Speaker: Associate Professor Zhongwen Zhang (School of Applied Economics, Renmin University of China)

Moderator: Assistant Professor Lan Lan (Li Anmin Institute of Economics, Liaoning University)

Guest Introducer: Professor You Yu (Li Anmin Institute of Economics, Liaoning University)

Time: 9:00–10:30 AM (Beijing Time), Monday, May 11, 2026

Venue: Room 112, Economics Building, Puhe Campus, Liaoning University

Online Access: Tencent Meeting ID: 730-281-8924

Language: Chinese/English

Abstract:

Against the backdrop of rapid digital technology evolution and persistently slowing productivity growth, the "Solow Paradox" in the digital economy era has rekindled scholarly attention. Most existing total factor productivity (TFP) measurement frameworks remain based on the two-factor model of capital and labor, making it difficult to fully capture the input and output contributions of data as a factor of production. From the perspective of data capital, this paper uses Chinese provincial-level industry data from 2003 to 2020. By constructing a price index that aligns with the characteristics of data investment, it measures China’s data investment and data capital stock using the cost method and perpetual inventory method. The paper then incorporates data capital into an extended Cobb–Douglas production function to reassess TFP. Further, an extended Tobin’s Q model is used to estimate the shadow price of data investment. The findings show that China’s data capital is still in the investment accumulation stage. Including data capital in production accounting systematically raises the real TFP growth rate, indicating that traditional measurement methods significantly underestimate TFP by omitting data as a factor. This underestimation exhibits significant industry heterogeneity, with the largest correction in the services sector, followed by the digital industry, and the smallest in manufacturing. This study offers a new perspective for interpreting the Solow Paradox in the digital economy era: it may not be entirely due to technology’s failure to enhance productivity, but also linked to insufficient recognition of data capital in the existing accounting framework. The paper provides empirical evidence and policy implications for improving the data factor accounting system, broadening data capital accumulation channels, and advancing the market-based allocation of data factors.

Speaker Profile:

Zhongwen Zhang is an Associate Professor at the School of Applied Economics, Renmin University of China; Director of the Industrial Economics Department; Director of the Digital Economics Teaching and Research Office; and an Outstanding Young Scholar of Renmin University. His research focuses on industrial economics and digital economics. He has led and participated in multiple national-level projects, including those funded by the National Social Science Foundation, the National Natural Science Foundation, and national high-end think tanks. He provides decision-making advisory services to ministries and commissions including the General Office of the State Council, the Publicity Department of the CPC Central Committee, the Cyberspace Administration of China, the National Development and Reform Commission, the Ministry of Industry and Information Technology, and the National Data Bureau. He has published over 30 academic papers in leading domestic and international journals such as Management World, The World Economy, China Industrial Economics, and the Journal of the Asia Pacific Economy. Several of his research outcomes have been adopted by the National Bureau of Statistics, incorporated into official industry classification standards for the digital economy, and some have been republished by Xuexi.cn and applied to the reform of data factor statistical accounting in Shenzhen. He is a recipient of the Third Prize of China’s Emerging Scholar Award on Data Factors.