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
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
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
Development of general methodology for estimating complex time series models. This project will develop novel methods and models for analysing socio-economic and financial data measured over time and will illustrate them with applications. The methods will allow for more efficient and more accurate processing of information and better forecasting which will facilitate better management and more timely policy response.
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
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.Read moreRead less
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.Read moreRead less
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.
Approximate Bayesian computation in state space models. Economic and financial data frequently exhibit dynamic patterns, driven by unobserved processes that relate to the behaviour of economic agents, or to institutional and technological change. To gain insight into such 'latent' processes is of paramount importance in terms of both understanding the economy and producing accurate, readily up-dated, forecasts of its future performance. Using a Bayesian approach, new simulation-based statistical ....Approximate Bayesian computation in state space models. Economic and financial data frequently exhibit dynamic patterns, driven by unobserved processes that relate to the behaviour of economic agents, or to institutional and technological change. To gain insight into such 'latent' processes is of paramount importance in terms of both understanding the economy and producing accurate, readily up-dated, forecasts of its future performance. Using a Bayesian approach, new simulation-based statistical methods for analysing latent variable models are proposed. Emphasis is given to the development of relatively simple techniques that are applicable to a wide range of empirically relevant models, with a view to improving the access of non-specialists to this powerful form of statistical analysis.Read moreRead less