ARC Financial Integrity Research Network. The integrity of the financial system is constantly under stress because of the development of ever more complex financial instruments, structures and strategies, and the associated research technologies that continues to accelerate worldwide. FIRN's vision is to harness the considerable strengths of Australia's internationally renowned finance, accounting and economics researchers into a research agenda to address issues concerning the integrity of the ....ARC Financial Integrity Research Network. The integrity of the financial system is constantly under stress because of the development of ever more complex financial instruments, structures and strategies, and the associated research technologies that continues to accelerate worldwide. FIRN's vision is to harness the considerable strengths of Australia's internationally renowned finance, accounting and economics researchers into a research agenda to address issues concerning the integrity of the financial system. It will enable Australian research in this area to match the scale and impact of similar research in other major international financial centres, and play an essential role in placing Australia among the world's leaders in financial markets related research.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150100795
Funder
Australian Research Council
Funding Amount
$365,000.00
Summary
New approaches to estimating nonlinear time-varying macroeconometric models. Quantitative models are essential for formulating good policies. In a changing world, the analysis should be based on models that allow the behaviour of the economy to change over time. Due to computational limitations, however, one is often restricted to linear models, even when nonlinear ones are more appropriate. This project aims to develop new methods for estimating time-varying nonlinear models. Two important appl ....New approaches to estimating nonlinear time-varying macroeconometric models. Quantitative models are essential for formulating good policies. In a changing world, the analysis should be based on models that allow the behaviour of the economy to change over time. Due to computational limitations, however, one is often restricted to linear models, even when nonlinear ones are more appropriate. This project aims to develop new methods for estimating time-varying nonlinear models. Two important applications are also considered: one investigates how the zero lower bound on interest rates affects the monetary policy transmission mechanism; and, the other examines how uncertainties about monetary and fiscal policy affect economic growth and inflation. This project will have strong practical significance for conducting macroeconomic policy.Read moreRead less
Measuring inflation expectations and inflation expectations uncertainty. This project aims to construct model-based measures of inflation expectations and inflation expectations uncertainty. Inflation expectations can determine economic outcomes. This project will develop non-linear time-varying models to combine information from noisy and possibly biased measures of inflation expectations from surveys and financial markets. These model-based measures are expected to be better calibrated and to ....Measuring inflation expectations and inflation expectations uncertainty. This project aims to construct model-based measures of inflation expectations and inflation expectations uncertainty. Inflation expectations can determine economic outcomes. This project will develop non-linear time-varying models to combine information from noisy and possibly biased measures of inflation expectations from surveys and financial markets. These model-based measures are expected to be better calibrated and to provide valuable information for policymakers for formulating macroeconomic policies. They can be used to better assess the credibility of monetary policy and shed light on the causes of low inflation rate in developed economies.Read moreRead less
Haemodynamic investigation of flow diverter stents for the treatment of intracranial aneurysms. This project will explore the engineering of a flow diverter, an endovascular device for the treatment of brain aneurysms. The project will determine the optimal design of new types of flow diverters, which in turn could improve the effectiveness of treatments, thus reducing the associated costs of cerebral haemorrhage and stroke.
Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces an ....Partially Observable MDPs, Monte Carlo Methods, and Sustainable Fisheries. Partially Observable Markov Decision Processes (POMDPs) provide a general mathematical framework for sequential decision making under uncertainty. However, solving POMDPs effectively under realistic assumptions remains a challenging problem. This project aims to develop new efficient Monte Carlo algorithms to significantly advance the application of POMDPs to real-world decision problems involving complex action spaces and system dynamics. Both theoretical and algorithmic approaches will be applied to sustainable fishery management --- an important problem for Australia and an ideal context for POMDPs. The project will advance research in artificial intelligence, dynamical systems, and fishery operations, and benefit the national economy.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
Geometric parameters in Learning Theory. We aim to investigate the behaviour of geometric parameters which appear naturally in Statistical Learning Theory. Those parameters are used to control the sample complexity, which is the size of a random sample needed to produce an accurate prediction. They are also of independent interest in the local theory of Banach spaces. We shall use geometric methods originating in the local theory of Banach spaces to investigate the parameters and the way they in ....Geometric parameters in Learning Theory. We aim to investigate the behaviour of geometric parameters which appear naturally in Statistical Learning Theory. Those parameters are used to control the sample complexity, which is the size of a random sample needed to produce an accurate prediction. They are also of independent interest in the local theory of Banach spaces. We shall use geometric methods originating in the local theory of Banach spaces to investigate the parameters and the way they influence sample complexity. All the problems we focus on are not only important from the Machine Learning point of view, but are intriguing in their theoretical implications.Read moreRead less
Special Research Initiatives - Grant ID: SR0354461
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
Australian Panel Data Users Network. Recent years have seen increased concern about how economic, social and technological changes interact with experiences occurring within families, workplaces and communities. Understanding these forces, however, requires panel data that track agents over time. Australia has only recently begun investing heavily in such data, raising concerns about our capacity to capitalize on this investment.
The aims of this network therefore include:
· enhancing the ca ....Australian Panel Data Users Network. Recent years have seen increased concern about how economic, social and technological changes interact with experiences occurring within families, workplaces and communities. Understanding these forces, however, requires panel data that track agents over time. Australia has only recently begun investing heavily in such data, raising concerns about our capacity to capitalize on this investment.
The aims of this network therefore include:
· enhancing the capacity of researchers to undertake panel data research;
· promoting cross-disciplinary research using panel databases;
· facilitating opportunities for contact between panel data researchers; and
· promoting the use of appropriate methods for analysing panel data.
It is expected that large benefits will flow to the community, especially through improved and better informed public debate and government policy-making.Read moreRead less
Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstra ....Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstrap) methods, which will provide a much-needed improvement over the existing (asymptotic) methods for making inference about the long-run. Our research will lead to more reliable models for long-term planning in business, industry and government.Read moreRead less
Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The ....Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The outcome of this project will be immediately useful for macroeconomic policy makers such as the Reserve Bank of Australia and the Treasury, and for industry bodies such as Tourism Australia. Read moreRead less