Forecasting when model stability is uncertain. Forecasts of macroeconomic and financial variables play a crucial role in forward planning undertaken by government and financial institutions, but the predictability of these series is often context and time specific, making standard forecasting techniques unreliable. This project aims to develop new modelling and forecasting techniques that can adapt to structural changes in the model soon after they occur. It aims to derive relevant econometric t ....Forecasting when model stability is uncertain. Forecasts of macroeconomic and financial variables play a crucial role in forward planning undertaken by government and financial institutions, but the predictability of these series is often context and time specific, making standard forecasting techniques unreliable. This project aims to develop new modelling and forecasting techniques that can adapt to structural changes in the model soon after they occur. It aims to derive relevant econometric theory, use simulations to study the properties of the proposed techniques, as well as apply these new techniques to observed data.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
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 methods for modelling complex trends in climate and energy time series. The project aims to contribute to Australian and international efforts on emission control by advancing the methods for quantifying the relationships between energy production, emission and climate, and assessing the real and financial risks associated with changing the ways in which economies produce and use energy. The project is interdisciplinary and expects to develop new knowledge in the areas of energy and climate ....New methods for modelling complex trends in climate and energy time series. The project aims to contribute to Australian and international efforts on emission control by advancing the methods for quantifying the relationships between energy production, emission and climate, and assessing the real and financial risks associated with changing the ways in which economies produce and use energy. The project is interdisciplinary and expects to develop new knowledge in the areas of energy and climate econometrics. The anticipated outcomes of this project are new methods for modelling variables with complex trends, and an innovative data-driven approach for learning from policy experiences of other countries. This should provide significant benefits by enabling evidence-based policy making in the era of climate change. Read moreRead less
Fractional Integration, Power Laws and Econometric Models: Some Methodological and Theoretical Developments. The fundamental objectives of this project are to: (i) Extend
current econometric practice and consider the use of power laws as
a basis for the construction of a more flexible and realistic
class of models for the analysis of economic and financial time
series. (ii) To develop inferential techniques appropriate for the
modelling of dynamic econometric systems that incorporate
struc ....Fractional Integration, Power Laws and Econometric Models: Some Methodological and Theoretical Developments. The fundamental objectives of this project are to: (i) Extend
current econometric practice and consider the use of power laws as
a basis for the construction of a more flexible and realistic
class of models for the analysis of economic and financial time
series. (ii) To develop inferential techniques appropriate for the
modelling of dynamic econometric systems that incorporate
structure characterized by power laws. This will be achieved by
building upon the class of fractionally integrated processes. New
econometric models and methodologies for the analysis of
non-stationarity series will be developed, along with the
associated theoretical results.Read moreRead less
Semi-parametric bootstrap-based inference in long-memory models. Given the long lead times involved in implementing economic decisions, a clear understanding of the long-term dynamics driving key variables is crucial. This project will produce significant advances in the analysis of long-range dependence, with decisions underpinned by more accurate and robust statistical information as a consequence.
Approximate Bayesian computation in state space models. Economic and financial data frequently exhibit dynamic patterns, driven by unobserved processes that relate to the behaviour of economic agents, or to institutional and technological change. To gain insight into such 'latent' processes is of paramount importance in terms of both understanding the economy and producing accurate, readily up-dated, forecasts of its future performance. Using a Bayesian approach, new simulation-based statistical ....Approximate Bayesian computation in state space models. Economic and financial data frequently exhibit dynamic patterns, driven by unobserved processes that relate to the behaviour of economic agents, or to institutional and technological change. To gain insight into such 'latent' processes is of paramount importance in terms of both understanding the economy and producing accurate, readily up-dated, forecasts of its future performance. Using a Bayesian approach, new simulation-based statistical methods for analysing latent variable models are proposed. Emphasis is given to the development of relatively simple techniques that are applicable to a wide range of empirically relevant models, with a view to improving the access of non-specialists to this powerful form of statistical analysis.Read moreRead less
Helping Central Banks Measure Unobserved Variables Using Real-time Forecasts. The project addresses structural measurement problems confronted routinely by central bankers. The techniques developed, and the estimates provided, will aid directly the Partner Organisations (the Reserve Bank of Australia, the Reserve Bank of New Zealand and Norges Bank) and other central banks in formulating monetary policy. The analysis will allow interest rates in Australia and elsewhere to be set with greater pre ....Helping Central Banks Measure Unobserved Variables Using Real-time Forecasts. The project addresses structural measurement problems confronted routinely by central bankers. The techniques developed, and the estimates provided, will aid directly the Partner Organisations (the Reserve Bank of Australia, the Reserve Bank of New Zealand and Norges Bank) and other central banks in formulating monetary policy. The analysis will allow interest rates in Australia and elsewhere to be set with greater precision. The techniques developed in this project will facilitate the understanding and communication of monetary policy within the central banks concerned, and enhance communication of monetary policy strategy to the public.Read moreRead less