Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]

This article shows the prediction of the level of insolvency in companies that are not listed on the stock exchange belonging to the health sector for one and two years in advance, using the multiple logistic regression analysis based on indicators of liquidity, indebtedness, financial structure and...

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Fecha de publicación:: 2018

Institución:: Universidad de Medellín

Repositorio:: Repositorio UDEM

Idioma:: spa

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network_acronym_str	REPOUDEM2
network_name_str	Repositorio UDEM
repository_id_str
dc.title.none.fl_str_mv	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
title	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
spellingShingle	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit] Financial indicators Insolvency Logit models
title_short	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
title_full	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
title_fullStr	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
title_full_unstemmed	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
title_sort	Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]
dc.subject.none.fl_str_mv	Financial indicators Insolvency Logit models
topic	Financial indicators Insolvency Logit models
description	This article shows the prediction of the level of insolvency in companies that are not listed on the stock exchange belonging to the health sector for one and two years in advance, using the multiple logistic regression analysis based on indicators of liquidity, indebtedness, financial structure and pro_tability. The period 2010@@@2013 is taken as a reference for a sample of 3,930 companies categorized by size (large, medium, small and micro), and classified by their level of high, medium and low insolvency risk. The success results of the models are between 70% and 80% for each of the years, validating the results obtained throughout the study. © 2019, Universidad Pablo de Olavide.
publishDate	2018
dc.date.accessioned.none.fl_str_mv	2020-04-29T14:53:46Z
dc.date.available.none.fl_str_mv	2020-04-29T14:53:46Z
dc.date.none.fl_str_mv	2018
dc.type.eng.fl_str_mv	Article
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dc.type.coar.fl_str_mv	http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.none.fl_str_mv	info:eu-repo/semantics/article
dc.identifier.issn.none.fl_str_mv	1886516X
dc.identifier.uri.none.fl_str_mv	http://hdl.handle.net/11407/5723
identifier_str_mv	1886516X
url	http://hdl.handle.net/11407/5723
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language	spa
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dc.relation.citationvolume.none.fl_str_mv	26
dc.relation.citationstartpage.none.fl_str_mv	128
dc.relation.citationendpage.none.fl_str_mv	145
dc.relation.references.none.fl_str_mv	Alaka, H., Oyedele, L., Owolabi, H., Kumar, V., Ajayi, S., Akinade, O., Bilal, M., Systematic Review of Bankruptcy Prediction Models: Towards a Framework for Tool Selection (2018) Expert Systems with Applications, 94, pp. 164-184 Altman, E., Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy (1968) The Journal of Finance, 23 (4), pp. 589-609 Altman, E., (1981) Financial Handbook, , New York: John Wiley & Sons Appiah, K., Chizema, A., Arthur, J., Predicting corporate failure: A systematic literature review of methodological issues (2015) International Journal of Law and Management, 57 (5), pp. 461-485 Aziz, M., Dar, H., Predicting corporate bankruptcy: Where we stand? (2006) Corporate Governance: The International Journal of Business in Society, 6 (1), pp. 18-33 Beaver, W.H., Financial Ratios as Predictors of Failure (1966) Journal of Accounting Research, 4 (3), pp. 71-111 Collins, R., Green, R., Statistical methods for bankruptcy forecasting (1982) Journal of Economics and Business, 34 (4), pp. 349-354 De Llano, P., Piñeiro, C., Rodriguez, M., Business failure prediction. A contribution to the synthesis of a theory, through comparative analysis of different prediction techniques (2016) Estudios de Economía, 43 (2), pp. 163-198 Fitzpatrick, F., A Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Firm (1932) Certified Public Accountant, 6, pp. 727-731 Korol, T., Early warning models against bankruptcy risk for Central European and Latin American enterprises (2013) Economic Modelling, 31, pp. 22-30 Laffarga, J., Martín, J., Vázquez, M., El análisis de la solvencia de las instituciones bancarias: Propuesta de una metodología y aplicaciones a la Banca española (1985) ESIC-Market, 48, pp. 51-73 Lennox, C., Identifying failing companies: A re-evaluation of the logit, probit and DA approaches (1999) Journal of Economics and Business, 51 (4), pp. 347-364 Lincoln, M., An empirical study of the usefulness of accounting ratios to describe levels of insolvency risk (1984) Journal of Banking & Finance, 8 (2), pp. 321-340 McDonald, B., Morris, M., The statistical validity of the ratio method in financial analysis: An empirical examination (1984) Journal of Business Finance & Accounting, 11 (1), pp. 89-97 Mures, M., García, A., Vallejo, M., Análisis del fracaso empresarial por sectores: Factores diferenciadores (2012) Pecunia, pp. 53-83. , Monográfico 2010 Ohlson, J., Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980) Journal of Accounting Research, 18 (1), pp. 109-131 Pereira, J., Crespo, M., Sáez, J., Modelos de Previsão do Fracasso Empresarial: Aspectos a considerar (2007) Revista de Estudos Politécnicos, 4 (7), pp. 111-118. , (en portugués) Pérez, C., Santín, D., (2007) Minería de datos. Técnicas y herramientas, , Madrid: Paraninfo Platt, H., Platt, M., Predicting corporate financial distress: Reflections on choice-based sample bias (2002) Journal of Economics and Finance, 26 (2), pp. 184-199 Premachandra, I., Bhabra, G., Sueyoshi, T., DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique (2009) European Journal of Operational Research, 193 (2), pp. 412-424 Ravi, P., Ravi, V., Bankruptcy prediction in banks and firms via statistical and intelligent techniques-A review (2007) European Journal of Operational Research, 180 (1), pp. 1-28 Rodríguez, C., Maté, M., López, F., El contagio en el fracaso empresarial como consecuencia de la proximidad geográfica: Un análisis con los estadísticos join-count aplicado al sector servicios (2017) Revista de Métodos Cuantitativos para la Economía y la Empresa, 23, pp. 75-95 Sun, J., Li, H., Huang, Q., He, K., Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014) Knowledge-Based Systems, 57, pp. 41-56 Tam, K., Kiang, M., Predicting bank failures: A neural network approach (1990) Applied Artificial Intelligence, 4 (4), pp. 265-282 Tascón, M., Castaño, F., Variables y modelos para la identificación y predicción del fracaso empresarial: Revisión de la investigación empírica reciente (2012) Revista de Contabilidad, 15 (1), pp. 7-58 Turetsky, H., McEwen, R., An empirical investigation of firm longevity: A model of the ex ante predictors of financial distress (2001) Review of Quantitative Finance and Accounting, 16 (4), pp. 323-343 Zmijewski, M., Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984) Journal of Accounting Research, 22, pp. 59-82
dc.rights.coar.fl_str_mv	http://purl.org/coar/access_right/c_16ec
rights_invalid_str_mv	http://purl.org/coar/access_right/c_16ec
dc.publisher.none.fl_str_mv	Universidad Pablo de Olavide
dc.publisher.program.none.fl_str_mv	Administración de Empresas
dc.publisher.faculty.none.fl_str_mv	Facultad de Ciencias Económicas y Administrativas
publisher.none.fl_str_mv	Universidad Pablo de Olavide
dc.source.none.fl_str_mv	Revista de Metodos Cuantitativos para la Economia y la Empresa
institution	Universidad de Medellín
repository.name.fl_str_mv	Repositorio Institucional Universidad de Medellin
repository.mail.fl_str_mv	repositorio@udem.edu.co
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spelling	20182020-04-29T14:53:46Z2020-04-29T14:53:46Z1886516Xhttp://hdl.handle.net/11407/5723This article shows the prediction of the level of insolvency in companies that are not listed on the stock exchange belonging to the health sector for one and two years in advance, using the multiple logistic regression analysis based on indicators of liquidity, indebtedness, financial structure and pro_tability. The period 2010@@@2013 is taken as a reference for a sample of 3,930 companies categorized by size (large, medium, small and micro), and classified by their level of high, medium and low insolvency risk. The success results of the models are between 70% and 80% for each of the years, validating the results obtained throughout the study. © 2019, Universidad Pablo de Olavide.spaUniversidad Pablo de OlavideAdministración de EmpresasFacultad de Ciencias Económicas y Administrativashttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85077237101&partnerID=40&md5=f211ea890034fc8bfb1d98506ef8bcd226128145Alaka, H., Oyedele, L., Owolabi, H., Kumar, V., Ajayi, S., Akinade, O., Bilal, M., Systematic Review of Bankruptcy Prediction Models: Towards a Framework for Tool Selection (2018) Expert Systems with Applications, 94, pp. 164-184Altman, E., Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy (1968) The Journal of Finance, 23 (4), pp. 589-609Altman, E., (1981) Financial Handbook, , New York: John Wiley & SonsAppiah, K., Chizema, A., Arthur, J., Predicting corporate failure: A systematic literature review of methodological issues (2015) International Journal of Law and Management, 57 (5), pp. 461-485Aziz, M., Dar, H., Predicting corporate bankruptcy: Where we stand? (2006) Corporate Governance: The International Journal of Business in Society, 6 (1), pp. 18-33Beaver, W.H., Financial Ratios as Predictors of Failure (1966) Journal of Accounting Research, 4 (3), pp. 71-111Collins, R., Green, R., Statistical methods for bankruptcy forecasting (1982) Journal of Economics and Business, 34 (4), pp. 349-354De Llano, P., Piñeiro, C., Rodriguez, M., Business failure prediction. A contribution to the synthesis of a theory, through comparative analysis of different prediction techniques (2016) Estudios de Economía, 43 (2), pp. 163-198Fitzpatrick, F., A Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Firm (1932) Certified Public Accountant, 6, pp. 727-731Korol, T., Early warning models against bankruptcy risk for Central European and Latin American enterprises (2013) Economic Modelling, 31, pp. 22-30Laffarga, J., Martín, J., Vázquez, M., El análisis de la solvencia de las instituciones bancarias: Propuesta de una metodología y aplicaciones a la Banca española (1985) ESIC-Market, 48, pp. 51-73Lennox, C., Identifying failing companies: A re-evaluation of the logit, probit and DA approaches (1999) Journal of Economics and Business, 51 (4), pp. 347-364Lincoln, M., An empirical study of the usefulness of accounting ratios to describe levels of insolvency risk (1984) Journal of Banking & Finance, 8 (2), pp. 321-340McDonald, B., Morris, M., The statistical validity of the ratio method in financial analysis: An empirical examination (1984) Journal of Business Finance & Accounting, 11 (1), pp. 89-97Mures, M., García, A., Vallejo, M., Análisis del fracaso empresarial por sectores: Factores diferenciadores (2012) Pecunia, pp. 53-83. , Monográfico 2010Ohlson, J., Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980) Journal of Accounting Research, 18 (1), pp. 109-131Pereira, J., Crespo, M., Sáez, J., Modelos de Previsão do Fracasso Empresarial: Aspectos a considerar (2007) Revista de Estudos Politécnicos, 4 (7), pp. 111-118. , (en portugués)Pérez, C., Santín, D., (2007) Minería de datos. Técnicas y herramientas, , Madrid: ParaninfoPlatt, H., Platt, M., Predicting corporate financial distress: Reflections on choice-based sample bias (2002) Journal of Economics and Finance, 26 (2), pp. 184-199Premachandra, I., Bhabra, G., Sueyoshi, T., DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique (2009) European Journal of Operational Research, 193 (2), pp. 412-424Ravi, P., Ravi, V., Bankruptcy prediction in banks and firms via statistical and intelligent techniques-A review (2007) European Journal of Operational Research, 180 (1), pp. 1-28Rodríguez, C., Maté, M., López, F., El contagio en el fracaso empresarial como consecuencia de la proximidad geográfica: Un análisis con los estadísticos join-count aplicado al sector servicios (2017) Revista de Métodos Cuantitativos para la Economía y la Empresa, 23, pp. 75-95Sun, J., Li, H., Huang, Q., He, K., Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014) Knowledge-Based Systems, 57, pp. 41-56Tam, K., Kiang, M., Predicting bank failures: A neural network approach (1990) Applied Artificial Intelligence, 4 (4), pp. 265-282Tascón, M., Castaño, F., Variables y modelos para la identificación y predicción del fracaso empresarial: Revisión de la investigación empírica reciente (2012) Revista de Contabilidad, 15 (1), pp. 7-58Turetsky, H., McEwen, R., An empirical investigation of firm longevity: A model of the ex ante predictors of financial distress (2001) Review of Quantitative Finance and Accounting, 16 (4), pp. 323-343Zmijewski, M., Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984) Journal of Accounting Research, 22, pp. 59-82Revista de Metodos Cuantitativos para la Economia y la EmpresaFinancial indicatorsInsolvencyLogit modelsModeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]Articleinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Támara Ayús, A.L., Departamento de Finanzas, Escuela de Economía y Finanzas Universidad EAFIT, Colombia; Villegas, G.C., Administrativas Universidad de Medellín, Colombia; Leones Castro, M.C., Departamento de Finanzas, Escuela de Economía y Finanzas Universidad EAFIT, Colombia; Salazar Bocanegra, J.A., Departamento de Finanzas, Escuela de Economía y Finanzas Universidad EAFIT, Colombiahttp://purl.org/coar/access_right/c_16ecTámara Ayús A.L.Villegas G.C.Leones Castro M.C.Salazar Bocanegra J.A.11407/5723oai:repository.udem.edu.co:11407/57232020-05-27 19:13:39.955Repositorio Institucional Universidad de Medellinrepositorio@udem.edu.co

Modeling of insolvency risk in health sector companies using logit models [Modelación del riesgo de insolvencia en empresas del sector salud empleando modelos logit]

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