. The tools produced will provide Australia's scientists and policy-makers with a greater capacity to manage the risks associated with these challenges. A side-benefit of the research will be high-quality publications that enhance the nation's reputation in this cutting edge research.Read moreRead less
Modelling Dynamic Correlations in the Volatility of Patents and Technical Change. National/community benefits include a clearer understanding of the relation between patents and industrial innovation, measuring the effects of patents on technical change, economic growth and job creation, and analysing their fluctuations over time. The project analyses the variability in technological innovations, measures the impact of innovations on total output and key factors of production, namely labour, cap ....Modelling Dynamic Correlations in the Volatility of Patents and Technical Change. National/community benefits include a clearer understanding of the relation between patents and industrial innovation, measuring the effects of patents on technical change, economic growth and job creation, and analysing their fluctuations over time. The project analyses the variability in technological innovations, measures the impact of innovations on total output and key factors of production, namely labour, capital, energy and materials, and emphasizes the usefulness of the results. Expected outcomes include changing current ideas regarding output generation, understanding broad issues underlying patents and their variability, advancing multi-disciplinary knowledge, using information intelligently and promoting a culture of innovation.Read moreRead less
Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods an ....Preventing Exfiltration of Sensitive Data by Malicious Insiders or Malwares. Data exfiltration is a serious threat as highlighted in recent leakage of sensitive data that resulted in huge economic losses as well as unprecedented breaches of national security. The aim of this project is to develop a comprehensive and robust solution for detection and prevention of sensitive data exfiltration attempts by malware and unauthorised human users. Expected outcomes include scalable monitoring methods and efficient algorithms that will be able to prevent real-time exfiltration and identify previously undetected exfiltration of sensitive data. This should provide significant benefits to governments, defence networks as well as businesses and health sectors, as it will protect them from sophisticated cyber attacks.
Read moreRead less
Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for mis ....Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for misinformation is high, the overall quality of results will be enhanced. This research will be submitted to highly ranked health economics and econometrics journals to be made available to relevant policymakers intent on ensuring a healthy society.Read moreRead less
Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models domin ....Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models dominate. This project will generalise these techniques to allow for various forms of the threshold variable(s), including categorical and continuous, endogenous and exogenous, and those measured with error.Read moreRead less
Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research w ....Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research will facilitate the design of policies and regulations by regulatory authorities that need to evaluate new financial products, their associated risks and their impacts on the financial markets.Read moreRead less
Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to an ....Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to analyse a portfolio of returns and risk, and the determination of its applicability using numerical simulation techniques. The expected outcomes are an optimal practical method for analysing a portfolio of assets, a scientific monograph, and publications in leading international journals.Read moreRead less
Blind separation of mutually correlated sources. This project is aimed at developing novel techniques for blind separation of mutually correlated sources. The expected outcomes will significantly advance the theory of blind source separation and improve the performance of important practical systems, such as densely deployed sensor networks and wireless video surveillance systems.
Stochastic Index Numbers and Their Application in Accounting, Economics and Finance. Index numbers of prices, such as the Consumer Price Index and the All Ordinaries Index, are among the most important economic statistics for the whole economy. But despite their importance, currently constructed price indexes do not use all the information available in the underlying price data, namely the dispersion among the individual prices. This project will develop and apply a methodology for a new approa ....Stochastic Index Numbers and Their Application in Accounting, Economics and Finance. Index numbers of prices, such as the Consumer Price Index and the All Ordinaries Index, are among the most important economic statistics for the whole economy. But despite their importance, currently constructed price indexes do not use all the information available in the underlying price data, namely the dispersion among the individual prices. This project will develop and apply a methodology for a new approach to index numbers that incorporates this information and leads to tractable ways of estimating the whole distribution of the index value, rather than just one number. The practical usefulness of this mthodology will be demonstrated with applications in accounting (sustainable earnings), economics (real exchange rates) and finance (share prices).Read moreRead less