A Review of Public Expenditure Efficiency Evaluation Using Data Envelopment Analysis: A Case Study of Research Expenditure Efficiency in Iranian Industrial Universities

Authors
1 PhD student, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
2 Professor, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
Abstract
The efficiency of government expenditures is the ability to generate greater outputs using specified resources. Due to constraints on government resources, improving public expenditure efficiency has become crucial for reducing public budget consumption. Calculating the efficiency of public expenditures and implementing performance-based budgeting has led to the use of mathematical methods to optimize and assess government organizations' efficiency. One effective approach is Data Envelopment Analysis , a technique that evaluates the relative efficiency of decision-making units by comparing inputs and outputs. When combined with other econometric or statistical methods, DEA offers a broader perspective on how units and organizations perform in terms of budget utilization. Furthermore, comparing similar units highlights the strengths and weaknesses of each system, guiding decision-makers.
The objective of this study is to evaluate the challenges in calculating public expenditure efficiency using DEA, by reviewing studies comparing the performance of various governments in international comparisons. The review highlights the methodological challenges, indicator selection, and decision-making unit selection.
A case study evaluates the efficiency of public expenditures in research and development for 9 industrial universities in Iran, across four scenarios. Two DEA models are employed: the weighted sum model and the multi-layer weighted sum model. The indicators include university research budgets and output performance metrics for research, such as the number of articles, books, theses, and patents. The results show that university efficiency varies depending on the inputs and outputs considered. Finally, policy recommendations are provided for applying these models in higher education.

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Articles in Press, Accepted Manuscript
Available Online from 04 January 2026

  • Receive Date 05 August 2025
  • Revise Date 20 November 2025
  • Accept Date 04 January 2026
  • Publish Date 04 January 2026