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Research Topic : analysis
Field of Research : Econometric and Statistical Methods
Australian State/Territory : VIC
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  • Researchers (13)
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  • Funded Activity

    Discovery Projects - Grant ID: DP150101012

    Funder
    Australian Research Council
    Funding Amount
    $296,700.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP170104421

    Funder
    Australian Research Council
    Funding Amount
    $337,000.00
    Summary
    Econometric model building and estimation. This project aims to tackle issues in econometric model building and estimation under cross sectional dependence, heterogeneity and nonlinearity. This project will seek to establish flexible econometric models associated with estimation methods and user-friendly computational techniques to try to solve real world problems. The research outcomes are expected to be useful to empirical researchers in evaluating and improving model building and forecasting .... Econometric model building and estimation. This project aims to tackle issues in econometric model building and estimation under cross sectional dependence, heterogeneity and nonlinearity. This project will seek to establish flexible econometric models associated with estimation methods and user-friendly computational techniques to try to solve real world problems. The research outcomes are expected to be useful to empirical researchers in evaluating and improving model building and forecasting from better models in climatology, demography, economics, environment, finance, machine learning and neural networks.
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    Funded Activity

    Discovery Projects - Grant ID: DP210100652

    Funder
    Australian Research Council
    Funding Amount
    $326,363.00
    Summary
    Estimating and Testing Heterogeneous Structural Changes. This project aims to develop new methods of extracting non-central, irregular patterns from data, and to detect such patterns in climate data and city-level racial composition data. The project expects to have methodological and empirical contributions, propose innovative data-driven approaches, and extract important features of climate and racial-composition data. The anticipated outcomes of this project are new methods of measuring the r .... Estimating and Testing Heterogeneous Structural Changes. This project aims to develop new methods of extracting non-central, irregular patterns from data, and to detect such patterns in climate data and city-level racial composition data. The project expects to have methodological and empirical contributions, propose innovative data-driven approaches, and extract important features of climate and racial-composition data. The anticipated outcomes of this project are new methods of measuring the relationship between human activities and extreme weather, and for quantifying dynamic racial composition. These empirical results should demonstrate the substantial benefits of the new methods by presenting important empirical evidence for designing policies against extreme weather and racial segregation.
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    Funded Activity

    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP130104229

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    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.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190101152

    Funder
    Australian Research Council
    Funding Amount
    $339,000.00
    Summary
    Econometric methods for distributional policy effects. This project aims to develop new econometric methods that can measure distributional policy effects by accounting for heterogeneous policy impacts among observationally equivalent individuals. The project expects to develop quantile regression methods under a difference-in-differences framework that accommodates issues of censoring and sample selection. The outcomes of this project are expected to substantially broaden the scope of the stand .... Econometric methods for distributional policy effects. This project aims to develop new econometric methods that can measure distributional policy effects by accounting for heterogeneous policy impacts among observationally equivalent individuals. The project expects to develop quantile regression methods under a difference-in-differences framework that accommodates issues of censoring and sample selection. The outcomes of this project are expected to substantially broaden the scope of the standard mean difference-in-differences approach and have significant contributions to empirical studies in the future. The project intends to provide statistically valid inferential procedures and conduct simulation exercise and empirical studies relevant to policy evaluation for the benefit of Australia and other jurisdictions.
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    Funded Activity

    Discovery Projects - Grant ID: DP110102721

    Funder
    Australian Research Council
    Funding Amount
    $470,574.00
    Summary
    An econometric analysis of the impact of education on health in developing countries. This project will provide empirical knowledge on whether education affects health over the life course in developing countries. This research will aid the design of more cost effective strategies aiming to reduce poverty and promote economic development, which will ultimately lead to a more prosperous and safe region and world.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101414

    Funder
    Australian Research Council
    Funding Amount
    $393,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP140103220

    Funder
    Australian Research Council
    Funding Amount
    $335,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP170100729

    Funder
    Australian Research Council
    Funding Amount
    $391,000.00
    Summary
    The validation of approximate Bayesian computation. This project aims to establish the theoretical validity of approximate Bayesian computation (ABC) and to develop diagnostic methods for assessing its reliability in empirical applications. Given the increased complexity of modern statistical models, new ways of conducting statistical inference are needed. Approximate Bayesian computation is a new statistical tool. This project expects its findings will be useful in all fields where complex phen .... The validation of approximate Bayesian computation. This project aims to establish the theoretical validity of approximate Bayesian computation (ABC) and to develop diagnostic methods for assessing its reliability in empirical applications. Given the increased complexity of modern statistical models, new ways of conducting statistical inference are needed. Approximate Bayesian computation is a new statistical tool. This project expects its findings will be useful in all fields where complex phenomena feature and approximate methods are the only feasible way of understanding those phenomena.
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