New Insights on Modelling Time Trends with Panel Data: Theory and Practice. This project aims to tackle important challenges in time trend modelling by taking advantage of panel data structures. This project expects to propose flexible models in time trend modelling to retrieve reliable inference. The expected outcomes include innovative econometric models and methods that have a wide range of applications, and are particularly suited for empirical problems within large and complex systems. This ....New Insights on Modelling Time Trends with Panel Data: Theory and Practice. This project aims to tackle important challenges in time trend modelling by taking advantage of panel data structures. This project expects to propose flexible models in time trend modelling to retrieve reliable inference. The expected outcomes include innovative econometric models and methods that have a wide range of applications, and are particularly suited for empirical problems within large and complex systems. This will provide significant benefits to all fields in which data displays any form of trending behaviour. The proposed model is used to evaluate the economic consequences of climate change and global housing market contagion, which provide strong evidence-based insights to the environmental and economic policies in Australia.Read moreRead less
Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.Read moreRead less
Econometric studies of the dynamics of loneliness and social isolation. This project aims to provide new insights into the socioeconomic dynamics of loneliness and social isolation using advanced econometric modelling techniques applied to longitudinal data from Australia and the UK. This project will apply advanced econometric modelling techniques to data from four nationally-representative longitudinal surveys to substantively help address these knowledge gaps, giving policy-makers new informa ....Econometric studies of the dynamics of loneliness and social isolation. This project aims to provide new insights into the socioeconomic dynamics of loneliness and social isolation using advanced econometric modelling techniques applied to longitudinal data from Australia and the UK. This project will apply advanced econometric modelling techniques to data from four nationally-representative longitudinal surveys to substantively help address these knowledge gaps, giving policy-makers new information about how to address these growing societal concerns. The expected outcomes will provide policy-makers with a better understanding of the socioeconomic triggers for loneliness and social isolation; quantify the costs of loneliness and social isolation on health and wellbeing; and identify policy interventions aimed at reducing loneliness and social isolation.Read moreRead less
Microeconometric Analysis of Socioeconomic Inequity in Mental Healthcare. The project aims to describe the extent of socioeconomic inequity in Australian mental healthcare use, identify the causal pathways that drive inequities, and conduct economic evaluations of programs aimed at increasing healthcare access. Microeconometric methods will be used to analyse large, longitudinal datasets that have not previously been used for this purpose. The project expects to provide a greater understanding o ....Microeconometric Analysis of Socioeconomic Inequity in Mental Healthcare. The project aims to describe the extent of socioeconomic inequity in Australian mental healthcare use, identify the causal pathways that drive inequities, and conduct economic evaluations of programs aimed at increasing healthcare access. Microeconometric methods will be used to analyse large, longitudinal datasets that have not previously been used for this purpose. The project expects to provide a greater understanding of the barriers that people face in accessing treatment and how to overcome them. Such understanding is currently missing from academic literatures and policy inquiries. Ultimately, the research should aid in the design of cost-effective policies that improve health outcomes and that reduce inequities in treatment access.Read moreRead less
Econometric methods for distributional policy effects. This project aims to develop new econometric methods that can measure distributional policy effects by accounting for heterogeneous policy impacts among observationally equivalent individuals. The project expects to develop quantile regression methods under a difference-in-differences framework that accommodates issues of censoring and sample selection. The outcomes of this project are expected to substantially broaden the scope of the stand ....Econometric methods for distributional policy effects. This project aims to develop new econometric methods that can measure distributional policy effects by accounting for heterogeneous policy impacts among observationally equivalent individuals. The project expects to develop quantile regression methods under a difference-in-differences framework that accommodates issues of censoring and sample selection. The outcomes of this project are expected to substantially broaden the scope of the standard mean difference-in-differences approach and have significant contributions to empirical studies in the future. The project intends to provide statistically valid inferential procedures and conduct simulation exercise and empirical studies relevant to policy evaluation for the benefit of Australia and other jurisdictions.Read moreRead less
Discrimination in Policing: Evidences from Natural Experiments. Ensuring that institutions are discrimination-free is key for the harmony of a society and the strength of a nation’s social contract. This research aims to investigate whether Australian law enforcement discriminates against certain groups and to explore the mechanisms explaining how it decides with whom to strictly enforce the law and
with whom to be lenient. This research program focuses on speeding fines as they offer unique nat ....Discrimination in Policing: Evidences from Natural Experiments. Ensuring that institutions are discrimination-free is key for the harmony of a society and the strength of a nation’s social contract. This research aims to investigate whether Australian law enforcement discriminates against certain groups and to explore the mechanisms explaining how it decides with whom to strictly enforce the law and
with whom to be lenient. This research program focuses on speeding fines as they offer unique natural experiments allowing rigorous exploration of these issues. The expected outcome is a better understanding of discrimination in Australia and the factors explaining it, which should contribute to better policy design and lead to more equitable treatment for all Australians.Read moreRead less
Economic analysis of child maltreatment and child protection. This project aims to investigate the economic causes and consequences of child maltreatment. It expects to generate new knowledge by applying microeconometric methods to large Australian administrative databases that track children’s health, education and welfare receipt over time. The expected outcomes of this project include an expanded knowledge base on how economic shocks affect maltreatment, the economic consequences of placing c ....Economic analysis of child maltreatment and child protection. This project aims to investigate the economic causes and consequences of child maltreatment. It expects to generate new knowledge by applying microeconometric methods to large Australian administrative databases that track children’s health, education and welfare receipt over time. The expected outcomes of this project include an expanded knowledge base on how economic shocks affect maltreatment, the economic consequences of placing children in out-of-home care, and the value of economic policies for reducing the intergenerational transmission of maltreatment. This should provide significant benefits, such as providing practical evidence to policy makers and service providers that help prevent child maltreatment and reduce its harms.Read moreRead less
Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolut ....Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolution algorithms, and cooperative co-evolutionary strategies. The outcome results will be demonstrated by practical evaluations over public datasets and comparisons to related works. The project is beneficial to the nation in both theory of artificial intelligence techniques and applications of real transport systems.Read moreRead less
Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given comp ....Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given computational budget. Expected outcomes of this project include efficient, effective and broadly applicable time series classification technologies. This should provide significant benefits to myriad sectors, transforming data science for time series problems and supporting innovation in industry, commerce and government.Read moreRead less
Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical cluste ....Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical clustering algorithms for dynamic networks – with performance guarantees of efficiency and clustering quality – and prototype software, guiding us to pick a good clustering. Expected benefits include better understanding of spread in evolving social networks, accelerating the software testing cycle, and improved topic detection.Read moreRead less