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.
Choice foundations: Diagnostic tools for individual-level model development. This project aims to improve policy making in areas such as transport, environment and health, by better representation of how people make decisions. An interdisciplinary team of economists and psychologists will build on new mathematical and statistical tools to test for adherence to choice axioms that underlie observed choice behaviour. The project will produce a set of computerized statistical tools to implement the ....Choice foundations: Diagnostic tools for individual-level model development. This project aims to improve policy making in areas such as transport, environment and health, by better representation of how people make decisions. An interdisciplinary team of economists and psychologists will build on new mathematical and statistical tools to test for adherence to choice axioms that underlie observed choice behaviour. The project will produce a set of computerized statistical tools to implement the testing of choice axioms using Bayesian methods with the capacity to improve a wide array of applied economics work at the national and international levels.Read moreRead less
Identification Power and Instrument Strength in Discrete Outcome Models. This project aims to develop new econometric and statistical techniques to quantify causal effects in treatment models with discrete outcomes. Expected outcomes include a much-needed weak instrument test, a measure for identification strength in partial identification setting, and an instrument-covariate selection procedure for high dimensional discrete models based identification power. The benefits include advanced knowle ....Identification Power and Instrument Strength in Discrete Outcome Models. This project aims to develop new econometric and statistical techniques to quantify causal effects in treatment models with discrete outcomes. Expected outcomes include a much-needed weak instrument test, a measure for identification strength in partial identification setting, and an instrument-covariate selection procedure for high dimensional discrete models based identification power. The benefits include advanced knowledge in econometrics and statistics, and enhanced tools for program evaluation and policy assessment in empirical causal analysis using observational data. The project falls into the category of smarter information use and is relevant to any national priority areas where policy interventions require assessment.Read moreRead less
Challenging econometric issues in nonlinear high-dimensional spatio-temporal prediction: theory and applications. This project will develop cutting-edge methodologies to break through challenging issues in nonlinear spatio-temporal econometric prediction. It will yield a new generation of prediction tools that enpower practitioners in Australia to produce more accurate forecasts, with more informed countermeasures to viarious economic and enviromental risks.
Selection of mixed strength moment restrictions and optimal inference . This project aims to develop consistent model selection criteria even if the target model only provides a weak signal about the parameter of interest. This project expects to generate new knowledge on model selection using new and innovative techniques. Expected outcomes include the quantification of the maximum information on parameter from weak-signal models; new entropy-based model selection criteria; and a robust investi ....Selection of mixed strength moment restrictions and optimal inference . This project aims to develop consistent model selection criteria even if the target model only provides a weak signal about the parameter of interest. This project expects to generate new knowledge on model selection using new and innovative techniques. Expected outcomes include the quantification of the maximum information on parameter from weak-signal models; new entropy-based model selection criteria; and a robust investigation of the still debated hypothesis in environmental economics that with open and liberalized trade, developing countries would become pollution havens for dirty industries of advanced countries. Success in this undertaking will dramatically enlarge the pool of applied work involving economic models with weak signals.Read moreRead less