지방교육청의 재정운용 유형화 연구

Abstract

There are growing concerns about efficient fiscal management and expenditure structure due to the decline of the school-age population, the expansion of educational autonomy, and the increase of block grant in education finance. The local education financial analysis system has been developed to fulfill fiscal responsibility and evaluate the efficiency and performance of fiscal management, but research on the operational performance and development potential of this system is insufficient. This study analyzed the financial soundness and financial efficiency index of the local school district based on the financial index of the local education finance analysis system through cluster analysis, a machine learning unsupervised learning approach. A result of the analysis reveals that heterogeneous clustering by financial indicators of local education offices was found, and this offers implications on how policy can be improved such as simplification of financial analysis indicators and data-based decision-making was presented.