The Economics of Data: Implications for the Data-Driven Economy

Abstract

The economics of the emerging data-driven economy can be situated in theoretical models of endogenous growth which introduce research and development, human capital formation, and Schumpeterian creative destruction as drivers of economic growth, together with positive externalities related to local knowledge spillovers. This theoretical framework allows for differential rates of growth in different countries based on their policies to support innovation and for innovation to generate market power and monopoly rents. However, the data-driven economy has several structural features that make it at least a special case of the general endogenous growth model, if not a new model altogether. These include pervasive information asymmetry, the industrialization of learning through artificial intelligence, the proliferation of superstar firms due to "winner take most" market dynamics, new forms of trade and exchange, the value of which is not captured by traditional economic accounting systems, and systemic risks due to vulnerabilities in the information infrastructure. This note explores these issues.