This article concerns itself with fees that Apple and Google might charge to business users in their respective mobile ecosystems. We lay out the economic analysis behind the goals of the DMA—contestability and fairness—as they apply to third-party app store access fees. We focus on the access fees for alternatives to the Apple App Store, as this has become contentious in the early enforcement of the DMA. Much of our analysis, however, also applies also to Google and/or any other designated gatekeeper.
This paper makes several foundational points. First, the DMA permits Apple to charge a fixed fee to review the security of third-party app stores or apps distributed through and operated on Apple’s operating system ('Review Fee'). The level of such a fee should be related to the cost of the review function for the reasons we describe below. Generally, because the cost of conducting a review is independent of the revenue an app generates, so too should be the Review Fee collected to cover that cost.
Second, there are many fees that apply to different elements of the Apple ecosystem (e.g., the cost of a handset, advertising in the app store, etc.) that are unaffected by the DMA. However, we show that one element of this complex fee structure—the fees Apple places on third-party app stores for the right to reside on iOS ('Access Fee')—is constrained to zero under the DMA given current knowledge and institutions. We explain why believe that setting this one fee to zero is required for compliance with the DMA and why this restriction is proportionate. In brief, because third-party app stores are potential competitors to Apple’s ecosystem, non-zero Access Fees would block contestability, making them very harmful unless very particular conditions hold. Meanwhile, any financial harm to the gatekeeper that might result from setting this fee at zero is limited because of the freedom the gatekeeper has to monetise its ecosystem in other ways that are compliant with European law, including by selling devices, advertising, and other services.
Third, fees imposed on one category of business users may have implications in respect of fairness and contestability for a wholly separate category of business users. The regulator must remain alert for these ‘adjacent’ anticompetitive effects. Of particular relevance here, a fee Apple imposes on app developers only if those developers distribute through a rival app store imposes a direct cost on those developers to be sure, but it also undermines fairness and contestability in the app store market. By punishing app developers for using an alternative distribution channel, the fee suppresses app developers’ use of those new channels, depriving the new channels both of revenue from the app developers (which is unfair) and the benefits that would accrue from network effects that would make them more attractive to end users (which also undermines contestability).
On 25 March 2024, the Commission opened an investigation against Apple in regard to its compliance with Article 5(4) DMA, the requirement to allow effective use of third-party app stores, and on 24 June 2024 the Commission opened another investigation against Apple in regards to its compliance with Article 6(4)’s obligation to provide effective use of its operative system. Our final point is that if the Commission finds non-compliance under Article 29, it can proceed to specify what Apple should do by using the procedure in Article 8(2). In particular, we recommend that the Commission use Article 8(2) to specify an Access Fee of zero to rival distribution channels, including third-party app stores, allow a positive Review Fee, and combine these with unconstrained pricing for other elements of the ecosystem such as advertising and the price of the handset (consistent with the law). Opening the app store market without delay is necessary in order to obtain the innovation and entry by business users that is the purpose of the DMA. This solution is simple and proportionate and can be supported with the materials and evidence gathered thus far.
It is theoretically possible that our proposal is the unique compliant fee structure; in other words, it is possible that there are no Access Fees Apple could impose on third-party app stores that are unrelated to its market power and increase social welfare. Any other lawful fee charged by Apple would need to advance contestability and fairness; fees for advertising or reviewing apps may fall in this category. It is beyond the scope of the current paper to prove our recommendation is the only possible solution, but we discuss the reasons why we think this is likely below.
We demonstrate how to use economic principles to inform the Commission’s determination of whether a gatekeeper’s fee structures applicable to the app and app store ecosystems comply with the DMA’s requirements. Based on analogs to the telecommunications industry, the policy community may believe a compliant Access Fee should be based on the wellknown efficient component pricing rule. We explain why this is unlikely to be a helpful pathway in the case of digital platforms, and that economic analysis supports a zero Access Fee in the case of third-party app stores.
This paper identifies a set of possible regulations that could be used both to make the search market more competitive and simultaneously ameliorate the harms flowing from Google’s current monopoly position. The purpose of this paper is to identify conceptual problems and solutions based on sound economic principles and to begin a discussion from which robust and specific policy recommendations can be drafted.
Economic thinking and analysis lie at the heart of the objectives and the design of the EU Digital Markets Act. However, the design of the DMA reflects a very deliberate—and reasonable—intention to ensure clarity, speed, administrability, and enforceability. In doing so, this procompetitive regulation omits several elements of standard competition law where economics has typically played a key role. Nonetheless, we believe that economic insights and analysis—including behavioural economic thinking—will continue to play an important role in enabling the DMA to achieve its ambitious and laudable goals, albeit in a somewhat different way.
The Commission is charged with implementing the Digital Markets Act (DMA). Based on economic and legal reasoning, this paper asks how the Commission can fulfil this challenging task effectively. We make recommendations about how the Commission might prioritize cases, design optimal internal work structures, maximize the compliance mechanism’s effectiveness, avoid reinventing at least some wheels by leaning on antitrust tools and knowledge, and leveraging the Commission’s concurrent antitrust and regulatory powers to ensure the speedy and effective resolution of current and future investigations.
The ability to make accurate predictions relating to consumer preferences is a key factor of a digital firm’s success. Examples include targeted advertisements and, more broadly, business models relying on capturing consumers’ attention. The prediction technologies used to learn consumer preferences rely on consumer generated data. Despite the importance of data-driven technologies, there is a lack of knowledge about the precise role that data-scale plays for prediction accuracy. From a policy perspective, a better understanding about the role of data is needed to assess the risks that “big data” might pose for competition. This article highlights potential complementarities in algorithmic learning, which suggest data-scale advantages might be substantial. We analyze our hypothesis using search engine data from Yahoo! and provide evidence consistent with locally increasing returns to scale. The ability to make accurate predictions relating to consumer preferences is a key factor of a digital firm’s success. Examples include targeted advertisements and, more broadly, business models relying on capturing consumers’ attention. The prediction technologies used to learn consumer preferences rely on consumer generated data. Despite the importance of data-driven technologies, there is a lack of knowledge about the precise role that data-scale plays for prediction accuracy. From a policy perspective, a better understanding about the role of data is needed to assess the risks that “big data” might pose for competition. This article highlights potential complementarities in algorithmic learning, which suggest data-scale advantages might be substantial. We analyze our hypothesis using search engine data from Yahoo! and provide evidence consistent with locally increasing returns to scale..