IMF-使成本会计数据为公共财政管理服务（英）

Making Cost Accounting Data Work for Public Financial Management Lorena Rivero del Paso, Chloe Cho, and Ramon Narvaez Terron WP/25/159 IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. 2025 AUG * The authors would like to thank Alejandro Platas López for his valuable contribution to developing the machine learning model, aswell as for his sharp comments and additions to Section IV.2 and the annexes related to machine learning. Special thanks arealso due to Massimo Mastruzzi at the World Bank for contributing the BOOST dataset, which served as the basis for the budget credibility analysis in Section III.1. The authors further extend their gratitude to Cigdem Aslan and Sailendra Pattanayak for their meticulous review and Alok Verma for his thoughtful and constructive feedback. © 2025 International Monetary Fund WP/25/159IMF Working Paper Fiscal Affairs Department Making Cost Accounting Data Work for Public Financial Management Prepared by Lorena Rivero del Paso, Chloe Cho and Ramon Narvaez Terron* Authorized for distribution by Katherine Baer August 2025 IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management. ABSTRACT: This paper examines the role of cost accounting in public financial management, focusing on budget credibility, performance-based budgeting, public procurement, and corruption detection. Despite demonstrated benefits, cost accounting remains underutilized in the public sector due to implementation constraints. The working paper proposes the adoption of automated cost accounting systems to streamline processes, reduce operational costs, and support complex data analyses. It further emphasizes the need for interoperability between government financial systems and administrative records to enhance the granularity of costing indicators. The paper also explores machine learning as a method to support budgetary decision-making with cost accounting data. JEL Classification Numbers: H83, C80, C81, H11, H61 Keywords: Cost accounting; Budget credibility; Performance budgeting; Procurement; Interoperability; Machine learning; Anomaly detection; Automation; Digital transformation; Digitalization; GovTech; Financial Management Information Systems Author’s E-Mail Address: lriverodelpaso@imf.org; ccho@imf.org; ramon.narvaez.terron@gmail.com WORKING PAPERS Making Cost Accounting Data Work for Public Financial Management Prepared by Lorena Rivero del Paso, Chloe Cho, and Ramon Narvaez Terron IMF WORKING PAPERS Making Cost Accounting Data Work for Public Financial Management