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Magnus Söderberg

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magnus.soderberg@ratio.se
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  • Griffith University

Professor Magnus Söderberg is affiliated with Griffith University in Australia, where he is director of the Center of Applied Energy Economics and Policy Research (CAEEPR). He works broadly with energy and environmental economic challenges. At Ratio, Magnus primarily works with behavioral economics applications with the aim of reducing the environmental burden of the waste sector.



Related publications

    Working paper

    A penalization approach for estimating inefficiency in stochastic frontier panel models

    Tchatoka, F. D., Söderberg, M., Hakeem, M. A.
    Download

    Publication year

    2025

    Published in

    University of Adelaide, School of Economics and Public Policy Working Paper.

    Abstract

    Efficiency analysis is essential for evaluating the performance of entities that deliver essential or standardized services. The estimator proposed by Jondrow et al. (1982) is widely used in this context, but it has been criticized for several shortcomings: it tends to bias inefficiency estimates toward the mean, distorts the distribution, and misrepresents the conditional distribution of inefficiency—especially in cross-sectional data.

    Zeebari et al. (2023) propose a regularization-based alternative that aligns sample and theoretical moments; however, this method is primarily designed for cross-sectional applications and does not extend naturally to panel data.

    In response, this paper introduces a penalized mode estimator for unit inefficiency in panel data. The estimator accounts for heteroskedasticity in both inefficiency and idiosyncratic errors. A closed-form expression is derived, and Monte Carlo simulations demonstrate its superior performance compared to existing methods. An empirical application using data from electricity providers in Australia, Canada, and New Zealand highlights the practical advantages of the proposed approach.

    Article (with peer review)

    Scale properties and efficient network structures in the Swedish electricity distribution market

    Söderberg, M., Vesterberg, M.

    Publication year

    2025

    Published in

    Journal of Regulatory Economics

    Abstract

    This paper examines the Swedish electricity distribution sector to highlight three key findings. First, we identify significant economies of scale among electricity distribution firms, indicating that larger firms operate more efficiently. Second, we explore alternative market structures and demonstrate that these can substantially reduce the aggregated costs of electricity distribution. Third, we use novel survey data to show that firms perceive the economic incentives for mergers to be insufficient. These findings suggest that policymakers should consider creating a regulatory environment that encourages consolidation and enhance efficiency in the sector.

    Working paper

    Working Paper No. 381: How social norm feedback can reduce unsorted waste and increase recycling in the residential sector

    Ek, C., & Söderberg, M.
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    Publication year

    2024

    Published in

    Ratio Working Paper No Series.

    Abstract

    The EU waste legislation requires member states to prepare 55% of municipal waste for re-use and recycling, to recycle 65% of all packaging waste by 2025, and to limit landfilling municipal waste to 10% by 2035. A large majority of the member states are at risk of missing one or more of these targets. Thus, there is a need to identify additional policies beyond command-and-control and market-based instruments that can effectively contribute to these targets. This policy brief describes one such policy: social norms feedback. This has been trialled with nearly 20,000 households in Sweden that faced Pay-as-you-throw schemes. In this setting, the unsorted waste fraction was reduced by around 10% and three quarters of that was due to increased recycling. The large trial sample and wide-ranging socio-economic characteristics suggests that 10-20% reduction of unsorted waste can be expected in jurisdictions with flat tariffs. If local governments collaborate and share the cost of waste truck equipment, then the policy is likely to generate a substantial economic surplus.

    Article (with peer review)

    Norm-based feedback on household waste: Large-scale field experiments in two Swedish municipalities

    Ek, C. & Söderberg, M.
    Download

    Publication year

    2024

    Published in

    Journal of Public Economics

    Abstract

    We conduct two large-scale randomized controlled trials to produce the first evidence that Home Energy Report-type norm feedback letters can be used to reduce household waste. We explore several feedback variants, including a novel short-run dynamic norm that emphasizes ongoing changes in waste behavior. Waste reductions are on the order of 7%–12% for all treatments, substantially larger than usually found in the energy or water domains. Effects are mostly driven by increased recycling of packaging and remain largely intact a year after the intervention ended. Feedback is highly cost effective compared to alternative non-price waste policies. However, net social benefits depend on household preferences for receiving feedback, which we elicit in a valuation survey, and whether existing waste fees internalize the marginal social cost of waste.

    Working paper

    Ratio Working Paper No. 372: Customers’ value-for-money for a regulated service across differen towners

    Biggar, D., & Söderberg, M. (2024). Customers’ value-for-money for a regulated service across different owners (Ratio Working Paper No. 372). Ratio.
    Download

    Publication year

    2024

    Published in

    Ratio Working Paper Series.

    Abstract

    What are the best ownership and governance arrangements for a natural monopoly facility? There are three broad approaches: (a) private ownership, coupled with arms-length public utility regulation; (b) some form of government (central, state, or local) ownership; and (c) customer or community ownership. While there is a substantial literature comparing outcomes under private and public (i.e., government) ownership, there is relatively little literature comparing private and/or government ownership with customer ownership. One of the obstacles of performance comparison is that different businesses may choose a different price-quality trade-off, making direct comparison impossible. In this study we cut through this problem by comparing customer perceptions of value-for-money. The study is based on interviews of more than 600 randomly selected electricity distribution customers in Sweden, approximately 150 in each ownership category (municipal, customer, private, and state). These distributors are subject to an identical regulatory framework. The results show that those owned directly by customers are perceived to deliver significantly more value for money than those owned by the government or by private investors. These results lend weight to the view that a well-governed customer-owned utility may lead to better outcomes than other owners.

    Working paper

    Working Paper No. 367: The Impact of population size and bin structure on the cost of municipal solid waste: evidence from Sweden and Norway

    Söderberg, M., Sundriyal, V. K., & Gabrielsson, J.
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    Publication year

    2023

    Published in

    Ratio Working Paper Series

    Abstract

    Increasing waste levels, combined with ambitious environmental targets, are exerting upward pressures on the cost for municipal solid waste in many countries. The purpose of this study is to investigate what municipalities can do to counteract this development. We collect information about population, cost and waste from 225 Swedish and Norwegian municipalities and empirically investigate how waste bin structure/type of waste collection system and population affect municipalities’ waste cost. Results indicate that 4-compartment bins is the most expensive bin structure (+13%) and using the same bin types in detached and multi-family dwellings leads to coordination savings (-18%). The cost minimising population is slightly above 600,000 inhabitants. Several of the surveyed municipalities have substantially fewer inhabitants than that and cost per inhabitant can be reduced by up to 30% in several locations through collaborations with larger neighbours. In Sweden, transferring the responsibility for solid waste from the municipalities (290 in total) to the regions (20 in total) would eliminate almost all scale inefficiencies.

    Article (with peer review)

    The Effect of Working from Home on Waste Behaviors

    Bonev, P., Söderberg, M., & Unternährer, M.

    Publication year

    2023

    Published in

    SSRN 4333193.

    Abstract

    We evaluate the effect of working from home on waste generated by individuals both at and away from their homes. To this end, we collect a unique dataset that matches administrative household-level waste data from Sweden with survey data on how many hours individuals work from home. A novel identification approach allows us to link waste generated away from home to the choice of work location. Our results suggest that working from home reduces organic and residual waste by 20% and 12%, respectively.

    Article (with peer review)

    Network Regulation under electoral competition

    Leroux, A., & Söderberg, M.

    Publication year

    2023

    Published in

    Energy Economics, 106614.

    Abstract

    Academics and policymakers generally agree that energy infrastructure should be subject to price regulation. More and more critics of modern regulatory approaches, however, point to the apparent failures of these mechanisms to achieve competitive pricing in practice. Some have suggested that customers ought to be involved in the regulatory process, but it is uncertain how customers’ perspectives can best be incorporated. In this study, we evaluate how electoral competition influences monopoly pricing by extending well-known regulatory laboratory experiments. We show that electoral competition has a significant and negative impact on prices. This effect disappears when electoral competition is implemented jointly with incentive regulation, implying substitutability rather than complementarity of regulation and electoral competition.

    The article can be accessed in full here.

    Article (with peer review)

    Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data

    Duras, T., Javed, F., Månsson, K., Sjölander, P., & Söderberg, M.

    Publication year

    2023

    Published in

    Energy Economics, 106621.

    Abstract

    Agencies that regulate electricity providers often apply nonparametric data envelopment analysis (DEA) to assess the relative efficiency of each firm. The reliability and validity of DEA are contingent upon selecting relevant input variables. In the era of big (wide) data, the assumptions of traditional variable selection techniques are often violated due to challenges related to high-dimensional data and their standard empirical properties. Currently, regulators have access to a large number of potential input variables. Therefore, our aim is to introduce new machine learning methods for regulators of the energy market. We also propose a new two-step analytical approach where, in the first step, the machine learning-based adaptive least absolute shrinkage and selection operator (ALASSO) is used to select variables and, in the second step, selected variables are used in a DEA model. In contrast to previous research, we find, by using a more realistic data-generating process common for production functions (i.e., Cobb–Douglas and Translog), that the performance of different machine learning techniques differs substantially in different empirically relevant situations. Simulations also reveal that the ALASSO is superior to other machine learning and regression-based methods when the collinearity is low or moderate. However, in situations of multicollinearity, the LASSO approach exhibits the best performance. We also use real data from the Swedish electricity distribution market to illustrate the empirical relevance of selecting the most appropriate variable selection method.

    The article in total can be read here.

    Article (with peer review)

    Regularized conditional estimators of unit inefficiency in stochastic frontier analysis, with application to electricity distribution market

    Zeebari, Z., Månsson, K., Sjölander, P., & Söderberg, M.

    Publication year

    2023

    Published in

    Journal of Productivity Analysis, 59(1), 79-97.

    Abstract

    In stochastic frontier analysis, the conventional estimation of unit inefficiency is based on the mean/mode of the inefficiency, conditioned on the composite error. It is known that the conditional mean of inefficiency shrinks towards the mean rather than towards the unit inefficiency. In this paper, we analytically prove that the conditional mode cannot accurately estimate unit inefficiency, either. We propose regularized estimators of unit inefficiency that restrict the unit inefficiency estimators to satisfy some a priori assumptions, and derive the closed form regularized conditional mode estimators for the three most commonly used inefficiency densities. Extensive simulations show that, under common empirical situations, e.g., regarding sample size and signal-to-noise ratio, the regularized estimators outperform the conventional (unregularized) estimators when the inefficiency is greater than its mean/mode. Based on real data from the electricity distribution sector in Sweden, we demonstrate that the conventional conditional estimators and our regularized conditional estimators provide substantially different results for highly inefficient companies.

    The article can be accessed here.

    Article (with peer review)

    Implicit yardstick competition between heating monopolies in urban areas: Theory and evidence from Sweden

    Bonev, P., Glachant, M., & Söderberg, M.

    Publication year

    2022

    Published in

    Energy Economics, 109, 105927.

    Abstract

    This article examines a novel regulatory mechanism in a setting with multiple local monopolists. The mechanism rests upon the behavioral assumption that cus- tomers form opinions about prices by comparing them with prices set by nearby mo- nopolies and that this comparison influences their behavior. In this way, an “implicit yardstick competition” emerges among monopolists although they do not operate in the same markets. We test this mechanism using a unique dataset of unregulated district heating monopolists in Sweden. We find a large effect of neighbors’ prices, which indicates that the implicit yardstick competition has a considerable disciplin- ing effect on monopolies’ pricing behavior.

    Working paper

    An empirical evaluation of the effect of working from home on waste behavior

    Bonev, P., Soederberg, M., & Unternährer, M.

    Publication year

    2022

    Published in

    University of St. Gallen, School of Economics and Political Science.

    Abstract

    We evaluate the effect of working from home on waste generated by individuals both at and away from their homes. To that end, we collect a unique dataset that matches administrative household-level waste data from Sweden with survey data on how many hours individuals work from home. A novel identification approach allows us to link waste generated away from home to the choice of location of work. Our results suggest that working from home reduces organic and residual waste by 20% and 12%, respectively.

    The article can be accessed here.

    Working paper

    Ratio Working Paper No. 346: Does published research influence policy outcomes? The case of regulated electricity networks in western Europe

    Söderberg, M. & Yang, Y.
    Download

    Publication year

    2021

    Published in

    Ratio Working Paper

    Abstract

    This study investigates the relationship between number of articles about electricity network regulation published in peer-reviewed journals and actual electricity network prices. Data on published articles are sourced from ScienceDirect and network prices are provided by Eurostat. Different empirical approaches give the same result, namely that an increase in the number of published articles reduces the regulated network price. When articles are highly relevant, one additional article published per year reduces the price by at least 10%. Results also show that the influence on prices is delayed and the effect lasts for a few years. A survey is sent out to regulators to better understand if the relationship can be interpreted as causal. Responses reveal that regulators do access and incorporate relevant research into their work. Considering the cost required to continuously publish relevant articles, research seems to be a highly effective complement to more traditional regulatory work.

    Working paper

    Ratio Working Paper No. 345: Regularized Conditional Estimators of Unit Inefficiency in Stochastic Frontier Analysis, with Application to Electricity Distribution Market

    Zeebari, Z., Månsson, K., Sjölander, P. & Söderberg, M.
    Download

    Publication year

    2021

    Published in

    Ratio Working Paper

    Abstract

    The practical value of Stochastic Frontier Analysis (SFA) is positively related to the level of accuracy at which it estimates unit-specific inefficiencies. Conventional SFA unit inefficiency estimation is based on the mean/mode of the inefficiency, conditioned on the estimated composite error. This approach shrinks the inefficiency towards its mean/mode, which generates a distribution that is different from the distribution of the unconditional inefficiency; thus, the accuracy of the estimated inefficiency is negatively correlated with the distance the inefficiency is located from its mean/mode. We propose a regularized estimator based on Bayesian risk (expected loss) that restricts the unit inefficiency to satisfy the underlying theoretical mean and variation assumptions. We analytically investigate some properties of the maximum a posteriori probability estimator under mild assumptions and derive a regularized conditional mode estimator for three different inefficiency densities commonly used in SFA applications. Extensive simulations show that, under common empirical situations, e.g., regarding sample size and signal-to-noise ratio, the regularized estimator outperforms the conventional (unregularized) approach when the inefficiency is greater than its mean/mode. With real data from electricity distribution sector in Sweden, we demonstrate that the conventional conditional estimators and our regularized conditional estimators give substantially different results for highly inefficient companies.