Recently, the Ministry of Education officially announced the winners of the Ninth Higher Education Scientific Research Outstanding Achievement Award (Humanities and Social Sciences). The research team led by Professor Wang Min from Yunnan University of Finance and Economics received the third prize in the Consulting Service Report category for their work titled “Risk Analysis of Sustainable Operation of Local Finances”. The main contributors to this achievement include Wang Min, Fang Zhu, Fu Runmin, Wang Weikun, Xiang Zhongxin, Sun Dahai, Huang Lijun, and Yuan Jiao, with Yunnan University of Finance and Economics listed as the primary unit of accomplishment.

The Higher Education Scientific Research Outstanding Achievement Award (Humanities and Social Sciences) aims to recognize and reward the outstanding achievements of philosophy and social science workers in higher education institutions. Established in 1995, the awards are evaluated every three to four years, and this marks the ninth edition. The evaluation for this round covered achievements from January 1, 2018, to December 31, 2021, with a total of 1,496 achievements recognized. This includes 1,196 awards for books and papers (including 118 first prizes, 513 second prizes, and 565 third prizes), 76 awards for consulting service reports (including 7 first prizes, 32 second prizes, and 37 third prizes), 21 awards for popular science books, and 203 awards for young scholars.

Professor Wang Min’s awarded work, “Risk Analysis of Sustainable Operation of Local Finances”, systematically analyzes the common manifestations of distorted financial data at the local level in China. It reveals the causes and related impacts of financial data distortion, presenting typical cases from various regions across the country. The study employs methods such as historical verification and data correlation analysis to quantitatively measure the extent of financial data distortion at both national and provincial levels, categorizing and grading the degree of distortion in financial data across China. The research further outlines the spatial distribution characteristics of financial data distortion in the country.

On an operational level, the study dissects the underlying causes of financial data distortion and proposes policy measures to achieve sustainable operation of local finances. This work holds significant importance for eliminating the dynamics that accumulate risks to financial sustainability and promoting stable and healthy economic and social development.