Examining the long term relationships between energy commodities prices and carbon prices on electricity prices using Markov Switching Regression

The present work aims to quantitatively measure the relationships between the price of energy commodities, coal, gas natural, fuel oil, carbon prices and the price of wholesale electricity in the Iberian Electricity Market, using 2018 daily data. To examine this relationship, we considered both techniques, Markov-Switching Dynamic Regression and Markov-Switching Autoregressive Regression, and proposed two equations with electricity price and coal price as dependent variables. According to the parameters estimated in the model, coal and gas affect the cost of electricity moderately at times in the day that are highly recessive. During the 2018 daily periods analysed, the relative changes in gas and coal prices led to a loss of competitiveness of natural gas, increased by the moderate evolution of carbon prices, and therefore the cost of coal fell sharply in the recent past. The evolution of both time-varying transition probabilities and energy commodities prices variables is informative. The transition probabilities of staying in the same state change throughout our sample of energy commodities and wholesale electricity prices. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Automated summary

The study aims to analyze the relationship between energy commodity prices, such as coal, natural gas, fuel oil, carbon prices, and wholesale electricity prices in the Iberian Electricity Market. The study uses Markov-Switching Dynamic Regression and Markov-Switching Autoregressive Regression techniques and proposes equations with electricity and coal prices as dependent variables. The results show that coal and natural gas moderately affect electricity costs during highly recessive time periods.