Local electricity distribution firms own their power grids, making them natural monopolies with no direct competitors due to the inefficiency of having multiple grid owners competing in parallel. Thus, since these firms have a responsibility toward their shareholders to maximize profits, there are no natural incentives for price competition, leaving customers susceptible to predatory pricing practices and high electricity costs. To address this issue, most developed societies impose regulations to minimize the market power of natural monopolies. Typically, these regulations impose a ceiling on prices to limit consumer costs, ensuring firms can still cover expenses and possibly secure a sustainably profitable return, while also pressuring firms to lower costs, and consumer prices to the standards of the most efficient monopolies.
It has been argued that Sweden's regulation of electricity distribution prices – not to be confused with flexible Nordpool market prices – has been less successful than other comparable countries. According to Eurostat, during the low-inflation era from 2010 to 2020, Sweden experienced a 37% increase in real distribution prices, while real prices in Norway and Denmark remained nearly unchanged, and real prices in the European Union decreased. Moreover, not long ago, Ellevio predicted continued extreme electricity distribution price increases following the energy crises as a consequence of the war in Ukraine (www.dn.se, 14 Sep. 2022).
The European Commission has argued that one of the main reasons why electricity distribution prices have increased in countries such as Sweden is because the cost incentives have not been strong enough. Why hasn't the electricity distribution sector's inefficiencies in Sweden and other high-cost EU countries been resolved? One reason is the unreliability of available methods to identify firm-level inefficiencies for regulatory purposes, and the existing model does not sufficiently safeguard the economic interests of end households and industries. Therefore, our aim is to investigate these issues:
Professor Kristofer Månsson is a full professor in Statistics at Jönköping International Business School, Jönköping University, Sweden, since 2019. Kristofer Månsson’s research is focused on causal inference and forecasting using machine learning techniques and efficiency analysis via data envelopment and stochastic frontier analysis. His publication list includes variable selection methods for data envelopment analysis and instrumental variable selection. It also includes estimation methods for inefficiencies via stochastic frontier analysis and forecasting using mixed data sampling.
In addition to the journal publications, Månsson is project leader (together with professor Pär Sjölander) in a research project funded by the Hamrin foundation entitled “Improving the Swedish regulatory model for electricity distribution”. He is also involved in a second research project focusing on nowcasting Swedish gross domestic production via machine learning techniques funded by Torsten Söderberg foundation.
Månsson earned his PhD in statistics developing shrinkage estimators for common microeconometric models. 2014 he earned his second PhD in economics focusing on nonlinear time series analysis.
Professor Pär Sjölander is a full professor in Econometrics at Jönköping International Business School, Jönköping University, Sweden, since 2014. He has held the following academic leadership roles; Prodekanus of Jönköping University (2019–2024), Head of Discipline in Statistics (2014–2019), and Academic Director of International Development Collaboration (2013–2024). Sjölander has also served on the JIBS Strategy Group (2014–2020), the Research Faculty Board (2012–2024), and the Board of Education and Research Education (2019–2024).
As a professor of econometrics, Sjölander’s research emphasizes developing and applying empirically relevant statistical methods in economic sciences, ultimately aimed at addressing practical, socially relevant challenges. His current research mainly focuses on energy economics, developing and utilizing advanced econometric methods and various machine learning approaches. Sjölander co-leads a Hamrin Foundation-funded research project with professor Kristofer Månsson, titled ”Improving the Swedish Regulatory Model for Electricity Distribution”.
“The Hamrin Foundation distinguishes itself by emphasizing research with clear societal relevance and prioritizing effective research communication to ensure public accessibility. The application process is very non-bureaucratic concentrating on the project's societal relevance rather than bureaucratic formalities. This approach reflects that this foundation understands that addressing complex societal challenges often requires the application of advanced objective research methods”
