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..
As large amounts of data become available and can be communicated more easily and processed more effectively, information has come to play a central role for economic activity and welfare in our age. This essay overviews contributions to the industrial organization of information markets and nonmarkets, while attempting to maintain a balance between foundational frameworks and more recent developments. We start by reviewing mechanism-design approaches to modeling the trade of information. We then cover ratings, predictions, and recommender systems. We turn to forecasting contests, prediction markets, and other institutions designed for collecting and aggregating information from decentralized participants. Finally, we discuss science as a prototypical information nonmarket with participants who interact in a non-anonymous way to produce and disseminate information. We aim to familiarize the reader with the central notions and insights in this burgeoning literature and also point to some critical open questions that future research will have to address.
This paper is concerned with competition in digital platform markets where network effects are strong. As is widely acknowledged, these markets have an inherent tendency towards concentration, leaving consumers with little competition in the market. We explain how interoperability regulation can help stimulate competition in the market in a way that benefits consumers.
We analyze the use of the concepts of fairness and contestability in the Digital Markets Act (DMA) and propose formal definitions rooted in the economic analysis of digital markets as well as the goals of the proposed law. We discuss the implication of these concepts for innovation in digital markets.
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.
This is the sixth in a series of papers prepared by a collection of economists and policy experts in the United States, the UK, and the European Union who have studied, and are committed to the improvement of, competition in digital markets. Previous papers addressed consumer protection in online markets, regulating the market for general search services, the concepts of “fairness” and “contestability” as used in the Digital Markets Act, the use of “equitable interoperability” as a “super tool” to restore and encourage competition in online markets, and coherence between US and European approaches to digital regulation.
The advent of mobile devices and digital media platforms in the past decade represents the biggest shock to cognition in human history. Robust medical evidence is emerging that digital media platforms are addictive and, when used in excess, harmful to users’ mental health. Other types of addictive products, like tobacco and prescription drugs, are heavily regulated to protect consumers. Currently, there is no regulatory structure protecting digital media users from these harms. Antitrust enforcement and regulation that lowers entry barriers could help consumers of social media by increasing competition. Economic theory tells us that more choice in digital media will increase the likelihood that some firms will vie to offer higher-quality and safer platforms. For this reason, evaluating harm to innovation (especially safety innovation) and product variety may be particularly important in social media merger and conduct cases. Another critical element to antitrust enforcement in this space is a correct accounting of social media’s addictive qualities. Standard antitrust analysis seeks to prohibit conduct that harms consumer welfare. Economists have taught the antitrust bar that the output of a product or service is a reliable proxy for consumer welfare. However, output and welfare do not have this relationship when a product is addictive. Indeed, in social media markets, increased output is often harmful. We argue that antitrust analysis must reject the output proxy and return to a focus on consumer welfare itself in cases involving addictive social media platforms. In particular, courts should reject defenses that rely only on gross output measures without evidence that any alleged increases in output actually benefit consumers.
We study data linkages among heterogeneous firms and examine how they shape the outcome of privacy regulation. A single consumer interacts sequentially with two firms: one firm collects data on consumer behavior; the other firm leverages the data to set a quality level and a price. A data linkage benefits the consumer in equilibrium when the recipient firm is sufficiently similar to the collecting firm. We then endogenize linkage formation under various forms of privacy regulation. We show that voluntary consent requirements are beneficial to consumers in equilibrium but that bans on discriminatory price and quality offers are harmful.
We quantify the distortionary effects of nexus tax laws on Amazon’s distribution network investments between 1999 and 2018. We highlight the role of two features of the expansion of Amazon’s network: densification of the network of distribution facilities and vertical integration into package sortation. Densification results in a reduction in the cost of shipping orders, but comes at the expense of higher facility operating costs in more expensive areas and lower scale economies of processing shipments. Nexus laws furthermore generate additional sales tax liabilities as the network grows. Combining data on household spending across online and offline retailers with detailed data on Amazon’s distribution network, we quantify these trade-offs through a static model of demand and a dynamic model of investment. Our results suggest that Amazon’s expansion led to significant shipping cost savings and facilitated the realization of aggregate economies of scale. We find that abolishing nexus tax laws in favor of a non-discriminatory tax policy would induce the company to decentralize its network, lowering its shipping costs. Non-discriminatory taxation would also entail lower revenue, however, as tax-inclusive prices would rise, resulting in a fall in profit overall. This drop and the decline in consumer welfare from higher taxes together fall short of the increases in tax revenue and rival profit, suggesting that the abolishment of nexus laws would lead to an increase in total welfare.