This paper introduces a newly developed model that examines the interplay between trade, growth, and digital data, emphasizing data’s dual role as both a driver of growth and a source of privacy concerns. Departing from existing trade and growth models that have largely overlooked digital data’s unique characteristics, this paper provides the first comprehensive analysis of how data influences growth through data flows and knowledge diffusion, while simultaneously introducing associated privacy trade-offs.

A key novelty of this model lies in its clear distinction between digital data and traditional “ideas.” Both concepts share the characteristics of non-rivalry and stocklike accumulation, meaning they are cumulative and can be used by multiple entities with negligible additional cost. However, ideas are generally understood to produce only positive externalities, whereas digital data uniquely generates both positive and negative externalities simultaneously, including privacy and cybersecurity concerns for consumers.

The model is built within a dynamic general equilibrium framework that incorporates international trade and endogenous technological change, extending the work of Rivera-Batiz and Romer (1991) by integrating the evolution of digital data. Consumption activities, both domestic and a portion of foreign consumption, actively contribute to a country’s evolving data stock. This generated data then acts as a negative externality in the utility function of privacy-conscious consumers, reducing their welfare, even as it serves as a primary input for the R&D sector, fueling the growth engine.

Key findings from this new model highlight significant impacts: First, (economic growth) the model shows that unrestricted cross-border data flows are a significant stimulant for economic growth. This positive effect is further magnified by stronger knowledge spillovers and an increased number of trading partners. Conversely, stricter restrictions on data flows directly impede economic growth. The paper notes that trade liberalization alone, without the diffusion of ideas or data flows, only generates a level effect and does not affect long-term economic growth.

Second, (trade-off with individual welfare) another central finding is the inherent trade-off between economic growth and individual welfare. While open data flows promote economic expansion, they simultaneously intensify privacy concerns, leading to a reduction in individual welfare. This conflict is particularly pronounced in scenarios with limited or inefficient knowledge diffusion. Conversely, the model indicates that stricter data regulations, while hindering growth, can enhance individual welfare by mitigating these privacy risks. To navigate the identified trade-off between growth and privacy, the paper advocates against data localization and strongly supports the implementation of deep digital trade agreements. These agreements are proposed as crucial mechanisms to facilitate freer data flows and knowledge sharing, thereby mitigating the inherent conflict and unlocking the full potential of the digital economy.