Competition Problems and Governance of Non-personal Agricultural Machine Data: Comparing Voluntary Initiatives in the US and EU

Abstract

The arrival of digital data in agriculture opens the possibility to realise productivity gains
through precision farming. It also raises questions about the distribution of these gains
between farmers and agricultural service providers. Farmers’ control of the data is often
perceived as a means to appropriate a larger share of these gains. We show how data-driven
agricultural business models lock farm data into machines and devices that reduce
competition in downstream agricultural services markets. Personal data protection regulation
is not applicable to non-personal agricultural machine data. Voluntary data charters in the
EU and US emulate GDPR-like principles to give farmers more control over their data but do
not really change market-based outcomes due to their legal design. Third-party platforms are
a necessary intermediary because farmers cannot achieve the benefits from applications that
depend on economies of scale and scope in data aggregation. The low marginal value of
individual farm data in such applications puts farmers in a weak bargaining position. Neutral
intermediaries that are not vertically integrated into agricultural machines, inputs or services
may circumvent monopolistic data lock-ins provided they can access the data. Unless they
find a way to generate and monetise economies of scale and scope with their data, their
business model may not be sustainable. Regulatory intervention that facilitates portability and
interoperability might be useful for farmers to overcome data lock-ins, but designing data
access rights is a complicated issue as many parties contribute data to the production process
and may claim access rights. Minor changes in who gets access to which data under which
conditions may have significant effects on stakeholders. We conclude that digital agriculture
still has some way to go to reach equitable and efficient solutions to data access rights.
Similar situations are likely to occur in other industries that rely on non-personal machine
data.

Keywords: smart farming, agricultural data, data governance, non-personal machine data, data access rights, competition policy

JEL Classification: K21, K2