Private Funding of “Free” Data: A Theoretical Framework

ABSTRACT One might think that the private value of data equals the net present value of data sales revenue. In fact, even data with zero sales revenue can still have substantial private value. This paper develops a theoretical framework in which data can either be sold to users or distributed “free” by the owner of a complementary capital asset. For example, the results from a survey of tourists can either be sold to travel agencies or distributed free by a hotel whose rooms are complementary to the survey results. This paper then solves that theoretical framework, calculates data values, and identifies parameter regions for which sold data are less valuable than free data. Free data are particularly valuable when data are strongly complementary with capital, when data are complementary to other data (Coyle and Li 2021), or when piracy reduces data sales revenue. This paper illustrates the importance of free data with a back‐of‐the‐envelope calculation for the United States. To start out, the paper reviews three previous case studies which together studied $1.4 trillion of free data creation in 2017 (Soloveichik 2023; Soloveichik 2024a). This paper then uses those case studies, existing input–output tables, and occupational employment to extrapolate that total private creation of free data in the United States was $6.9 trillion in 2017. In that same year, including free data in the economic statistics raises measured gross domestic product by $4 trillion, raises measured household production by $0.6 trillion of previously untracked data creation, and raises measured consumer durable services by $5.1 trillion of imputed services from free data owned by consumers.