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: 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
Discovery Early Career Researcher Award - Grant ID: DE120101130
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
New models and estimation methods in nonlinear panel data econometrics. This project will develop new econometric models and methods for capturing dynamic and complex relationships within economic and social systems. The outcomes of this project are expected to improve policy making process concerning climate change, economy and financial markets, through providing accurate estimates of relationships of interest.
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.
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
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.
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
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
Discovery Early Career Researcher Award - Grant ID: DE120100748
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Robust inference for behavioural models in economics and finance. The project will develop novel methodology to estimate behavioural models in economics and finance, which may give better insights on economic development. Knowledge gained from this project will be useful for Australian industries, banks, investment funds and the government for the effective formulation of their business strategies and policies.
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.