Discovery Early Career Researcher Award - Grant ID: DE170100787
Funder
Australian Research Council
Funding Amount
$331,000.00
Summary
Misspecification in models of economic behaviour. This project aims to develop a robust method for estimation and inference with misspecified economic models. Economic models are designed to test hypotheses about economic behaviour and to estimate key parameters, but their validity and accuracy critically depend on the assumption that the model is correctly specified, which is often doubtful. This project will reparametrize the model to allow for misspecification. The project aims to help modell ....Misspecification in models of economic behaviour. This project aims to develop a robust method for estimation and inference with misspecified economic models. Economic models are designed to test hypotheses about economic behaviour and to estimate key parameters, but their validity and accuracy critically depend on the assumption that the model is correctly specified, which is often doubtful. This project will reparametrize the model to allow for misspecification. The project aims to help modellers produce results that better inform decision-makers and help them make more reliable decisions.Read moreRead less
Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bu ....Robust methods for heteroscedastic regression models for time series. What is the variability of the exchange rate of the Euro to the Australian dollar? Can the use of the electrocardiogram of a patient be improved as a diagnostic tool for heart disease? A well-known limitation of the existing statistical methods for answering these types of questions is that a small proportion of extreme observations have the potential to lead to results that are more in agreement with the outliers than with bulk of the data. As a consequence, the statistical analyses may lead to wrong conclusions. This project aims to develop new methodologies to solve this problem for a large class of studies. Applications to stock market risk, exchange rate, and diagnosis of heart diseases will illustrate the new methods.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.
Discovery Early Career Researcher Award - Grant ID: DE200101070
Funder
Australian Research Council
Funding Amount
$376,496.00
Summary
Consequences of Model Misspecification in Approximate Bayesian Computation. In almost any empirical application, the model the analyst is working with constitutes a misspecified description of the true process that has generated the data. While the method of Approximate Bayesian computation (ABC) is now a staple in the toolkit of the applied modeller, the impact of misspecification in ABC is unknown. This project aims to undertake a rigorous study into the behaviour of ABC under model misspecifi ....Consequences of Model Misspecification in Approximate Bayesian Computation. In almost any empirical application, the model the analyst is working with constitutes a misspecified description of the true process that has generated the data. While the method of Approximate Bayesian computation (ABC) is now a staple in the toolkit of the applied modeller, the impact of misspecification in ABC is unknown. This project aims to undertake a rigorous study into the behaviour of ABC under model misspecification. Expected outcomes include new theoretical results for ABC under misspecification and new methods capable of detecting/mitigating model misspecification. This project will provide significant benefits in all spheres where reliable, robust statistical inference methods are required in order to make reliable decisions.
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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.
Massively parallel algorithms for Bayesian inference and decision making. This project uses the graphical processing units of desktop computers, originally developed for games and video, to enhance substantially the quantitative tools used on a daily basis by economists. It will develop procedures and software to enhance the reliability of economic predictions and policy.
Predicting the value and use of urban land. This project aims to develop a comprehensive, robust and user-friendly set of modelling tools to predict land values more accurately. Accurate predictions of land values reduce state government revenue risks and improve resource management. The expected outcome of this project is the development of modelling tools which, can be used to study land use allocation, infrastructure delivery and government taxation revenue. This should provide significant be ....Predicting the value and use of urban land. This project aims to develop a comprehensive, robust and user-friendly set of modelling tools to predict land values more accurately. Accurate predictions of land values reduce state government revenue risks and improve resource management. The expected outcome of this project is the development of modelling tools which, can be used to study land use allocation, infrastructure delivery and government taxation revenue. This should provide significant benefits such as the development of new econometric theory, advanced computational methods and evidence-based guidelines for policymakers.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100713
Funder
Australian Research Council
Funding Amount
$340,000.00
Summary
Nonparametric estimation and forecasting of yield curve dynamics. This project aims to develop a suite of nonparametric estimation and forecasting techniques for yield curves, which describe how interest rates vary with different maturities. Its significance for monetary policy and fixed-income investment is interesting to policy makers and financial practitioners. Time-varying features are needed in the specification of the yield curve, given the constantly changing financial environment in whi ....Nonparametric estimation and forecasting of yield curve dynamics. This project aims to develop a suite of nonparametric estimation and forecasting techniques for yield curves, which describe how interest rates vary with different maturities. Its significance for monetary policy and fixed-income investment is interesting to policy makers and financial practitioners. Time-varying features are needed in the specification of the yield curve, given the constantly changing financial environment in which bond markets operate. Expected outcomes include new statistical methods and forecasting procedures applicable to empirical problems in economics and finance.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
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