Boomerang price shocks in electricity: impact of asset write downs and regulatory suppression on price shocks in the network electricity sector

<p>Electricity prices doubled between 2007 and 2013 in most Australian capital cities (Mountain, 2020, p188). The network sector was the dominant driver of higher electricity prices (Australian Competition and Consumer Commission, 2018, piv). The prices of state-owned networks rose significantly higher than private peers (Australian Competition and Consumer Commission, 2018, pp10-23). </p> <p>This empirical observation has led to duelling narratives. The <em>gold-plating </em>narrative contends that deficiencies in the regulatory framework incentivised state-owned networks to seek excessive expenditure and returns (Mountain, 2010, p5770; and Grattan Institute, 2012, p3). In contrast, the <em>keep the lights on </em>narrative argues that higher expenditure was required to address reliability and safety issues, following regulatory decisions in the previous decade that suppressed expenditure and ‘wrote down’ asset values (Ausgrid, 2008, p4). </p> <p>This paper contributes to the literature by using a ‘mechanistic’ model to quantify price movements using variables identified in both narratives. The model has been adapted from the ecology field and has been fitted with data from the NSW distributor Ausgrid, the network with the largest price increase in the National Electricity Market. </p> <p>Our key finding is that the <em>gold-plating </em>variables including stronger reliability targets, overstated demand forecasts, declining efficiency and higher rate of return contributed to about half of Ausgrid’s price increase between 2009 to 2014. The variables identified by the <em>keep the lights on </em>narrative such as asset write downs, suppressed replacement and declining energy volumes accounted for the other half. </p> <p>We contend that the lessons of the <em>keep the lights on </em>narrative have been ignored by policy makers. We identify key metrics of regulatory suppression to show that South Australian, Victorian, and Tasmanian distribution networks are at risk of price shocks in the future. The analysis presented in this paper shows that these networks have a significantly under-valued Regulatory Asset Base and replace assets below a sustainable rate. Together, our model suggests these metrics are a recipe for steeply rising prices in the future. </p>