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Auditors and early signals of financial distress in local governments

Author

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  • Sandra Cohen
  • Antonella Costanzo
  • Francesca Manes-Rossi

Abstract

Purpose - This study aims to analyze whether and how a set of financial ratios calculated on the basis of financial statement information would allow auditors of Italian local governments (LGs) to get an indication of LGs’ financial distress risk and, hence, to support politicians and managers in promptly detecting financial distress. Design/methodology/approach - A model comprising a set of financial indicators that would distinguish distressed from not distressed LGs through a logistic regression approach has been estimated and applied to Italian LGs. The model is built on the basis of information pertaining to 44 distressed and 53 not distressed LGs for up to five years prior to bankruptcy and covers the period 2003-2012. Findings - The model reveals that the percentage of personnel expenses over revenues, the turnover ratio of short-term liabilities over current revenues and the reliance on subsidies (calculated as subsidies per capita) are factors discriminating non-distressed LGs from the distressed ones. Practical implications - The model could have political and practical implications. The possible use of this model as a complementary tool in auditing activities might be helpful for auditors in detecting financial distress promptly, thus potentially enabling politicians and managers to search for different ways to manage public resources to avoid the detrimental consequences related to the declaration of distress. Originality/value - This model, contrary to existing models that use accrual accounting data, is applicable to LGs that adopt a modified cash accounting basis.

Suggested Citation

  • Sandra Cohen & Antonella Costanzo & Francesca Manes-Rossi, 2017. "Auditors and early signals of financial distress in local governments," Managerial Auditing Journal, Emerald Group Publishing Limited, vol. 32(3), pages 234-250, March.
  • Handle: RePEc:eme:majpps:maj-05-2016-1371
    DOI: 10.1108/MAJ-05-2016-1371
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    Citations

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    Cited by:

    1. Dionisio Buendía-Carrillo & Juan Lara-Rubio & Andrés Navarro-Galera & María Elena Gómez-Miranda, 2020. "The impact of population size on the risk of local government default," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 27(5), pages 1264-1286, October.
    2. Nora Muñoz-Izquierdo & María-del-Mar Camacho-Miñano & María-Jesús Segovia-Vargas & David Pascual-Ezama, 2019. "Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence," IJFS, MDPI, vol. 7(2), pages 1-23, April.
    3. Rizky Aji Shiddiqy & Nurkholis & Yeney Widya Prihatiningtias, 2022. "The prediction of financial distress probability in East Java province governments," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(1), pages 152-160, January.
    4. Youssef Zizi & Amine Jamali-Alaoui & Badreddine El Goumi & Mohamed Oudgou & Abdeslam El Moudden, 2021. "An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression," Risks, MDPI, vol. 9(11), pages 1-24, November.
    5. Majidah, 2018. "Auditor Retention: Auditor and Auditee Factors," GATR Journals jfbr145, Global Academy of Training and Research (GATR) Enterprise.
    6. Dody Hapsoro & Tiara Rani Santoso, 2018. "Does Audit Quality Mediate the Effect of Auditor Tenure, Abnormal Audit Fee and Auditor's Reputation on Giving Going Concern Opinion?," International Journal of Economics and Financial Issues, Econjournals, vol. 8(1), pages 143-152.
    7. Emanuele Padovani & Luca Rescigno & Jacopo Ceccatelli, 2018. "Municipal Bond Debt and Sustainability in a Non-Mature Financial Market: The Case of Italy," Sustainability, MDPI, vol. 10(9), pages 1-25, September.

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