Generalized Digital Intelligence Economy Theory

Speaker：Xie Danxia, Tenured Associate Professor, Tsinghua University

Host：Yang Yang, Associate Professor, Lingnan College

Time and Date：14:30, March 20, 2026 (Friday)

Venue：C.S.LAM Conference Room (103), Lingnan Hall

Language：Chinese

Abstract：

The speaker's series of research attempts to provide a workhorse model for the digital intelligence economy. The operation of the digital economy and AI economy requires close collaboration of many core elements. As a production factor, data does not generate value alone but is closely related to the allocation of resources such as computing power and storage.This paper develops a general equilibrium model of the digital economy, incorporating data, computing power, storage, and algorithms into a unified analytical framework, constructing a more universally explanatory theoretical framework for the digital economy. In the general equilibrium model, the accumulation of data is constrained by data storage devices, and the efficiency of data utilization is affected by computing power. When data is non-competitively shared and utilized across all production and innovation sectors, the endogenous data volume, storage, total computing power, and computing power allocation within the economy mutually influence each other, forming a market competition equilibrium. The study finds that market competition equilibrium may encounter potential issues such as excessive computing power investment, unreasonable computing power allocation, and insufficient innovation. Under different market conditions, market competition equilibrium may result in insufficient data sharing or data abuse. Based on the benchmark model, this paper conducts model extensions from aspects such as data resale, data synthesis, computing power and privacy, production and innovation digitalization, algorithmic innovation open-source, dynamic accumulation of storage and computing power, and energy. Finally, this paper proposes a series of policy recommendations from multiple dimensions, including improving the data governance system and optimizing computing power subsidy mechanisms, aiming to further unleash the potential of digital economy development and provide support for building an efficient, innovative, and coordinated sustainable digital economy ecosystem. Ultimately, this paper attempts to establish a "Generalized Digital Intelligence Economy Theory" encompassing data, storage, computing power, algorithms, and energy.

Profile:

Xie Danxia is a PhD supervisor and Tenured Associate Professor at the Institute of Economics, School of Social Sciences, Tsinghua University. He is also the Deputy Director of the World Artificial Consciousness Association and Director of the Industry-Urban Integration Research Center of Zhejiang Yangtze River Delta Research Institute. His research interests include digital economy, AI economy, macroeconomics, regional economics, law and economics, labor and health economics, finance, and international and development economics. His papers have been published in top domestic and international journals such as PNAS, Management Science, Economic Research Journal, and Management World.