Market Power Research Articles

Estimating labor market monopsony power from a forward-looking perspective

This paper proposes a new approach to estimate the monopsony power of the labor market based on a forward-looking model of firm wage posting and worker job separation. In contrast to the literature, workers make job switching decisions based on firm-specific wage growth trajectories associated with different employers. The model is estimated using a matched employer employee panel data from Germany. The separation elasticity estimated from this model is greater than that from the conventional approach, suggesting that ignoring worker responses to heterogeneous wage growth rates lead to a potential overestimation of the actual monopsony power.

A methodology to map chains of general practices in the Netherlands

Abstract Background Commercial entities are increasingly interested in acquiring Dutch general practices (GPs). They see profitable opportunities in upscaling by forming chains. Chain organizations integrate business processes of GPs within one organizational unit. The governance structure of these chains can be complex, leading to opacity and difficulties to see conflicts of interest and market power. To investigate how this development may have an impact on quality and accessibility of care, it is first needed to establish the ways in which these chains are formed. By mapping the chain structure in a data-driven way, impact monitoring becomes possible. For the Netherlands we investigated how chain structures of GPs can be empirically identified. Methods Background data of approximately 4,800 Dutch GPs from the Nivel Healthcare Professional Registries was linked with data from the Chamber of Commerce’s Trade Register. This enabled the determination of the legal form, business location, ownership, and director identification for all GPs. By this data-driven manner, the variation in organizational structures of all Dutch GPs was mapped and analyzed. Results Four different chain variants of Dutch GP chains were identified based on three types of relations between the chain organization and their GPs: ownership, location and the composition of the board of directors. Based on ownership, two ‘top-down’ chain variants were identified. Two ‘bottom-up’ chain variants were found based on location and board composition: (1) a chain organization acquires a seat on the board of the GP, and (2) the GP and the chain organization share the same business address. Combining these variants provides a new typology of GP chains in the Netherlands. Conclusions Our methodology enables to empirically map chain formation in primary care. By developing a new typology in a systematic way, a foundation is created to monitor organizational developments and their impact on quality and accessibility of care. Key messages • A typology of Dutch GP chains was developed based on three relations: the ownership, composition of the board and the establishment location of the chain organization and its practices. • Our methodology was put into practice to map different chain structures of GPs in the Netherlands, but it is not limited to primary care and can also be applied in other sectors and countries.

LFformer: An improved Transformer model for wind power prediction.

Wind power forecasting has complex nonlinear features and behavioral patterns across time scales, which is a severe test for traditional forecasting techniques. To address the multi-scale problem in wind power forecasting, this paper innovatively proposes an ultra-short-term forecasting model LFformer based on Legendre-Fourier, which firstly focuses on the important information in the input sequences by using the encoder-decoder architecture, and then scales the range of the original data with the Devlin normalization method, and then utilizes the Legendre polynomials to The data sequence is projected into a bounded dimensional space, the historical data is compressed using feature representation, then feature selection is performed using the low-rank approximation method of Fourier Transform, the prediction is inputted into the multilayer perceptron through the multi-scale mixing mechanism, and finally the results are outputted after back-normalization. The experimental results show that compared with the existing prediction methods, the model realizes the improvement of prediction accuracy and stability, especially in the ultra-short-term prediction scenario, with obvious advantages. The research results are not only valuable for improving the overall operational efficiency of the wind power system, but also help to enhance the stable operation of the power grid, which provides strong technical support and guarantee for wind power enterprises to improve the competitiveness of bidding for Internet access in the power market competition.

Developing the industrial capacity for energy transitions: Resource formation for offshore wind in Europe

As energy transitions progress from formative to growth or acceleration phases, issues related to resource formation increase in importance. In this paper we address a type of resource formation that has received scant attention in the sustainability transitions literature to date: developing the industrial capacity to manufacture and deliver key complementary assets (i.e. components and services) to large energy projects. Such supply chain elements constitute a significant share of investment, are crucial for the upscaling of low-carbon technologies, and offer important job and value creation opportunities for different regions and countries. Empirically we study the build-up of industrial capacity to supply key complementary assets to the European offshore wind power market in the 2000–2019 period through three phases (formative, take-off, growth) of development. We provide explanations to observed spatio-temporal patterns of industrial capacity development by considering 1) industry life-cycle dynamics, 2) pre-existing assets and industrial relatedness, and 3) home market opportunities.

Has the real rate of return “depreciated”?

AbstractThe average depreciation rate in the United States has increased since the 1970s, a pattern most likely matched in other advanced economies. We argue that a higher depreciation rate has reduced the risk-free interest rate. We do so in a quantitative overlapping-generations model which allows for risk-premia and market power. We show that the importance of the rate of depreciation on the risk-free interest rate depends crucially on the elasticity of intertemporal substitution as well as the size of market power. Our calibrated model shows that higher depreciation plausibly reduced the risk-free rate by 30 basis points over the past half century. We contrast our results with models using a representative-agent framework (Farhi and Gourio in Accounting for macro-finance trends: market power, intangibles, and risk premia. Brookings papers on economic activity, 147, 2019) which typically do not find a role for the rate of depreciation.

Coordinating the energy transition: Electrifying transportation in California and Germany

California and Germany share ambitious emission reduction targets. Yet California is ahead of Germany in electrifying transportation by several metrics, including the number of public charging stations. We show that variation in the politics of coordination in California and Germany explains the different outcomes. Transforming energy systems requires coordination across various complementary technologies and infrastructures—here between the supply of electric vehicles and the buildout of charging stations. In California, a strong electrification coalition emerged across automakers selling electric vehicles as well as utilities and third-party firms providing charging infrastructure. Power market rules made capital investments for charging infrastructure instantly profitable for California monopoly utilities. By contrast, in Germany's liberalized power market, investing in capital-intensive charging infrastructure was not profitable for electric utilities. As a result, utilities did not emerge as a political force in the electrification coalition. Instead, utilities and automakers were in gridlock, failing to coordinate electric vehicle rollout and public charging station buildout. Our findings highlight the limits of business-led coordination, raising the question which institutions help address coordination failures in clean energy transitions.

Green Technology Innovations and Corporate Customer Concentration—The Perspectives of Financing Constraints and Social Responsibility

Green technology innovations propel both economic development and environmental sustainability. Exploring the contributing factors to green technology innovations carries important policy implications, but research from the perspective of supply chain relationships has been rare. This paper examines the impact of corporate customer concentration on green technology innovations and explores its influencing mechanisms using the data of Chinese A-share listed companies. The results show that a high customer concentration inhibits the quantity and quality of green technology innovations, a finding that is robust when endogeneity is addressed and when alternative measures and an alternative estimation model are employed. Financing constraints and social responsibility play intermediary roles in the impact of customer concentration on green technology innovations. A high customer concentration tends to increase corporate financing constraints and reduce corporate social responsibility performance, which hinder green technology innovations. The heterogeneity analysis reveals that the inhibitory effect of customer concentration on green technology innovations is less severe in digitally transformed enterprises, mature enterprises, or enterprises with a high level of market power. As this study provides a novel perspective on the contributing factors to corporate green innovations, it offers important policy recommendations.

Retraction Note: Performance comparison using firefly and PSO algorithms on congestion management of deregulated power market involving renewable energy sources

Retraction Note: Performance comparison using firefly and PSO algorithms on congestion management of deregulated power market involving renewable energy sources

Concentrated bank market and SMEs’ collateral issues: a study of the firms of developing Asian countries

Collateral is a significant challenge for small and medium enterprises (SMEs) in acquiring formal credit. Bank market concentration can cause to increase collateral demand through enhancing bank market power. This study explores the relationship between bank market concentration and the collateral challenges faced by SMEs in accessing bank credit by employing a probit regression model. The analysis utilizes a sample of over 25,000 firms from 19 developing Asian nations. The datasets combine firm-level data sourced from the Business Environment and Enterprise Performance Survey (BEEPS) with country-level financial data obtained from the Global Financial Development Data (GFDD) which are provided by the World Bank. The results reveal a significant positive correlation between bank market concentration and the collateral challenges encountered by SMEs in developing Asian countries. In markets characterized by high levels of banking concentration, financial institutions tend to exhibit risk-averse behavior, manifesting in an increased propensity to demand collateral for both SME and large enterprise loans. Consequently, this heightened bank concentration exerts additional pressure on SMEs in acquiring bank credit. To foster an environment conducive to SME financing, countries with high levels of banking concentration should enact regulatory measures aimed at managing and constraining market concentration levels.

The effects of bank mergers on listed U.S. borrowers

AbstractWe examine the effects of U.S. bank mergers on listed U.S. borrowers. Target bank borrowers receive lower loan spreads and no change in loan amount post‐merger in comparison to pre‐merger. In contrast, acquiring bank borrowers receive an increase in loan amount and a relatively small decrease in loan spread in the post‐merger period. Analysis shows that these benefits are available only when borrowers have bargaining power through lending relationships with non‐merging banks. We examine how borrower size, merger type, bank size, and borrower relationship intensity affect our results. Overall, our analysis suggests that efficiency gains from bank consolidation outweigh market power effects.

Impact of Servitization on Employee Satisfaction with Performance Evaluation Systems: A Case Study of China’s New Energy Sector Amid Power Market Reforms

This study investigates the mechanisms by which service-oriented transformation affects employee satisfaction with performance evaluation systems within the context of China’s electricity market reform. Using CGN New Energy’s Guangxi Branch as a case study and applying the grounded theory method, the research systematically analyzes employees’ perceptions of fairness, transparency, and career development during the transition from a product-oriented to a service-oriented model, based on in-depth interviews and surveys. The findings reveal that while servitization enhances employee skill development and career satisfaction, it also introduces challenges, such as increased work pressure and the demand for more transparent performance evaluation systems. This study provides valuable insights into optimizing management practices and performance evaluation systems in renewable energy companies, contributing both theoretically and practically to the literature on organizational transformation in the energy sector. These conclusions are not only significant for Chinese enterprises but also offer important reference points for global energy companies undergoing similar transitions.

Localized environmental governance for carbon dioxide removal in small island developing states: Challenges and opportunities

Accelerating the net-zero economy requires understanding energy consumption patterns, renewable technology attitudes, and acceptance of sustainable energy systems. This study explores how behavioral modification campaigns reduce residential energy use, promote energy-efficient products, and improve consumption patterns. Decentralization and digitization of energy infrastructure have spawned new markets and business models, giving customers more energy control and improving efficiency. The unique regulatory structure of Ireland's single power market makes it a compelling case study. The study examines Irish consumers' sustainable energy beliefs and behaviors from 1992 to 2022 using a 40-question survey. The data show that smart energy solutions for carbon-conscious families have pros and cons. Consumer knowledge of environmental issues and willingness to accept new energy technology are high, but cost and perceived complexity remain impediments to wider implementation. The research emphasizes technical innovation and behavioral change in energy reduction and greener energy promotion. These findings can help engineers, industry stakeholders, and politicians reach climate policy goals and carbon neutrality. Policymakers should support smart energy adoption, reduce cost barriers, and simplify the process. A fair and sustainable net-zero economy transition requires consumer education and decentralized energy market policies. This research underscores the importance of customized policies that leverage technology and behavior to mitigate the effects of climate change.

Optimization Study of New Media Operation on Enterprise Application Strategy

With the rapid development of Internet technology and the popularization of smart devices, new media platforms have become an important channel for modern information dissemination. This study will focus on the optimization measures of new media operations on the application strategies of enterprises and will focus on how most enterprises can increase market penetration and user interaction through new media platforms and study the impact of this change on the marketing efficiency and cost of enterprises. This research adopts a combination of quantitative and qualitative analysis to examine the actual effects and ROI of new media marketing campaigns by analyzing big data. Meanwhile, the successful marketing strategies of platforms such as TikTok are analyzed in-depth through case study methodology, exploring the data-driven mechanism and user behavior analysis behind them. According to research, new media marketing has high cost-effectiveness compared to traditional marketing means. It is not difficult to conclude that new media provide powerful marketing tools for enterprises, enabling them to achieve efficient market penetration at lower costs. However, enterprises also need to face the challenges of fast content updating and the risk of online public opinion, and a high degree of freedom of expression is one of the drawbacks of new media platforms. Therefore, enterprises in the future should pay more attention to the flexibility and innovation of new media strategies, and constantly adjust and optimize their marketing strategies to adapt to the fast-changing market environment and Internet environment.

Structural Market Power in the Presence of Renewable Energy Sources

Structural Market Power in the Presence of Renewable Energy Sources

Optimal Dispatching Strategy for Textile-Based Virtual Power Plants Participating in GridLoad Interactions Driven by Energy Price

The electricity consumption of the textile industry accounts for 2.12% of the total electricity consumption in society, making it one of the high-energy-consuming industries in China. The textile industry requires the use of a large amount of industrial steam at various temperatures during production processes, making its dispatch and operation more complex compared to conventional electricity–heat integrated energy systems. As an important demand-side management platform connecting the grid with distributed resources, a virtual power plant can aggregate textile industry users through an operator, regulating their energy consumption behavior and enhancing demand-side management efficiency. To effectively address the challenges in load regulation for textile industry users, this paper proposes a coordinated optimization dispatching method for electricity–steam virtual-based power plants focused on textile industrial parks. On one hand, targeting the impact of different energy prices on the energy usage behavior of textile industry users, an optimization dispatching model is established where the upper level consists of virtual power plant operators setting energy prices, and the lower level involves multiple textile industry users adjusting their purchase and sale strategies and changing their own energy usage behaviors accordingly. On the other hand, taking into account the energy consumption characteristics of steam, it is possible to optimize the production and storage behaviors of textile industry users during off-peak electricity periods in the power market. Through this electricity–steam optimization dispatching model, the virtual power plant operator’s revenue is maximized while the operating costs for textile industry users are minimized. Case study analyses demonstrate that this strategy can effectively enhance the overall economic benefits of the virtual power plant.

Cooperation and Profit Allocation Mechanism of Traditional and New Energy Complementary Power Generation: A Framework for Renewable Portfolio Standards

To boost the sustainable development of energy and the environment, a new power system with clean energy sources has been proposed by the Chinese government and traditional coal-fired power units are being transformed into regulation service providers for this new energy power system. Then, in this study, complementary power generation cooperation between traditional coal-fired power and new energy power producers is analyzed and discussed, and the energy quota agents, power sellers, are also included. Based on the cooperation game idea, different decision-making models of the tripartite power entities are elaborately constructed. Then, according to the price linkage mechanism between new energy and traditional thermal power, the profit of all power subjects is calculated and the profit allocation process is also analyzed. The conclusions show that the similarity of the two wholesale power price coefficients verifies the symmetry of the cooperative status of power producers. For BPC and SPC quota patterns, for example, BPC is bundled with new energy power and green certificates, whereas SPC is separate. Under the SPC pattern, there is a critical value for effective cooperation between the two power producers in the price range of traditional thermal power or new energy, which can achieve a win–win situation of increasing economic benefits and the consumption scale. Under the BPC pattern, the dynamic benefit compensation mechanism, which is the corrected Shapley value based on the RPS quota ratio, can solve the compressed profit of traditional coal-fired power producers. In contrast, the overall effect of profit allocation using the nucleolar method is not ideal. This study aims to give full play to the elastic induction effect of RPS to promote the sustainable transformation of traditional thermal power energy, especially combining the market mechanism to encourage traditional coal-fired power units to improve green technology to advance the construction of the green power market in China.

A study of electricity sales offer strategies applicable to the participation of multi-energy generators in short- and medium-term markets

Due to the increasing proportion of renewable energy, a multi-layered and multi-timescale energy market has emerged in many countries such as China. In the meanwhile, power generation companies must develop more intelligent and dynamic offer strategies to adapt to today's intricate energy trading. Because of the difficulty in describing the dynamic trading environment caused by the uncertainty of renewable energy, previous studies have not fully explored the offer strategy especially in both short-term and medium-term electricity markets. In response to this challenge, this research introduces a novel biding strategy framework leveraging a Asynchronous Advantage Actor-Critic (A3C) algorithm, which can effectively address the decision making in dynamic and uncertain energy markets. The framework focuses on intra-monthly transaction clearing mechanisms with the aim of optimally enhancing earnings. The research formulates an offer model both for thermal and renewable power generation enterprises, which is applicable to medium-term monthly and intra-monthly trading. The study then validates this framework through three distinct analyses: the returns of various bid methods under standard scenarios, the offer strategies return of power generation companies with diverse cost profiles, and the impact of varying renewable energy proportions. The multi-angle simulations confirm that the model presented in this paper offers a scientific basis for the development of offer strategies for power generation companies and enable power generating firms to effectively adopt to the current power market.

A systematic content analysis of innovation in European competition law

AbstractInnovation plays a crucial role in defining competitive dynamics. Given this fact, one might expect ‘innovation’ to play a consistent role in antitrust law. The present article conducts a systematic content analysis of the case law of the Court of Justice of the European Union to test this hypothesis. The findings suggest that EU courts treat innovation inconsistently in competition law cases, often assigning different weight to innovation in similar contexts and neglecting central parameters agreed upon in the literature. To address this inconsistency, the article proposes measures to maintain the predictability of competition law analysis while giving innovation a more central role in the definition of relevant markets, evaluation of market power, and assessment of practices.

Measurement and Validation of Market Power in China’s Log Import Trade—Empirical Analysis Based on PTM Model and AIDS Model

China is the world’s largest importer of logs, possessing the scale to exert significant influence in the international market. This paper uses a fixed-effect variable coefficient Pricing-to-Market panel model to measure China’s market power in log import trade. It also utilizes the Almost Ideal Demand System model from an elasticity perspective to explore the market behavior characteristics of various source countries in China’s log import trade, thereby validating the mechanism of market power. The results indicate that: ① China’s main trading partners can be categorized into four groups according to their market power in the log import trade. Specifically, China holds superlative market power in log imports from Indonesia, Malaysia, and Myanmar; holds strong market power in log imports from Russia, the Democratic Republic of the Congo, and Mozambique; holds weak market power in log imports from Papua New Guinea, Equatorial Guinea, France, Germany, Australia, and New Zealand; and holds no market power in Japan, Cameroon, and the United States. ② As China’s expenditure on log imports increases, there is a tendency to purchase high-quality precious wood and a greater concern for the legality of market transactions. Consequently, China is anticipated to augment its imports from source countries with no or weak market power. ③ The simple price elasticity of log imports from each source country is negative. Source countries with stronger market power tend to increase prices to achieve higher total revenue, while those with weaker market power are more inclined to lower prices to achieve the same. ④ Log products from various source countries are complementary in the Chinese market, indicating that China’s substantial demand for logs relies on the simultaneous supply from multiple countries and diverse wood types. Based on the existence or absence of market power in China’s log import trade, this paper provides targeted insights into enhancing international market power and reducing trade losses.

Data Protection Considerations in Competition Law Assessments: A Qualitative Document Analysis of EU Decision Texts

Abstract Personal data are both protected by a fundamental right and serves as a source of market power. As such, a complex interplay between data protection and competition law arises, sparking debate among policymakers and scholars on whether to incorporate data protection considerations (DPCs) in competition law assessments. Proponents argue that competition cases involving such an interplay require a normative contribution from data protection law, while opponents emphasize the practical challenges of considering data protection as a non-economic public policy objective. We identify nine ways in which data protection might ultimately surface in competition law assessments, categorized into five areas: (i) competition enforcement actions, (ii) existing legal and regulatory framework, (iii) personal data collection, (iv) exclusionary abuses, and (v) alleviation of competition concerns. Using a multiple-step approach for qualitative document analysis, we explore how these considerations have surfaced in the European Commission’s decisional practice through a dataset of 2.041 EU competition decision texts based on articles 101 TFEU and 102 TFEU and the EU Merger Regulation. We identify 53 decisions where DPCs have surfaced, especially in the information and communication industry, where they are more frequently subjected to commitments. In line with the evolving literature, we observe an increasingly integrationist trend as these considerations surface more frequently, particularly since the adoption of the General Data Protection Regulation in 2016 and the Digital Markets Act proposal in 2020. We also find a pattern where data protection provisions are included in commitments as a ‘tick-the-box’ exercise. Several influential alleviations of competition concerns suggest that the Commission is more comfortable using data protection to approve transactions unconditionally rather than as a substantive argument for commitments. We conclude by making a case for a more collaborative approach based on the European Court of Justice’s recent Meta Platforms (2023) judgment. Data protection should be considered in competition law assessments if its normative contribution is required. Such a stance would simply align with the internal logic of competition law without unlawfully expanding its material scope.