Trending time series models with non- and semi-parametric methods. The outcomes of this project will not only complement but also enhance the existing strengths and reputation of Australian researchers in the field of econometrics. The outcomes are also expected to help improve model building and forecasting from better models in climatology, economics, environmetrics and financial econometrics.
Modelling Hidden Processes which Drive Economic and Financial Systems. The ability to forecast complex economic systems is crucial to benefit from peak performance, and to prepare for and safeguard against downturn. This project aims to make significant discoveries concerning hidden processes which drive such systems, using rigorous, cutting-edge, flexible econometric methods. Resulting outcomes will be improved understanding of - and ability to forecast - important economic phenomena such as vo ....Modelling Hidden Processes which Drive Economic and Financial Systems. The ability to forecast complex economic systems is crucial to benefit from peak performance, and to prepare for and safeguard against downturn. This project aims to make significant discoveries concerning hidden processes which drive such systems, using rigorous, cutting-edge, flexible econometric methods. Resulting outcomes will be improved understanding of - and ability to forecast - important economic phenomena such as volatility in price series, extremal (risky) behaviour of financial systems, and turning points of the business cycle. Discoveries will be disseminated through published papers and presentations at a major international conference. Ongoing e-research links with France will also be established.Read moreRead less
Non- and Semi-Parametric Panel Data Econometrics: Theory and Applications. This project proposes to tackle several very important and difficult issues in modelling general climatological, economic and financial panel data that involve possible trending components. This project seeks to establish some general asymptotic theory for model estimation and specification technologies that are suited to such general nonlinear panel data that may be stochastically non-stationary and endogenous. The resea ....Non- and Semi-Parametric Panel Data Econometrics: Theory and Applications. This project proposes to tackle several very important and difficult issues in modelling general climatological, economic and financial panel data that involve possible trending components. This project seeks to establish some general asymptotic theory for model estimation and specification technologies that are suited to such general nonlinear panel data that may be stochastically non-stationary and endogenous. The research outcomes of this project are expected to be applicable in evaluating and improving empirical model building and forecasting from better models in climatology, economics and finance with possible endogeneity and nonlinearity and non-stationarity.Read moreRead less
Improved theory and practice in econometric modelling of nonlinear spatial time series. Modern Australia faces many challenges in economic and global climate changes, which require advanced statistical technologies in modeling and forecasting of econometric spatial time series data. This project will provide flexible models and methods that enable practitioners to more accurately measure and manage economic and climatic risks.
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
Pooling econometric models for prediction and decision making. The project develops methods for combining econometric models with the goal of improving prediction. It applies these methods to macroeconomic models used to improve monetary policy and to asset return models used to improve financial risk management.
Macroeconomic forecasting in a 'Big Data' world. This project will develop methods for forecasting important macroeconomic variables where a large set of predictors is available. As well as raw variables and composite indices such as principal components. This project will also include various lags and nonlinear functions of potential predictors. The project will adapt Bayesian statistical methods for selecting these predictors so that they can be applied to time series data, thus developing inn ....Macroeconomic forecasting in a 'Big Data' world. This project will develop methods for forecasting important macroeconomic variables where a large set of predictors is available. As well as raw variables and composite indices such as principal components. This project will also include various lags and nonlinear functions of potential predictors. The project will adapt Bayesian statistical methods for selecting these predictors so that they can be applied to time series data, thus developing innovative forecasting methods that can be used on a range of important problems involving 'Big Data'. The project will compare forecasts from different methods using simulated and empirical data from the US and Australia. For the latter an outcome will be an online handbook of available Australian economic data for public use.Read moreRead less
New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evo ....New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evolution over time. In so doing, they enable both accurate inferences regarding the dynamic structure of the data to be drawn and accurate forecasts of future event counts to be produced.Read moreRead less
New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the ....New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the policy making process.Read moreRead less