|dc.description.abstract||Climate change has drawn increasing attentions in recent years due to its impact on the global environmental system. It motivated policy interventions around the world to constrain emissions of Greenhouse Gases (GHG), which has been scientifically proved to be the cause of this phenomenon. In July 2012, the Australian government introduced Carbon Pricing Mechanism (CPM) as national climate change mitigation policy. This thesis utilizes statistical models and experimental methodology to evaluate the effects of carbon pricing and related policy uncertainty on Australian electricity sector.
The study firstly evaluates the effect of CPM implementation on both electricity spot market and derivative market. After refining the collected sampling data to non-zero trading volume electricity price, changes in electricity prices and volatility level that can be attributed to carbon pricing are assessed with the designed algorithms. By distinguishing between the exchange-traded (ETD) and over-the-counter (OTC) contracts, this study investigates the response to CPM implementation in these two segments of electricity derivative market. Besides analysing market characteristics such as turnover, liquidity and speculation with numerical and algorithm methods, the study applies parametric asymmetry statistical test, which is based on the spatial correlation concept from the chaos theory, to detect the nonlinear price movement. The transition of price regime is further studied with the Smooth Transition Autoregressive (STAR) model simulation, which enables the division of one-dimensional space into k regimes with linear autoregressive model.
As carbon costs were included in the ETD contracts, whereas it was not the case for OTC contracts, an implied carbon price is derived from the market data for electricity derivative contracts to reflect the market expectation of carbon costs. After simulating the dynamics of implied carbon price with the Autoregressive Conditional Heteroscedasticity (ARCH) model, an out-of-sample forecasting is conducted with the one-step ahead projection technique to validate the model simulation. Moreover, Vector Autoregressive (VAR) model links implied carbon price and the S&P/ASX 200 Utilities (AXUJ) index of Australian Stock Exchange, in order to explore whether expectation of carbon price in electricity derivative market influenced the stock price variability of electricity companies. By deriving the impulse response function, which is the long-run multiplier derived from the vector moving average (VWA) form of the VAR model, the study is able to trace out the time path of implied carbon price and the AXUJ index after one unit volatility shock within twenty periods. The projection indicates the magnitude of volatility interaction between the electricity derivative market and the Australian stock market.
During the CPM implementation, policy uncertainty arose as a result of political controversies. A laboratory experiment is designed to collect data from random selected cohorts, which helps to assess the policy risk as well as to analyse the influence of policy uncertainty on production decisions and abatement investment. In the experiment, players act as independent emitters, whose production activities generate revenue and release emissions, which in turn induce compliance costs under the regulation. However, emitters could reduce their compliance costs by either upgrading abatement technology or lowering production level. The aim of profit maximization motivates them to adjust production and investment expenditures according to individual efficiencies. Furthermore, the experiment innovates with a specific mechanism to simulate the policy uncertainty related to CPM implementation. A random probability following the binomial statistical distribution is generated to represent the likelihood of policy repeal, which determines the termination of the regulation framework. Data regarding emitters’ choices in production quantity and investment are gathered to analyse behaviour under a regulation framework. The experimental data are then compared with the performance of controlled group, whose behaviour is observed under the condition without policy uncertainty. The results are further interpreted with the statistical methodologies such as fixed-effect regression and the Wilcoxon–Mann–Whitney test to reveal the effect of uncertainty associated with carbon pricing policy implementation.
Statistical analysis shows an increasing trend of electricity price level as a result of carbon pricing. Price reaction in electricity spot market manifested a pattern of abrupt increase, while the price transition in electricity derivative market was smoother. In comparison to OTC contracts, short-term ETD derivatives demonstrated faster price transition. This can be explained by the growing speculative activities of financial intermediaries that drove up turnover and liquidity in the ETD market. Furthermore, autoregressive model with conditional heteroscedastic error term proved its capability to capture the dynamics of implied carbon price. Its course reflected the influence of policy uncertainties on market expectation. Due to the high carbon pass-through rate, carbon pricing led to higher wholesale electricity price, which in turn enhanced the expected return of non-state-owned electric utility companies. As the dominant participants on the electricity derivative market, electricity generators and retailers have little exposure to the stock market. As a result, the magnitude of volatility co-movement between implied carbon price and the AXUJ index of the Australian Stock Exchange was limited. Research findings also illustrate that uncertainties associated with the regulation framework undermined the policy effect and weakened the motivation for abatement investment. As a consequence, emitters conducted less abatement than the predetermined policy target. Moreover, after the regulation termination, emitters with high emission intensities restarted to emit because of removal of emission constraint. Overall, data collected from the electricity markets and experiment were reliable to evaluate the effect of carbon pricing policy on electricity sector.
Experience from Australian CPM implementation demonstrated the effect of carbon pricing policy in constraining GHG emissions of the electricity sector. A well-developed derivative market would contribute to the mitigation of risk caused by carbon pricing. However, policy uncertainty could induce speculations, which weaken the emission abatement motivation. Hence, active policy reaction and persistent engagement are necessary for the combat against climate change and sustainable development of human society. The studies in this thesis report the actual development of Australian electricity markets under the influence of CPM. It contributes to the policy effect evaluation and the future design of carbon pricing policy.||en_AU|
|dc.publisher||University of Sydney||en_AU|
|dc.publisher||Faculty of Agriculture and Environment||en_AU|
|dc.publisher||School of Life and Environmental Sciences||en_AU|
|dc.subject||Implied Carbon Price||en_AU|
|dc.title||The Effects of Carbon Pricing and related Policy Uncertainty on the Australian Electricity Sector||en_AU|
|dc.type.pubtype||Doctor of Philosophy Ph.D.||en_AU|
|Appears in Collections:||Sydney Digital Theses (Open Access)|