Recently, the research by 111 Center researchers Ye Jingjing and Wang Xiaoxiao, along with their research partners (Yu Baixue, the School of Finance and Public Administration of Hubei University Economics; Fu Jiasha, Research Institute of Economics and Management, Southwestern University of Finance and Economics), titled The Taxation Governance Logic of Data Elements Circulation: Evidence Based on Housing Market Tax Administration Data, was officially published in Issue 12 of Journal of Management World in 2025, a top journal.
Abstract
This paper reveals the micro-mechanism of data, as a new production factor, exhibiting increasing marginal returns in tax governance. The study finds that the increase in housing transaction volume caused by tax incentives leads to an accumulation of data elements within tax zones, which in turn drives a continuous improvement in tax collection efficiency (taxable price/transaction price). From the perspective of data sources, the policy effect is more pronounced in zones with a higher increase in data elements (new transactions). In contrast, no significant difference in tax administration efficiency is observed in zones with a higher stock of data elements (historical transactions). Compared to the scale of data elements, the quality of internal data elements has a more pronounced effect on improving tax administration efficiency, while the impact of external data quality from third-party transactions is limited. From a temporal perspective, zones with a higher increase in data elements show a clear dynamic upward trend in tax administration efficiency, confirming the central role of continuous data updates (rather than static stock) in driving sustained improvements in tax administration efficiency. It is important to note that, since the accumulation of data elements is related to transaction frequency, the improvement in tax administration efficiency is mainly concentrated in lower-wealth housing with more frequent transactions. This could potentially lead to vertical inequities in the actual tax burden. This study provides valuable empirical evidence for the further advancement of "data-driven taxation."
About the Authors
Ye Jingjing is a professor at Zhongnan University of Economics and Law (ZUEL), a researcher at the Center for International Cooperation and Disciplinary Innovation of Income Distribution and Public Finance, and a doctoral advisor. She holds a Ph.D. from Southern Methodist University, USA. Her research focuses on tax administration and national governance, fiscal expenditure, and subsidy design. Her related work has been published in authoritative domestic and international journals such as Journal of Management World, The Journal of World Economy, China Economic Quarterly, Journal of Banking and Finance, Urban Studies, and China Economic Review. She has been selected for provincial-level talent programs and as a candidate for academic and technical leadership. She has led and participated in four major projects funded by the National Social Science Fund of China, one project funded by the National Natural Science Foundation of China, one project funded by the Ministry of Education Foundation on Humanities and Social Sciences, and more than ten other national and provincial/ministerial-level projects. Her research achievements have won several awards, including the Excellent Paper Award from the Camphor Tax Forum, the Chinese Society of Technology Economics, the Fiscal Forum, and the China Association of Labor Economics. The research results from her practical investigations have been widely reposted and reported by media outlets such as Beijing News and Xinhuanet, creating a positive social impact.
Wang Xiaoxiao is a lecturer at the School of Public Finance and Taxation, Zhongnan University of Economics and Law (ZUEL), and a researcher at the Center for International Cooperation and Disciplinary Innovation of Income Distribution and Public Finance. She holds a Ph.D. in Economics. She graduated in 2023 from the School of Economics of Peking University with a major in Fiscal Economics. Her research areas include optimal taxation theory, focusing on topics such as income distribution and the bounded rationality of taxpayers. Her research has been published in academic journals such as Economic Research Journal, Economic Perspectives, Journal of Financial Research, and Economic Science. She presided over the Youth Project of the National Natural Science Foundation of China, titled "Re-distribution Policy Optimization under the Dynamic Evolution of Income Risk: An Analysis Based on a Multi-information Friction Principal-Agent Model."