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.
High-frequency Estimation of Term Structure Models at the Zero Lower Bound. This project aims to quantify monetary policy shocks as shifts of the entire term structure of interest rates, when the central bank’s policy rate is constrained at the near-zero level. The proposed method will use a high-dimensional panel of high frequency government bond data. The term structure and resultant policy shocks estimated at intra-day frequencies for major economies including Australia, will be made publicly ....High-frequency Estimation of Term Structure Models at the Zero Lower Bound. This project aims to quantify monetary policy shocks as shifts of the entire term structure of interest rates, when the central bank’s policy rate is constrained at the near-zero level. The proposed method will use a high-dimensional panel of high frequency government bond data. The term structure and resultant policy shocks estimated at intra-day frequencies for major economies including Australia, will be made publicly available. This project expects to deepen our understanding of how monetary policy decisions affect the macroeconomy in a near-zero interest-rate environment. This should provide significant benefits to policymakers for implementing and monitoring monetary policy in achieving desired economic outcomes.Read moreRead less
Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect t ....Prior sensitivity analysis for Bayesian Markov chain Monte Carlo output. This project aims to develop the first set of techniques to implement an automated output sensitivity analysis for Markov Chain Monte Carlo (MCMC) estimation methods. Computationally intense Bayesian MCMC provide a powerful alternative to classical methods for the estimation of economic models. An obstacle to their wider application is that researchers need to specify prior beliefs about model parameters that will affect the results. The expected outcomes will enable researchers to undertake a routine assessment of the sensitivity of the results to prior inputs.Read moreRead less
Estimation of the continuous piecewise linear model and macroeconomic applications. Relationships between economic variables are often characterised by non-linearities. This project develops a method to analyse a type of non-linearity that is frequently encountered in economics and uses this method to study four specific applications concerning the dynamics of inflation, growth, and the exchange rate.
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
Discovery Early Career Researcher Award - Grant ID: DE150100795
Funder
Australian Research Council
Funding Amount
$365,000.00
Summary
New approaches to estimating nonlinear time-varying macroeconometric models. Quantitative models are essential for formulating good policies. In a changing world, the analysis should be based on models that allow the behaviour of the economy to change over time. Due to computational limitations, however, one is often restricted to linear models, even when nonlinear ones are more appropriate. This project aims to develop new methods for estimating time-varying nonlinear models. Two important appl ....New approaches to estimating nonlinear time-varying macroeconometric models. Quantitative models are essential for formulating good policies. In a changing world, the analysis should be based on models that allow the behaviour of the economy to change over time. Due to computational limitations, however, one is often restricted to linear models, even when nonlinear ones are more appropriate. This project aims to develop new methods for estimating time-varying nonlinear models. Two important applications are also considered: one investigates how the zero lower bound on interest rates affects the monetary policy transmission mechanism; and, the other examines how uncertainties about monetary and fiscal policy affect economic growth and inflation. This project will have strong practical significance for conducting macroeconomic policy.Read moreRead less
Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models domin ....Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models dominate. This project will generalise these techniques to allow for various forms of the threshold variable(s), including categorical and continuous, endogenous and exogenous, and those measured with error.Read moreRead less
Measuring inflation expectations and inflation expectations uncertainty. This project aims to construct model-based measures of inflation expectations and inflation expectations uncertainty. Inflation expectations can determine economic outcomes. This project will develop non-linear time-varying models to combine information from noisy and possibly biased measures of inflation expectations from surveys and financial markets. These model-based measures are expected to be better calibrated and to ....Measuring inflation expectations and inflation expectations uncertainty. This project aims to construct model-based measures of inflation expectations and inflation expectations uncertainty. Inflation expectations can determine economic outcomes. This project will develop non-linear time-varying models to combine information from noisy and possibly biased measures of inflation expectations from surveys and financial markets. These model-based measures are expected to be better calibrated and to provide valuable information for policymakers for formulating macroeconomic policies. They can be used to better assess the credibility of monetary policy and shed light on the causes of low inflation rate in developed economies.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