Research on the Optimization Path of Tax System Structure Based on Demographic Changes

发布人:戴宝莹 发布日期:2026-04-16阅读次数:5

Speaker:Xie E, Professor, Shandong University

Host:Nie Haifeng, Professor, Lingnan College

Time and Date:10:00, May 7, 2026 (Thursday)

Venue:Wang Dao Han Conference Room (101), Lingnan Hall

Language:Chinese

 

Abstract:

With the profound changes in China's demographic structure, particularly the accelerated aging of the population, the existing tax system faces new challenges. The rising dependency ratio, shifts in urban-rural population structures, and regional economic disparities impose higher demands on the design and implementation of tax policies. Against this backdrop, this paper examines the characteristics and historical evolution of China's tax system and demographic structure, analyzes their interrelationships, draws lessons from international experiences, and explores the construction of optimal tax theory in the context of demographic changes.  

 

Profile:

 

 

Xie E, a second-level professor and doctoral supervisor, is a national leading talent. His research has been published in journals such as Economic Research (5 articles) and Management World(2 articles), with 5 of these 7 articles published independently. He has led multiple national-level projects, including major projects of the National Natural Science Foundation of China, major projects of the National Social Science Fund of China (3 projects), key projects of the National Social Science Fund of China, general projects of the National Natural Science Foundation of China (2 projects), the National Publication Fund, and the National Excellent Doctoral Dissertation Author Special Fund. He also serves as a peer review expert for major projects of the National Social Science Fund of China, a conference review expert for the National Natural Science Foundation of China, and a conference review expert for the National Ten Thousand Talents Program for Young Top-Notch Talents and Leading Talents in Philosophy and Social Sciences.