Abstract

This paper starts with some basic economic characteristics of data that distinguish them from ordinary goods and services, including non-excludability and non-rivalry, economies of scope in data re-use and aggregation, the social value of data and their role in generating network effects. It explores how these characteristics contribute to the emergence of large digital platforms that generate a combination of positive and negative welfare effects for society, including data-driven network effects. It distinguishes between lexicographic and probabilistic data-driven matching in networks. Both may lead to market “tipping”. It emphasizes the social value of data and the positive and negative social externalities that may come with this. Platforms are necessary intermediaries to generate the social welfare or network externalities from data. However, the economic role of data-driven platforms is ambivalent. On the one hand, platforms enable society to benefit from positive externalities in data collection via economies of scale and scope in data aggregation of transactions and interactions across users, both firms and consumers. That gives them a privileged market overview that none of the individual users has. Platforms can use this information asymmetry to facilitate interaction and increase welfare for users. These data externalities attract users to the platform. On the other hand, data-driven network effects may result in monopolistic market power of platforms which they can use for their own benefit, at the expense of users. Any policy intervention that seeks to address the market power of online platforms requires careful balancing between these two poles. Finally, the paper briefly discusses ecosystems that leverage data to coordinate interactions between different platforms.

Highlights

  • Data are the driving force behind the digital economy, including the large online platforms that have emerged as key players in the digital economy

  • This paper starts with some basic economic characteristics of data that distinguish them from ordinary goods and services, including non-excludability and non-rivalry, economies of scope in data re-use and aggregation, the social value of data and their role in generating network effects

  • This paper presents some basic economic c ha rac teristics of data that distinguish them from ordinary goods and services

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Summary

Introduction

Data are the driving force behind the digital economy, including the large online platforms that have emerged as key players in the digital economy. This paper presents some basic economic c ha rac teristics of data that distinguish them from ordinary goods and services It explores how these characteristics contribu te to the emergence of large digital platforms that generate a combination of positive a nd n eg ative welfare effects for society. Th is o ccu rs when the incentives of private firms and/or consumers make them behave in ways that diminish overall social welfare This may justify regulatory intervention in data markets and the imposition of remedies to a dd res s these failures. In line with the European Commission’s “Better Regulation Guidelines”[1] we follow a b road er a ppro ach to possible regulatory intervention in data and data-driven services markets It include s m onop olistic m arket failures that are usually handled by competition law but extends to other sources of market failures s uch as externalities, asymmetric information and missing markets because of high transaction costs.

The economic characteristics of data
Data collection has an economic cost
The value of data depends on their use
Excludability and monopolistic data trade
Data are not a homogenous product
Non-rivalry and economies of scope in data re-use
Economies of scope in data aggregation
The social value of data
Platforms and data-driven network effects
Platforms in the digital economy
The role of data in platforms
Market failures in platforms
Negative information externalities
Negative effects from asymmetric information
Missing markets because of high transaction costs and risks
Transaction costs in personal data services markets
Transaction costs and lack of transparency in advertising markets
Data-driven ecosystems
Findings
Concluding remarks
Full Text
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