运用风险管理审计公共债务

IF 1.1 4区 管理学 Q4 MANAGEMENT Informs Journal on Applied Analytics Pub Date : 2023-05-22 DOI:10.1287/inte.2023.1165
A. Consiglio, Akis Kikas, Odysseas P. Michaelides, S. Zenios
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引用次数: 1

摘要

塞浦路斯共和国审计署对该国的公共债务进行了首次审计,寻求两个关键问题的答案。政府债务是否可持续?债务融资在确保最低成本和可接受风险方面是否高效有效?议会对审计结果进行了讨论,可能对公共财政产生重大影响。然而,公共债务管理相当复杂,最高审计机构国际组织建议,在进行审计时,充分的技术知识是必不可少的,包括对不确定的宏观经济、融资条件和政府财政立场的了解。我们使用基于情景树的风险管理模型进行审计。该模型确定了最优债务融资策略,以基准国家公共债务管理办公室的绩效并回答审计问题。我们还采用了一个综合评估模型来检查气候变化带来的风险。审计长在财政部长在场的情况下向议会审计委员会提出了调查结果,预计他的建议将对该国的债务业务产生重大影响。历史:本文被审稿。经费:这项工作得到塞浦路斯共和国审计署的支助。A. Consiglio部分由NRRP-GRINS [Grant PE00000018]资助。
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Auditing Public Debt Using Risk Management
The Audit Office of the Republic of Cyprus conducted the first-ever audit of the country’s public debt, seeking answers to two key questions. Is government debt sustainable, and is debt financing efficient and effective in securing the lowest cost with acceptable risks? The audit’s findings were discussed by the parliament and can have significant ramifications for public finance. However, public debt management is quite complex, and the International Organization of Supreme Audit Institutions suggests that sufficient technical knowledge is essential in undertaking an audit, including an understanding of the uncertain macroeconomy, financing conditions, and government fiscal stance. We use a risk management model based on scenario trees in conducting the audit. The model determines optimal debt financing strategies to benchmark the performance of the country’s Public Debt Management Office and answer the audit questions. We also incorporate an integrated assessment model to examine the risks from climate change. The auditor general presented the findings to the Parliamentary Audit Committee in the presence of the Minister of Finance, and his recommendations are expected to have a significant impact on the debt operations of the country. History: This paper was refereed. Funding: This work was supported by the Auditor General Office of the Republic of Cyprus. A. Consiglio was partially funded by NRRP-GRINS [Grant PE00000018].
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