New methods for modelling complex trends in climate and energy time series
- Professor Heather Anderson
- Professor Jiti Gao
- Professor Farshid Vahid
- Dr Wei Wei
- Professor Oliver Linton (University of Cambridge, U.K.)
- Professor Asger Lunde (Aarhus University, Denmark)
- Professor Peter Phillips (University of Auckland and Yale University)
This research group is part of the Monash Business School’s International Network of Excellence in High-Dimensional Dynamical Systems.
Project background and aims
This project aims to contribute to Australian and international efforts on emission control by advancing the methods for quantifying the relationships between energy production, emission and climate, and assessing the real and financial risks associated with changing the ways in which economies produce and use energy. This research adds the expertise of social scientists and time series analysts to societal efforts to ensure sustainable economic growth with a stable energy supply that has lower carbon emissions by
- Developing a scientific methodology that uses relevant quantitative information to identify the advanced economies that are similar to Australia; and
- Combining the experiences of this group of countries to provide an objective prediction of the likely consequences of Australia adopting specific renewable energy policies.
Specific aims of the project are to:
- Develop inferential methods that provide valid measures of common trends in variables, regardless of the exact nature of the trend (be it stochastic, deterministic, linear or nonlinear), and use these methods to measure the sensitivity of temperatures and other climatic features such as sea levels to greenhouse gases (GHG)
- Develop inferential methods that measure time-varying and non-linear relationships between trending variables such as greenhouse gases and energy consumption, and use these methods to forecast GHG levels under different scenarios.
- Develop inferential methods that allow the use of data from other countries with similar time series features (in disaggregated levels) to predict the effect of Australia adopting a policy that these other countries have already adopted.
- Adopt and adapt econometric models of volatility in asset markets to electricity prices in order to measure and forecast risk in this market, and hence facilitate the pricing of derivatives such as futures contracts.
The proposed work will develop new knowledge in the areas of energy and climate econometrics, and lead to improved precision in the measurement and prediction of environmental conditions, electricity generation and their co-movement. This will facilitate the development of policies that can meet Australia’s climate change goals whilst ensuring stable energy markets.
Australian Research Council Discovery Grant: DP200102769