TY - JOUR
T1 - Decoding the Australian Electricity Market
T2 - New Evidence from Three-Regime Hidden Semi-Markov Model
AU - Apergis, Nicholas
AU - Gozgor, Giray
AU - Lau, Chi Keung
AU - Wang, Shixuan
PY - 2019/2/1
Y1 - 2019/2/1
N2 - The hidden semi-Markov model (HSMM) is more flexible than the hidden Markov model (HMM). As an extension of the HMM, the sojourn time distribution in the HSMM can be explicitly specified by any distribution, either nonparametric or parametric, facilitating the modelling for the stylised features of electricity prices, such as the short-lived spike and the time-varying mean. By using a three-regime HSMM, this paper investigates the hidden regimes in five Australian States (Queensland, New South Wales, Victoria, South Australia, and Tasmania), spanning the period from June 8, 2008 to July 3, 2016. Based on the estimation results, we find evidence that the three hidden regimes correspond to a low-price regime, a high-price regime, and a spike regime. Running the decoding algorithm, the analysis systemically finds the timing of the three regimes, and thus, we link the empirical results to the policy changes in the Australian National Electricity Market. We further discuss the contributing factors for the different characteristics of the Australian electricity markets at the state-level.
AB - The hidden semi-Markov model (HSMM) is more flexible than the hidden Markov model (HMM). As an extension of the HMM, the sojourn time distribution in the HSMM can be explicitly specified by any distribution, either nonparametric or parametric, facilitating the modelling for the stylised features of electricity prices, such as the short-lived spike and the time-varying mean. By using a three-regime HSMM, this paper investigates the hidden regimes in five Australian States (Queensland, New South Wales, Victoria, South Australia, and Tasmania), spanning the period from June 8, 2008 to July 3, 2016. Based on the estimation results, we find evidence that the three hidden regimes correspond to a low-price regime, a high-price regime, and a spike regime. Running the decoding algorithm, the analysis systemically finds the timing of the three regimes, and thus, we link the empirical results to the policy changes in the Australian National Electricity Market. We further discuss the contributing factors for the different characteristics of the Australian electricity markets at the state-level.
KW - Australian electricity markets
KW - Hidden semi-Markov model
KW - Time-varying mean
KW - Price spikes
KW - Regime-switching
UR - http://www.scopus.com/inward/record.url?scp=85057037485&partnerID=8YFLogxK
U2 - 10.1016/j.eneco.2018.10.038
DO - 10.1016/j.eneco.2018.10.038
M3 - Article
VL - 78
SP - 129
EP - 142
JO - Energy Economics
JF - Energy Economics
SN - 0140-9883
ER -
