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
Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists ....Large dynamic time-varying models for structural macroeconomic inference. This project aims to broaden the range of macroeconomic models that have an integrated capacity for both greater realism and efficiency in analysis. This approach will be applied to two contexts at the forefront of current macroeconomic research, the effects of noisy productivity signals on business cycles and the effects of fiscal policy shocks. Flexible macro-econometric models underpin accurate inference by economists and policymakers and the project outputs should provide widespread and significant benefits by improving policy and boosting Australia’s comparative advantage.Read moreRead less
Measuring the effect of monetary policy on the economy. This project aims to measure the effect of monetary policy on the economy, notably consumption and investment, in Australia and the US. This research intends to fill a gap in the empirical macroeconomic literature, which focuses on the supply side of the economy. This project will account for unstable economic conditions caused by institutional or behavioural changes, such as financial development / liberalisation and preference shocks, in ....Measuring the effect of monetary policy on the economy. This project aims to measure the effect of monetary policy on the economy, notably consumption and investment, in Australia and the US. This research intends to fill a gap in the empirical macroeconomic literature, which focuses on the supply side of the economy. This project will account for unstable economic conditions caused by institutional or behavioural changes, such as financial development / liberalisation and preference shocks, in the analysis; and develop econometric methods tailored for application to models with time varying parameters. This project expects to contribute to understanding the economy’s recent unresponsiveness to monetary policy.Read moreRead less
Macroeconomic and Financial Modelling in an Era of Extremes. This project aims to develop methods to allow workhorse models in economics and finance to better reflect tail events--low probability extreme events, such as the Global Financial Crisis and the COVID-19 pandemic. It intends to address fundamental technical challenges in the estimation of such models, develop a coherent framework for counterfactual analysis of these models and propose methods to apply these models in a big-data environ ....Macroeconomic and Financial Modelling in an Era of Extremes. This project aims to develop methods to allow workhorse models in economics and finance to better reflect tail events--low probability extreme events, such as the Global Financial Crisis and the COVID-19 pandemic. It intends to address fundamental technical challenges in the estimation of such models, develop a coherent framework for counterfactual analysis of these models and propose methods to apply these models in a big-data environment. Expected outcomes include new insights into the transmission of tail risks in the global economic and financial system. This should provide significant benefits, including guidance to Australian and international policymakers charged with maintaining stability in the face of extreme events.Read moreRead less
Reliability of purchasing power parities from the World Bank. This project aims to provide an econometric framework to estimate purchasing power parities (PPPs) and a method to compute standard errors associated with the World Bank’s International Comparison Programme (ICP)’s PPPs. The ICP regularly compiles and publishes estimates of PPPs of currencies and real incomes. These results are used for study of global inequality and poverty; macroeconomic analysis; the Human Development Index; and cr ....Reliability of purchasing power parities from the World Bank. This project aims to provide an econometric framework to estimate purchasing power parities (PPPs) and a method to compute standard errors associated with the World Bank’s International Comparison Programme (ICP)’s PPPs. The ICP regularly compiles and publishes estimates of PPPs of currencies and real incomes. These results are used for study of global inequality and poverty; macroeconomic analysis; the Human Development Index; and cross-country productivity comparisons. However, no estimates of ICP PPPs’ reliability are available. Results from this project are likely to improve the quality of widely used data sets including the Penn World Tables and the University of Queensland International Comparison Database relevant to banking.Read moreRead less
Statistical Analysis of State-Dependent Government Spending Multipliers. This project aims to provide a new statistical analysis of the government spending multiplier by acknowledging that government spending is the sum of sectoral spending which has heterogeneous effects on the economy. An added complication is that the multiplier can also be state-dependent, meaning that its magnitude can differ across recessions and expansions. Expected outcomes of this project include a better understanding ....Statistical Analysis of State-Dependent Government Spending Multipliers. This project aims to provide a new statistical analysis of the government spending multiplier by acknowledging that government spending is the sum of sectoral spending which has heterogeneous effects on the economy. An added complication is that the multiplier can also be state-dependent, meaning that its magnitude can differ across recessions and expansions. Expected outcomes of this project include a better understanding of the components of the multiplier by novel decomposition and the development of a new statistical test for the state-dependency of the multiplier. This should provide significant benefits to researchers by bringing in new tools and insights and to policymakers by providing timely guidance on fiscal policies.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
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
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
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