🤖 AI Summary
This paper addresses the theoretical gap in characterizing investor heterogeneity in data investment capability within the data economy. Method: Departing from the representative-agent paradigm, it constructs the first analytically tractable heterogeneous-agent model, endogenizing data investment capability within agents’ utility functions and dynamic investment decisions. Contribution/Results: The model demonstrates how capability disparities systematically generate asymmetric growth in investment scale, productivity gains, and technological progress, while exacerbating financing frictions and economic inequality. Its core theoretical innovation is the formal identification of “data investment capability” as a key structural determinant of data factor allocation and economic divergence. This provides a rigorous foundation for designing data property rights regimes, tiered incentive mechanisms, and inclusive data governance frameworks—advancing both theoretical understanding and policy-relevant analysis of data-driven economic development.
📝 Abstract
In this short paper, we define the investment ability of data investors in the data economy and its heterogeneity. We further construct an analytical heterogeneous agent model to demonstrate that differences in data investment ability lead to divergent economic results for data investors. The analytical results prove that: Investors with higher data investment ability can obtain greater utility through data investment, and thus have stronger incentives to invest in a larger scale of data to achieve higher productivity, technological progress, and experience lower financial frictions. We aim to propose a prerequisite theory that extends the analytical framework of the data economy from the currently prevalent representative agent model to a heterogeneous agent model.