Structural Changes in Contagion Channels : the Impact of COVID-19 on the Italian Electricity Market

Participants in electricity zonal markets are mostly concerned with two layers of value-chain in the production, investment, consumption of electricity and its derived products. On the other hand, achieving the goal of restructuring, policy regulations and transformation, requires accurately identifying, quantifying, and measuring risk coupled with their corresponding return, leading to long-run efficiency benefits. Accomplishing these tasks became more challenging after the outbreak of the pandemic. To this effect, we propose a novel econometric approach to the identification of relevant market factors: (i) that influence structural changes positively and negatively, (ii) that contribute to high or low log-price transformation and (iii) that either transmit or receive risk and those that play dominant roles in terms of risk propagation and contributions to log-price transformation. The proposed model extends Bayesian graphical models with change points to a multiple layer set-up. The multi-layer graph encodes the two relevant channels of shock transmission that are volatility and log-transformed price contagion effects. The choice of these two layers seems a natural choice because electricity prices and their spiky nature coupled with inherent volatility constitute essential elements for market players to maximize their profits. The change point specification allows for detecting relevant changes in the energy market. We applied the proposed econometric framework to the Italian zonal markets. Our findings provides new relevant insights into price spike and volatility transmission in the zonal markets. The model captured relevant abrupt changes in prices and volatility in the zonal electricity market, and provides new evidence of interconnections of the risk alone, log-transformed price process alone, and risk versus log-transformed price process relationship and their interactions