Innovative approach to a fair tax system for Multinationals and Governments. Multinationals (MNCs) tax avoidance has become a national blight and a global problem impacting tax fairness, transparency and economic efficiency. This project aims to find the optimal solution for the tax avoidance problem for both MNCs and governments via effective cost-benefit analysis through the design of a cutting-edge interdisciplinary machine-learning technique. Expected outcomes will include profound breakthro ....Innovative approach to a fair tax system for Multinationals and Governments. Multinationals (MNCs) tax avoidance has become a national blight and a global problem impacting tax fairness, transparency and economic efficiency. This project aims to find the optimal solution for the tax avoidance problem for both MNCs and governments via effective cost-benefit analysis through the design of a cutting-edge interdisciplinary machine-learning technique. Expected outcomes will include profound breakthroughs for enhancing economic growth via tax policy reform in Australia but also globally through cross-country tax avoidance comparison. The benefits will be instrumental in reforming fiscal and investment policies that are highly critical for improving economic welfare and capital inflows in Australia.Read moreRead less
Risk management with real-time financial and business conditions indicators. This project will develop new methods that combine financial and macroeconomic information that arrives at different intervals to better understand the implications of this information for risk management and policy decision-making. This will support better risk management strategies especially when economic conditions are very volatile.
Diversification failures and improved measures of uncertainty. The project aims to develop new statistical tools, applicable when the conventional paradigm that diversification reduces risk fails and when textbook approaches to risk quantification severely under-report risk. The new tools enhance our capacity to build and manage natural, social and human-made systems in uncertain environments. Our effective response to many threats including financial crises and natural events, depends on this c ....Diversification failures and improved measures of uncertainty. The project aims to develop new statistical tools, applicable when the conventional paradigm that diversification reduces risk fails and when textbook approaches to risk quantification severely under-report risk. The new tools enhance our capacity to build and manage natural, social and human-made systems in uncertain environments. Our effective response to many threats including financial crises and natural events, depends on this capacity. Thus, the expected benefits in the form of more reliable and robust risk analytics will accrue when they are most needed.Read moreRead less
Can green investors drive the transition to a low emissions economy? The project aims to develop a game-theoretical approach to model the impact of climate change on financial markets by studying the interactions between the government, companies and investors. Expected outcomes include novel solution concepts for stochastic games with heterogeneous beliefs, asymmetric information, and model uncertainty, as well as optimal investment and production strategies under climate driven economic transi ....Can green investors drive the transition to a low emissions economy? The project aims to develop a game-theoretical approach to model the impact of climate change on financial markets by studying the interactions between the government, companies and investors. Expected outcomes include novel solution concepts for stochastic games with heterogeneous beliefs, asymmetric information, and model uncertainty, as well as optimal investment and production strategies under climate driven economic transitions. Results will be used to validate and improve the recently launched Australian based climate transition index. The project should yield significant benefits for the financial industry and investors by providing novel insights into financial risks during the transition to a low emissions economy.Read moreRead less
Deep learning based time series modeling and financial forecasting. This project pursues breakthroughs in time series modelling and develops novel statistical models and inference techniques, with a focus on modelling of financial time series data. The advances will be achieved through interdisciplinary research, combining recent advances in machine learning, Bayesian computation, financial econometrics and the increasing availability of Big Data. The outcomes will provide a new range of proven ....Deep learning based time series modeling and financial forecasting. This project pursues breakthroughs in time series modelling and develops novel statistical models and inference techniques, with a focus on modelling of financial time series data. The advances will be achieved through interdisciplinary research, combining recent advances in machine learning, Bayesian computation, financial econometrics and the increasing availability of Big Data. The outcomes will provide a new range of proven and powerful approaches for analysing time series and understanding time effects. The methodologies developed will lead to a greater accuracy in financial forecasting and risk management, and open up new horizons for the wider scientific community to analyse time series data.Read moreRead less
Frontiers of Risk Modelling: Dependence and Extremes of Levy Processes. This project plans to continue an ongoing theoretical study into continuous-time stochastic processes, concentrating on developing tools for the further analysis and understanding of extremal and multivariate phenomena with applications to portfolio analysis, value-at risk calculations and complex financial instruments, with particular emphasis on practical applications of the methodologies in the insurance and finance indus ....Frontiers of Risk Modelling: Dependence and Extremes of Levy Processes. This project plans to continue an ongoing theoretical study into continuous-time stochastic processes, concentrating on developing tools for the further analysis and understanding of extremal and multivariate phenomena with applications to portfolio analysis, value-at risk calculations and complex financial instruments, with particular emphasis on practical applications of the methodologies in the insurance and finance industries. Expected outcomes would be of direct interest to these industries as well as having significant mathematical interest.Read moreRead less
The econometrics of gravity models of trade: a re-assessment. This research will lead a much greater understanding of the empirical determinants of trade flows between countries. This project will apply cutting-edge data econometric techniques to the popular Gravity model of international trade flows. These more appropriate techniques will shed more light on some previous puzzling findings, such that regional trade agreements had little, or no, affect on trade.
Discovery Early Career Researcher Award - Grant ID: DE170100644
Funder
Australian Research Council
Funding Amount
$371,000.00
Summary
Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limi ....Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limitations for many econometric models, and apply them to important models in health economics and international trade. Such improvements are expected to reduce risk in public decision-making, resulting in better and more effective policies.Read moreRead less
International coalitions for climate change mitigation: the role of carbon market linkages and trade restrictions. This project uses cooperative game theory, implementation theory and agent-based modelling to investigate how coalitions to reduce greenhouse gas emissions could be formed and maintained among countries. Applications include the role of carbon market linkage and trade policy, in countries of the Asia-Pacific region.
New methods for modelling and forecasting risk. The project will develop and assess risk measures and risk forecasting. It will assess why customary measures failed in the financial crisis and develop new and better techniques. The project is unique in terms of the scope and range of methods to be applied and tested. It will be of value to investors, institutions and regulators alike.