IMF Working Papers

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Format: Chicago

Lorena Rivero del Paso, Chloe Cho, and Ramon Narvaez Terron. "Making Cost Data Work for Public Financial Management", IMF Working Papers 2025, 159 (2025), accessed 1/23/2026, https://doi.org/10.5089/9798229021470.001

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Disclaimer: 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.

Summary

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.

Subject: Budget planning and preparation, Expenditure, Fiscal accounting and reporting, Performance-based budgeting, Public financial management (PFM)

Keywords: Anomaly detection, Automation, Budget credibility, Budget planning and preparation, Cost accounting, cost accounting data, cost data, Digital transformation, Digitalization, Financial Management Information Systems, Fiscal accounting and reporting, Global, GovTech, Interoperability, Machine learning, machine learning algorithm, Performance budgeting, Performance-based budgeting, Procurement