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1. The competitive relationship between cloud computing and generative AI

Author:
Christophe Carugati
Publication Date:
12-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Cloud computing providers and generative artificial intelligence (GenAI) providers nurture a close, interdependent relationship: GenAI providers need cloud providers to train, run and deploy their GenAI solutions, while cloud providers see GenAI providers as a business driver to grow their market shares in cloud and related markets, such as productivity software or search engines. The cloud/GenAI relationship takes various forms, including exclusive and strategic partnerships, especially between large cloud providers and GenAI providers across all parts of the cloud market, including infrastructure, platforms and software. Competition benefits and risks are likely to result from the relationships. Competition benefits arise from increased competition and innovation in the cloud and GenAI sectors. Risks relate to potential concentrations arising from the partnerships between cloud and GenAI providers, and from anticompetitive practices, including discrimination in the supply of IT equipment by dominant IT providers, interoperability obstacles to switching, use of business-user data, self-preferencing of cloud services over third parties, tying and pure bundling. Merger control and antitrust laws can address some of the competition risks, while laws, including the European Union’s Digital Markets Act and Data Act, can deal with competition issues in digital markets and the cloud sector. Nevertheless there are gaps. The European Commission should amend existing EU instruments, including by changing the definition of a concentration under merger control, and should specify interoperability requirements for cloud providers under the Data Act. The Commission should also closely monitor developments in and outside Europe through market investigations, including with international counterparts, and should intervene to tackle imminent competition risks using fast procedural tools, such as interim measures.
Topic:
European Union, Antitrust Law, Artificial Intelligence, Cloud Computing, and Competition
Political Geography:
Europe and Global Focus

2. The Perils of Antitrust Econometrics: Unrealistic Engel Curves, Inadequate Data, and Aggregation Bias

Author:
Gabriel A. Lozada
Publication Date:
05-2023
Content Type:
Working Paper
Institution:
Institute for New Economic Thinking (INET)
Abstract:
Some economists argue antitrust policy should be based on empirical methods used by the Industrial Organization subdiscipline of economics, but non-economists must understand that those methods contain certain highly restrictive assumptions. Those assumptions involve econometric “identification,” and treating aggregate demand as if it were generated by a representative consumer (Muellbauer’s “generalized linear” preferences). We derive new results illustrating how restrictive the representative consumer assumption is; we explain aggregation bias in Almost Ideal Demand System models; and we show that data limitations make it even harder to justify economists’ restricting aggregate demands as one would the demand of a single individual.
Topic:
Economics, Antitrust Law, Data, and Econometrics
Political Geography:
Global Focus

3. An Economic Defense of Multiple Antitrust Goals: Reversing Income Inequality and Promoting Political Democracy

Author:
Mark Glick
Publication Date:
03-2022
Content Type:
Working Paper
Institution:
Institute for New Economic Thinking (INET)
Abstract:
Two recent papers by prominent antitrust scholars argue that a revived antitrust movement can help reverse the dramatic rise in economic inequality and the erosion of political democracy in the United States. Both papers rely on the legislative history of the key antitrust statutes to support their case. Not surprisingly, their recommendations have been met with alarm in some quarters and with skepticism in others. Such proposals by antitrust reformers are often contrasted with the Consumer Welfare Standard that pervades antitrust policy today. The Consumer Welfare Standard suffers from several defects: (1) It employs a narrow, unworkable measure of welfare; (2) It excludes important sources of welfare based on the assumption that antitrust seeks only to maximize wealth; (3) It assumes a constant and equal individual marginal utility of money; and (4) It is often combined with extraneous ideological goals. Even with these defects, however, if applied consistent with its theoretical underpinnings, the consideration of the transfer of labor rents resulting from a merger or dominant firm conduct is supported by the Consumer Welfare Standard. Moreover, even when only consumers (and not producers) are deemed relevant, the welfare of labor still should consistently be considered part of consumer welfare. In contrast, fostering political democracy—a prominent traditional antitrust goal that was jettisoned by the Chicago School—falls outside the Consumer Welfare Standard in any of its constructs. To undergird such important broader goals requires that the Consumer Welfare Standard be replaced with the General Welfare Standard. The General Welfare Standard consists of modern welfare economics modified to accommodate objective analyses of human welfare and purged of inconsistencies.
Topic:
Economics, Democracy, Income Inequality, and Antitrust Law
Political Geography:
Global Focus

4. Digital platforms and antitrust

Author:
Geoffrey Parker, Georgios Petropoulos, and Marshall Van Alstyne
Publication Date:
11-2020
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Digital platforms are at the heart of online economic activity, connecting multi-sided markets of producers and consumers of various goods and services. Their market power and their privileged ecosystem positions raise concerns that they may engage in anti-competitive practices that reduce innovation and consumer welfare. This paper deals with the role of market competition and regulation in addressing these concerns. Traditional (ex-post) antitrust intervention will be less effective in markets driven by network effects unless it is combined with a proper (ex-ante) regulatory framework. Antitrust tools should focus on value creation and its distribution before focusing on competition. The scope of regulatory intervention should satisfy three criteria: i) value creation from operation of the platforms does not decrease due to the policy intervention; in particular, interventions should not reduce network effects; ii) allocative efficiency is based on distributing the value created in a fair way among market participants e.g. use of the Shapley Value. Fair and transparent rules must govern the platform ecosystem; iii) dynamic efficiency and competition ensure that incentives for market misconduct and anticompetitive strategies such as artificial entry barriers are eliminated. Market interventions that target a firm’s market power should ideally retain value creation while also encouraging small firm entry and innovation. Data has a central role in online markets. Value creation is reinforced through a recursive a data capture and data deployment feedback loop which is enabled by machine learning technologies. A regulatory intervention that facilitates data sharing mechanisms, such that data will not only confer value to market leaders but also to their competitors to the benefit of consumers, is crucial for creating more competitive and innovative digital markets.
Topic:
Antitrust Law, Innovation, Strategic Competition, and Digital Finance
Political Geography:
Global Focus