Enhancing Genomic Prediction for Changing Environments in Wheat. Adverse weather is the primary risk faced by the Australian agriculture industry. This Project aims to develop the next generation of agriculture tools to unlock natural potential in wheat and improve yield stability across seasons and regions. Drawing on crop physiology, genetics and integrated modelling, this Project expects to generate new knowledge and technologies to untangle genetic and environmental interactions that affect ....Enhancing Genomic Prediction for Changing Environments in Wheat. Adverse weather is the primary risk faced by the Australian agriculture industry. This Project aims to develop the next generation of agriculture tools to unlock natural potential in wheat and improve yield stability across seasons and regions. Drawing on crop physiology, genetics and integrated modelling, this Project expects to generate new knowledge and technologies to untangle genetic and environmental interactions that affect productivity, enhance predictive capability, and initiate advanced breeding strategies to develop new crop varieties with superior resilience against changing climates. This should provide significant benefits, such as profit stability for wheat growers, elevated global market position and improved food security.Read moreRead less
Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to devel ....Regularisation methods of inverse problems: theory and computation. This project aims to investigate regularisation methods for inverse problems which are ill-posed in the sense that their solutions depend discontinuously on the data. When only noisy data is available, regularisation methods define stable approximate solutions by replacing the original inverse problem with a family of well-posed neighbouring problems monitored by a so-called regularisation parameter. The project expects to develop purely data-driven rules to choose the regularisation parameter and show how they work in theory, and in practice. It will also develop convex framework, acceleration strategies as well as preconditioning and splitting ideas to design efficient regularisation solvers.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
High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful me ....High Dimensional Approximation, Learning, and Uncertainty. This project aims to develop next-generation computational methods for complex problems in science and engineering that have many uncertain parameters, using advanced high-dimensional strategies and deep learning to enhance computational speed. The significance of the project is that these methods will help address important applications that at present are not feasible or at the edge of feasibility. The expected outcomes are powerful methods that will be mathematically rigorous and suitable for a wide variety of applications. The benefits are that the project will boost Australia’s position as a leader in innovation, and contribute to future developments over a wide area, from aerospace engineering to personalised computational oncology.Read moreRead less
Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists ....Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists and policymakers and the project outputs should provide widespread and significant benefits by improving policy and boosting Australia’s comparative advantage.Read moreRead less
Macroeconomic and Financial Modelling in an Era of Extremes. This project aims to develop methods to allow workhorse models in economics and finance to better reflect tail events--low probability extreme events, such as the Global Financial Crisis and the COVID-19 pandemic. It intends to address fundamental technical challenges in the estimation of such models, develop a coherent framework for counterfactual analysis of these models and propose methods to apply these models in a big-data environ ....Macroeconomic and Financial Modelling in an Era of Extremes. This project aims to develop methods to allow workhorse models in economics and finance to better reflect tail events--low probability extreme events, such as the Global Financial Crisis and the COVID-19 pandemic. It intends to address fundamental technical challenges in the estimation of such models, develop a coherent framework for counterfactual analysis of these models and propose methods to apply these models in a big-data environment. Expected outcomes include new insights into the transmission of tail risks in the global economic and financial system. This should provide significant benefits, including guidance to Australian and international policymakers charged with maintaining stability in the face of extreme events.Read moreRead less
Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. T ....Loss-based Bayesian Prediction. This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. The new paradigm should produce significant benefits for all fields in which the consequences of predictive inaccuracy are severe. Problems that lead to substantial economic, financial or environmental loss if predictions are incorrect will be given particular attention.Read moreRead less
Closing the Gap Between Theory and Data in Macroeconometrics. This project aims to bring econometric models (the empirical vehicle for inference) and economic models (the theory) closer together. A new model is intended to be proposed that will address a significant issue with the interpretation of the outputs of the econometric models. As a first contribution, the project is expected to develop the model and an inferential framework for this model using probability theory on manifolds. In a sec ....Closing the Gap Between Theory and Data in Macroeconometrics. This project aims to bring econometric models (the empirical vehicle for inference) and economic models (the theory) closer together. A new model is intended to be proposed that will address a significant issue with the interpretation of the outputs of the econometric models. As a first contribution, the project is expected to develop the model and an inferential framework for this model using probability theory on manifolds. In a second contribution, it is expected to construct an algorithm to permit inference leading to outputs useful to policy analysts. The model is intended to be parsimonious, which facilitates the development of a time-varying version to allow the model to evolve with the economy and provide better policy guidance.Read moreRead less
Bayesian inference for psychological theories with intractable likelihood. This project pursues breakthroughs which allow important questions of basic and applied science to be addressed using mathematical theories from cognitive psychology. Advances are made through an interdisciplinary effort, combining recent developments in econometric and statistical methods and cognitive science. The outcomes will advance knowledge and open up new avenues for applied research in important aspects of psych .... Bayesian inference for psychological theories with intractable likelihood. This project pursues breakthroughs which allow important questions of basic and applied science to be addressed using mathematical theories from cognitive psychology. Advances are made through an interdisciplinary effort, combining recent developments in econometric and statistical methods and cognitive science. The outcomes will advance knowledge and open up new avenues for applied research in important aspects of psychology. This research will result in new methods available to the wider scientific community which open up new horizons for understanding basic cognition, and human behavior in many domains. Read moreRead less
Flexible models and methods for cognitive model-based decision-making. This project aims to apply mathematical decision models to important questions of basic and applied science. Advances will be pursued through an interdisciplinary effort, combining recent developments in econometric and statistical methods, cognitive science and computing. The expected outcomes will bring a proven and powerful approach to a new range of questions investigating psychological aspects of choices about health c ....Flexible models and methods for cognitive model-based decision-making. This project aims to apply mathematical decision models to important questions of basic and applied science. Advances will be pursued through an interdisciplinary effort, combining recent developments in econometric and statistical methods, cognitive science and computing. The expected outcomes will bring a proven and powerful approach to a new range of questions investigating psychological aspects of choices about health care and consumer purchases. This project will provide significant benefits to the wider scientific community to understand basic cognition, and human behaviour in many domains.Read moreRead less