Utilization of Artificial Intelligence in fiscal stress forecasting: evidence for brazilian municipalities
DOI:
https://doi.org/10.14392/asaa.2024170307Keywords:
Governmental Financial Condition, Fiscal condition, Subnational Entities, Artificial Intelligence, Random ForestAbstract
Objective: The study applied Trussel and Patrick’s (2018) model, along with factors from Groves et al. (1981) Groves and Valente (2003), to forecast fiscal stress in Minas Gerais municipalities from 2016 to 2020, considering the Brazilian context.
Method: The Random Forest (RF) model, a machine learning technique from Decision Trees family, was used to predict fiscal stress in municipalities in Minas Gerais, which the choice of this model was due to its recent success in prediction problems, which motivated its application in the present study.
Results: The model showed an overall average accuracy of 68.2%. After defining some cut-off points, it was possible to achieve up to 85% early precision. The model demonstrated greater effectiveness in predicting the occurrence of fiscal stress than in its absence. However, the results varied significantly between different periods analyzed. It is also noteworthy that the most important variables are related to the liquidity category, while organizational and environmental variable factors demonstrated low importance. Such results corroborate and contradict some authors, as well as exceed some articles.
Contributions: The article brings two innovations, namely the use of Artificial Intelligence (AI) in research on Governmental Financial Condition in Brazil and the prediction of fiscal stress in Brazilian municipalities.
Downloads
References
Aarsaether, N. (1990). Organizational and Spatial Determinants of Fiscal Stress: An Analysis of Norwegian Municipalities. Public Budgeting & Finance, 10(1), 55-66. https://doi.org/10.1111/1540-5850.00850 DOI: https://doi.org/10.1111/1540-5850.00850
Altman, E. I., Danovi, A., & Falini, A. (2013). Z-Score Models’ Application to Italian Companies Subject to Extraordinary Administration. Journal of Applied Finance (Formerly Financial Practice and Education), 23(1), 1–10. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2686750
Afonso, A., & Jalles, J. T. (2020). Sovereign indebtedness and financial and fiscal conditions. Applied Economics Letters, 27(19), 1611-1616. https://doi.org/10.1080/13504851.2019.1707758 DOI: https://doi.org/10.1080/13504851.2019.1707758
Antulov-Fantulin, N., Lagravinese, R., & Resce, G. (2021). Predicting bankruptcy of local government: A machine learning approach. Journal of Economic Behavior and Organization, 183, 681–699. https://doi.org/10.1016/j.jebo.2021.01.014 DOI: https://doi.org/10.1016/j.jebo.2021.01.014
Benito, B., Bastida, F., & Muñoz, M. J. (2010). Factores Explicativos de la Presión Fiscal Municipal: Explanatory Factors of the Municipal Fiscal Burden. Revista de Contabilidad-Spanish Accounting Review, 13(2), 239-283. https://doi.org/10.1016/S1138-4891(10)70018-2 DOI: https://doi.org/10.1016/S1138-4891(10)70018-2
Bisogno, M., Cuadrado-Ballesteros, B., Santis, S., & Citro, F. (2019). Budgetary solvency of Italian local governments: an assessment. International Journal of Public Sector Management, 32(2), 122–141. https://doi.org/10.1108/IJPSM-11-2017-0328 DOI: https://doi.org/10.1108/IJPSM-11-2017-0328
Bolognesi, B., Ribeiro, E., & Codato, A. (2023). Uma Nova Classificação Ideológica dos Partidos Políticos Brasileiros. Dados, 66(2). https://doi.org/10.1590/dados.2023.66.2.303 DOI: https://doi.org/10.1590/dados.2023.66.2.303
Bowman, W., & Calia, R. (1997). Evaluating Local Government Financial Health: Financial Indicators for Cook, DuPage, Kane, Lake, McHenry e Will Counties. Chicago: The Civic Federation.
Brasil (2022). Visão Integrada das Dívidas da União, dos Estados, do Distrito Federal e dos Municípios. https://www.tesourotransparente.gov.br/historias/visao-integrada-das-dividas-da-uniao-dos-estados-do-distrito-federal-e-dos-municipios
Breiman, L. (2001). Random Forests. Machine Learning, 45, 5–32. https://doi.org/10.1023/A:1010933404324 DOI: https://doi.org/10.1023/A:1010933404324
Brien, S. T., Eger III, R. J., & Matkin, D. S. (2021). The timing of managerial responses to fiscal stress. Public Administration Review, 81(3), 414-427. https://doi.org/10.1111/puar.13359 DOI: https://doi.org/10.1111/puar.13359
Brown, K. W. (1993). The 10-point test of financial condition: Toward an easy-to-use assessment tool for smaller cities. Government Finance Review, 9, 1–21. https://localgovernment.extension.wisc.edu/files/2016/04/kenneth-brown-Ten-point-test.pdf
Chen, D. (2021). Risk Assessment of Government Debt Based on Machine Learning Algorithm. Complexity, 2021. https://doi.org/10.1155/2021/3686692 DOI: https://doi.org/10.1155/2021/3686692
Chung, I. H., & Williams, D. (2021). Local governments’ responses to the fiscal stress label: the case of New York. Local Government Studies, 47(5), 808–835. https://doi.org/10.1080/03003930.2020.1797693 DOI: https://doi.org/10.1080/03003930.2020.1797693
Clark, T. N. (1977). Fiscal Management of American Cities: Funds Flow Indicators. Journal of Accounting Research, 15, 54–94. https://doi.org/10.2307/2490632 DOI: https://doi.org/10.2307/2490632
Clark, T. N. (1994). Municipal fiscal strain: Indicators and causes. Government Finance Review, 10, 1–27. https://go.gale.com/ps/i.do?id=GALE%7CA16086840&sid=googleScholar&v=2.1&it=r&linkaccess=fulltext&issn=08837856&p=AONE&sw=w&casa_token=XC85Higz1-4AAAAA:ujKvciuvQw7yv8J_SIMZZ1SoCfcyNsjL0Lii7eKQ25qQ-E30222X2chQyYHfqqlzat4s6YjHvNpaLA
Cohen, S., Costanzo, A., & Manes-Rossi, F. (2017). Auditors and early signals of financial distress in local governments. Managerial Auditing Journal, 32(3), 234–250. https://doi.org/10.1108/MAJ-05-2016-1371 DOI: https://doi.org/10.1108/MAJ-05-2016-1371
Costa, C. C. D. M., Ferreira, M. A. M., Braga, M. J., & Abrantes, L. A. (2015). Fatores associados à eficiência na alocação de recursos públicos à luz do modelo de regressão quantílica. Revista de Administração Pública, 49(5), 1319-1347. https://doi.org/10.1590/0034-7612130868 DOI: https://doi.org/10.1590/0034-7612130868
Costa, F. M. D., & Leão, F. H. F. C. (2021). Gerenciamento de resultados e ciclo eleitoral em municípios brasileiros. Revista de Administração Pública, 55, 697-715. https://doi.org/10.1590/0034-761220200112 DOI: https://doi.org/10.1590/0034-761220200112
Cruvinel, D. P., & Lima, D. V. (2011). Adoção do regime de competência no setor público brasileiro sob a perspectiva das normas brasileiras e internacionais de contabilidade. Revista de Educação e Pesquisa em contabilidade, 5(3), 69-85. https://www.redalyc.org/pdf/4416/441642859005.pdf DOI: https://doi.org/10.17524/repec.v5i3.185
Cutler, A., Cutler, D. R., & Stevens, J. R. (2012). Random Forests. Ensemble Machine Learning, 157–175. https://doi.org/10.1007/978-1-4419-9326-7_5 DOI: https://doi.org/10.1007/978-1-4419-9326-7_5
Dantas Junior, A. F., Diniz, J. A., & Lima, S. C. (2019). A Influência Do Federalismo Fiscal Sobre O Estresse Fiscal Dos Municípios Brasileiros. Advances in Scientific and Applied Accounting, 12(3), 062–078. https://doi.org/10.14392/asaa.2019120304 DOI: https://doi.org/10.14392/ASAA.2019120304
García-Sánchez, I. M., Cuadrado-Ballesteros, B., Frías-Aceituno, J. V., & Mordan, N. (2012). A New Predictor of Local Financial Distress. International Journal of Public Administration, 35(11), 739–748. https://doi.org/10.1080/01900692.2012.679173 DOI: https://doi.org/10.1080/01900692.2012.679173
Groves, S. M., Godsey, W. M., & Shulman, M. A. (1981). Financial Indicators for Local Government. Public Budgeting & Finance, 1(2), 5–19. https://doi.org/10.1111/1540-5850.00511 DOI: https://doi.org/10.1111/1540-5850.00511
Groves, S. M., & Valente, M. G. (2003). Evaluating financial condition: A handbook for local government. 4. ed. revised by Karl Nollenberger. Washington: The international City/Country Management Association – ICMA.
Hendrick, R. (2004). Assessing and measuring the fiscal heath of local governments: Focus on Chicago suburban municipalities. Urban Affairs Review, 40(1), 78–114. https://doi.org/10.1177/1078087404268076 DOI: https://doi.org/10.1177/1078087404268076
Honadle, B. W. (2003). The states’ role in U.S. local government fiscal crises: A theoretical model and results of a national survey. International Journal of Public Administration, 26(13), 1431–1472. https://doi.org/10.1081/PAD-120024405 DOI: https://doi.org/10.1081/PAD-120024405
Iacuzzi, S. (2022). An appraisal of financial indicators for local government: a structured literature review. Journal of Public Budgeting, Accounting and Financial Management, 34(6), 69–94. https://doi.org/10.1108/JPBAFM-04-2021-0064 DOI: https://doi.org/10.1108/JPBAFM-04-2021-0064
Janitza, S., & Hornung, R. (2018). On the overestimation of random forest’s out-of-bag error. PloS one, 13(8), 1-31. https://doi.org/10.1371/journal.pone.0201904 DOI: https://doi.org/10.1371/journal.pone.0201904
Jarmulska, B. (2022). Random forest versus logit models: Which offers better early warning of fiscal stress?. Journal of Forecasting, 41(3), 455-490. https://doi.org/10.1002/for.2806 DOI: https://doi.org/10.1002/for.2806
Jucá, M. N., & Fishlow, A. (2021). Political uncertainty of impeachment upon corporate investment decisions. Borsa Istanbul Review, 21(2), 149–160. https://doi.org/10.1016/j.bir.2020.09.007 DOI: https://doi.org/10.1016/j.bir.2020.09.007
Kim, Y., & Warner, M. E. (2018). Geographies of local government stress after the great recession. Social Policy & Administration, 52(1), 365-386. https://doi.org/10.1111/spol.12307 DOI: https://doi.org/10.1111/spol.12307
Kloha, P., Weissert, C. S., & Kleine, R. (2005). Developing and Testing a Composite Model to Predict Local Fiscal Distress. Public Administration Review, 65(3), 313–323. https://doi.org/10.1111/j.1540-6210.2005.00456.x DOI: https://doi.org/10.1111/j.1540-6210.2005.00456.x
Lei de Responsabilidade Fiscal (LRF) (2000). “LEI COMPLEMENTAR Nº 101, DE 4 DE MAIO DE 2000”. Presidência da República. https://www.planalto.gov.br/ccivil_03/leis/lcp/lcp101.htm
Leiser, S., Wang, S., & Kargman, C. (2021). Perceptions of Local Government Fiscal Health and Fiscal Stress: Evidence from Quantile Regressions with Michigan Municipalities and Counties. State and Local Government Review, 53(4), 317-336. https://doi.org/10.1177/0160323X211038356 DOI: https://doi.org/10.1177/0160323X211038356
Lima, S. C. de, & Diniz, J. A. (2016). Contabilidade Pública - Análise Financeira Governamental (1ª ed.). Atlas.
Lin, T. C. W. (2019). Artificial Intelligence, Finance, and the Law. Fordham Law Review, 88(2), 531–551. https://ir.lawnet.fordham.edu/flr/vol88/iss2/6
Lobo, F. C., Ramos, P., & Lourenço, Ó. (2011). Causes of financial distress of Portuguese municipalities: empirical evidence. International Journal Monetary Economics and Finance, 4(4), 390–409. https://doi.org/10.1504/IJMEF.2011.043402 DOI: https://doi.org/10.1504/IJMEF.2011.043402
Magkonis, G., & Tsopanakis, A. (2016). The financial and fiscal stress interconnectedness: The case of G5 economies. International review of financial analysis, 46, 62-69. https://doi.org/10.1016/j.irfa.2016.03.019 DOI: https://doi.org/10.1016/j.irfa.2016.03.019
Maher, C. S., Hoang, T., & Hindery, A. (2020). Fiscal Responses to COVID-19: Evidence from Local Governments and Nonprofits. Public Administration Review, 80(4), 644–650. https://doi.org/10.1111/puar.13238 DOI: https://doi.org/10.1111/puar.13238
McDonald, B. D., & Larson, S. E. (2020). Implications of the coronavirus on sales tax revenue and local government fiscal health. Journal of Public and Nonprofit Affairs, 6(3), 377–400. https://doi.org/10.20899/JPNA.6.3.377-400 DOI: https://doi.org/10.20899/jpna.6.3.377-400
Miranda, W. L. L. C. de, Araújo, R. J. R. de, Leite, I. F., & Nobre, C. J. F. (2018). Avaliação da gestão fiscal nos estados brasileiros: Análise no quinquênio 2011 a 2015. Revista Mineira de Contabilidade, 19(1), 55–67. https://doi.org/10.21714/2446-9114rmc2018v19n1t05 DOI: https://doi.org/10.21714/2446-9114RMC2018v19n1t05
Navarro-Galera, A., Lara-Rubio, J., Buendía-Carrillo, D., & Rayo-Cantón, S. (2020). Analyzing political and systemic determinants of financial risk in local governments. Transylvanian Review of Administrative Sciences, 16(59), 104-123. http://dx.doi.org/10.24193/tras.59E.6 DOI: https://doi.org/10.24193/tras.59E.6
Oliveira, T. M. G., Dall’Asta, D., Zonatto, V. C. S., & Martins, V. A. (2021). Gestão Fiscal Municipal: uma análise sob a ótica do federalismo fiscal e dos ciclos políticos nos governos locais. Administração Pública E Gestão Social, 13(4). https://doi.org/10.21118/apgs.v13i4.11770 DOI: https://doi.org/10.21118/apgs.v13i4.11770
Preston, B. T. (1985). Rich Town, Poor Town: The Distribution of Rate-Borne Spending Levels in the Edwardian City. Transactions of the Institute of British Geographers, 10(1), 77–94. https://doi.org/10.2307/622251 DOI: https://doi.org/10.2307/622251
Psycharis, Y., Zoi, M., & Iliopoulou, S. (2016). Decentralization and local government fiscal autonomy: evidence from the Greek municipalities. Environment and Planning C: Government and Policy, 34(2), 262–280. https://doi.org/10.1177/0263774X15614153 DOI: https://doi.org/10.1177/0263774X15614153
Shi, Y. (2019). A response to fiscal stress: public sector employment reduction across states during a budget crisis. International Journal of Public Administration, 42(13), 1095-1105. https://doi.org/10.1080/01900692.2019.1575852 DOI: https://doi.org/10.1080/01900692.2019.1575852
Silva, M. C., Souza, F. J. V., Martins, J. D. M., & Câmara, R. P. B. (2020). Fatores explicativos da gestão fiscal em municípios brasileiros. Revista Contemporânea de Contabilidade, 17(42), 26–37. https://doi.org/10.5007/2175-8069.2020v17n42p26 DOI: https://doi.org/10.5007/2175-8069.2020v17n42p26
Stanley, D. T. (1980). Managing fiscal stress: the crises in the public sector. Chatham House Publishers.
Tang, C., Garreau, D., & von Luxburg, U. (2018). When do random forests fail?. Advances in neural information processing systems, 31. https://proceedings.neurips.cc/paper/2018/hash/204da255aea2cd4a75ace6018fad6b4d-Abstract.html
Tran, C., Kortt, M., & Dollery, B. (2019). Population size or population density? An empirical examination of scale economies in South Australian local government, 2015/16. Local Government Studies, 45(5), 632-653. https://doi.org/10.1080/03003930.2018.1501364 DOI: https://doi.org/10.1080/03003930.2018.1501364
Trussel, J. M., & Patrick, P. A. (2018). Assessing and ranking the financial risk of municipal governments. Journal of Applied Accounting Research, 19(1), 81–101. https://doi.org/10.1108/JAAR-05-2016-0051 DOI: https://doi.org/10.1108/JAAR-05-2016-0051
Turley, G., Di Medio, R., & McNena, S. (2020). A reassessment of local government’s financial position and performance: The case of Ireland. Administration, 68(2), 1–35. https://doi.org/10.2478/admin-2020-0009 DOI: https://doi.org/10.2478/admin-2020-0009
Vieira, M. A., De Ávila, L. A. C., & Lopes, J. D. V. S. (2021). Desenvolvimento socioeconômico e eficiência tributária: uma análise dos Municípios de Minas Gerais. Revista Universo Contábil, 16(3), 160-179. http://dx.doi.org/10.4270/ruc.2020320 DOI: https://doi.org/10.4270/ruc.2020320
Vieira, F. S. (2016). Crise econômica, austeridade fiscal e saúde: que lições podem ser aprendidas? Brasil: Instituto de Pesquisa Econômica Aplicada. http://repositorio.ipea.gov.br/bitstream/11058/7266/1/NT_n26_Disoc.pdf
Warner, M. E., Aldag, A. M., & Kim, Y. (2021). Pragmatic municipalism: US local government responses to fiscal stress. Public Administration Review, 81(3), 389-398. https://doi.org/10.1111/puar.13196 DOI: https://doi.org/10.1111/puar.13196
Zafra-Gómez, J. L., López-Hernández, A. M., & Hernández-Bastida, A. (2009). Developing an alert system for local governments in financial crisis. Public Money and Management, 29(3), 175–181. https://doi.org/10.1080/09540960902891731 DOI: https://doi.org/10.1080/09540960902891731
Zarkova, S., Kostov, D., Angelov, P., Pavlov, T., & Zahariev, A. (2023). Machine Learning Algorithm for Mid-Term Projection of the EU Member States’ Indebtedness. Risks, 11(4), 71. https://doi.org/10.3390/risks11040071 DOI: https://doi.org/10.3390/risks11040071
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Danie Vitor Tartari Garruti, Flávio Luiz de Moraes Barboza, Josedilton Alvez Diniz
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright for articles published in the ASAA Journal is held by the author, with first publication rights to the journal. By virtue of appearing in this publicly accessible journal, the articles are free to use, with their own attributions, in educational and non-commercial applications. The ASAA Journal will allow the use of published works for non-commercial purposes, including the right to submit the work to publicly accessible databases. Published articles are the authors' full and exclusive responsibility. There are no submission/publishing charges or fees for processing articles (APC).
