IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p9961-d1176997.html
   My bibliography  Save this article

Chilean Universities and Universal Gratuity: Suggestions for a Model to Evaluate the Effects on Financial Vulnerability

Author

Listed:
  • Juan Alejandro Gallegos Mardones

    (Departamento de Auditoría y Sistemas de Información, Facultad de Ciencias Económicas y Administrativas, Universidad Católica de la Santísima Concepción, Concepción 4030000, Chile)

  • Jorge Andrés Moraga Palacios

    (Facultad de Ingeniería, Universidad de Concepción, Concepción 4030000, Chile)

Abstract

Financial vulnerability can be understood as the risk of an organisation being unable to carry out routine its normal operations due to financial restrictions. Models to estimate financial vulnerability have mainly been developed for profit-making organisations, while few exist for non-profit organisations (NPOs). One example is higher education institutions, which have experienced important changes in Latin America through gratuity policies for student tuition. This study proposes a model to estimate the effects of gratuity on financial vulnerability, as previous studies have focused on the effects of enrolment. A binary logistic regression model is proposed, considering the following variables: debt, income concentration, operating margin, administration costs, and square metres of rooms per student. We applied this model to 54 universities between 2013 and 2019. The results showed that the model is relevant for the debt, size, and operating margin variables. Additionally, we observed that on average, all universities were negatively affected. This result is particularly true for state-owned universities because of certain management restrictions. A limitation of this study is the unavailability of other sources of non-financial information, such as each university’s business model and stock of strategic resources, which could improve our model, as this information is more related to control than to management.

Suggested Citation

  • Juan Alejandro Gallegos Mardones & Jorge Andrés Moraga Palacios, 2023. "Chilean Universities and Universal Gratuity: Suggestions for a Model to Evaluate the Effects on Financial Vulnerability," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9961-:d:1176997
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/9961/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/9961/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Enrico Bracci & Christopher Humphrey & Jodie Moll & Ileana Steccolini, 2015. "Public sector accounting, accountability and austerity: more than balancing the books?," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 28(6), pages 878-908, August.
    2. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 10(1), pages 167-179.
    3. repec:eme:aaaj00:aaaj-06-2015-2090 is not listed on IDEAS
    4. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    5. Thomas Ahrens & Laurence Ferry, 2015. "Newcastle City Council and the grassroots: accountability and budgeting under austerity," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 28(6), pages 909-933, August.
    6. Cleopatra Grizzle & Margaret F. Sloan & Mirae Kim, 2015. "Financial factors that influence the size of nonprofit operating reserves," Journal of Public Budgeting, Accounting & Financial Management, Emerald Group Publishing Limited, vol. 27(1), pages 67-97, March.
    7. Helen Irvine & Christine Ryan, 2019. "The financial health of Australian universities: policy implications in a changing environment," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 32(5), pages 1500-1531, August.
    8. Thomas Ahrens & Laurence Ferry, 2015. "Newcastle City Council and the grassroots: accountability and budgeting under austerity," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 28(6), pages 909-933, August.
    9. repec:eme:aaaj00:aaaj-03-2014-1658 is not listed on IDEAS
    10. repec:eme:aaaj00:aaaj-03-2018-3391 is not listed on IDEAS
    11. Daniel Zdolšek & Timotej Jagrič & Iztok Kolar, 2022. "Auditor’s going-concern opinion prediction: the case of Slovenia," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 106-121, December.
    12. Robert Zenzerović, 2009. "Business′ Financial Problems Prediction - Croatian Experience," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 22(4), pages 1-15, January.
    13. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 12(1), pages 1-25.
    14. Brass, Jennifer N., 2012. "Why Do NGOs Go Where They Go? Evidence from Kenya," World Development, Elsevier, vol. 40(2), pages 387-401.
    15. Fatih Ecer, 2013. "Comparing the Bank Failure Prediction Performance of Neural Networks and Support Vector Machines: The Turkish Case," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 26(3), pages 81-98, January.
    16. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    17. Enrico Bracci & Christopher Humphrey & Jodie Moll & Ileana Steccolini, 2015. "Public sector accounting, accountability and austerity: more than balancing the books?," Accounting, Auditing & Accountability Journal, Emerald Group Publishing Limited, vol. 28(6), pages 878-908, August.
    18. Cordery, Carolyn J. & Sim, Dalice & Baskerville, Rachel F., 2013. "Three models, one goal: Assessing financial vulnerability in New Zealand amateur sports clubs," Sport Management Review, Elsevier, vol. 16(2), pages 186-199.
    19. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, John Wiley & Sons, Ltd., vol. 18(1), pages 109-131.
    20. Harney, Stefano & Dunne, Stephen, 2013. "More than nothing? Accounting, business, and management studies, and the research audit," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 24(4), pages 338-349.
    21. Keating, Elizabeth K. & Fischer, Mary & Gordon, Teresa P. & Greenlee, Janet, 2005. "Assessing Financial Vulnerability in the Nonprofit Sector," Working Paper Series rwp05-002, Harvard University, John F. Kennedy School of Government.
    22. Radu Stroe & Nicoleta Barbuta-Misu, 2010. "Predicting the Financial Performance of the Building Sector Enterprises -- Case Study of Galati County (Romania)," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 2(1), pages 029-039, June.
    23. Juan Gallegos Mardones & Nelyda Campos-Requena, 2021. "Can higher education admission be more equitable? Evidence supporting the inclusion of relative ranking in the process," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 34(1), pages 2539-2554, January.
    24. Carolyn J. Cordery & Dalice Sim & Rachel F. Baskerville, 2013. "Three models, one goal: Assessing financial vulnerability in New Zealand amateur sports clubs," Sport Management Review, Taylor & Francis Journals, vol. 16(2), pages 186-199, April.
    25. Siekelova Anna & Kliestik Tomas & Adamko Peter, 2018. "Predictive Ability of Chosen Bankruptcy Models: A Case Study of Slovak Republic," Economics and Culture, Sciendo, vol. 15(1), pages 105-114, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jaroslav Mazanec & Viera Bartosova & Patrik Bohm, 2022. "Logit Model for Estimating Non-Profit Organizations’ Financial Status as a Part of Non-Profit Financial Management," Mathematics, MDPI, vol. 10(13), pages 1-18, June.
    2. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    3. Lillian Cheung & Amnon Levy, 1998. "An integrative analysis of business bankruptcy in Australia," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 22(2), pages 149-167, June.
    4. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 15(1), pages 133-150, June.
    5. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    6. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    7. Nicoleta Barbuta-Misu, 2012. "Aggregated Index for Modelling the Influence of Financial Variables on Enterprise Performance," EuroEconomica, Danubius University of Galati, issue 2(31), pages 155-165, May.
    8. Andrea Bedin & Monica Billio & Michele Costola & Loriana Pelizzon, 2019. "Credit Scoring in SME Asset-Backed Securities: An Italian Case Study," JRFM, MDPI, vol. 12(2), pages 1-28, May.
    9. Onofrei, Mihaela & Lupu, Dan, 2014. "The modelling of forecasting the bankruptcy in Romania," MPRA Paper 95511, University Library of Munich, Germany.
    10. Teija Laitinen & Maria Kankaanpaa, 1999. "Comparative analysis of failure prediction methods: the Finnish case," European Accounting Review, Taylor & Francis Journals, vol. 8(1), pages 67-92.
    11. Paweł Zając & Piotr Gurgul, 2012. "Forecasting of migration matrices in business demography," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(2), pages 387-404, June.
    12. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    13. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    14. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    15. Michal Pavlicko & Marek Durica & Jaroslav Mazanec, 2021. "Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries," Mathematics, MDPI, vol. 9(16), pages 1-26, August.
    16. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    17. Murray Nash & Michael Anstis & Michael Bradbury, 1989. "Testing Corporate Model Prediction Accuracy," Australian Journal of Management, Australian School of Business, vol. 14(2), pages 211-221, December.
    18. Antonio David Somoza Lopez & Josep Vallverdu Calafell, 2003. "Una comparacion de la seleccion de los ratios contables en los modelos contable-financieros de prediccion de la insolvencia empresarial," Working Papers in Economics 94, Universitat de Barcelona. Espai de Recerca en Economia.
    19. Akarsh Kainth & Ranik Raaen Wahlstrøm, 2021. "Do IFRS Promote Transparency? Evidence from the Bankruptcy Prediction of Privately Held Swedish and Norwegian Companies," JRFM, MDPI, vol. 14(3), pages 1-15, March.
    20. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9961-:d:1176997. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.