Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study
Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack o...
- Autores:
-
Blanco-Oliver, Antonio
Pino-Mejías, Rafael
Lara-Rubio, Juan
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2014
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/65939
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/65939
http://bdigital.unal.edu.co/66962/
- Palabra clave:
- 3 Ciencias sociales / Social sciences
Financial distress model
microenterprise start-ups
microfinancial institutions
Latin American
non-financial variables
modelo de dificultades financieras
microempresas de nueva creación
instituciones microfinancieras
América Latina
variables no financieras
Modelo de dificuldades financeiras
microempresas de criação recente
micro-instituições financeiras
América Latina
variáveis não financeiras
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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dc.title.spa.fl_str_mv |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
title |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
spellingShingle |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study 3 Ciencias sociales / Social sciences Financial distress model microenterprise start-ups microfinancial institutions Latin American non-financial variables modelo de dificultades financieras microempresas de nueva creación instituciones microfinancieras América Latina variables no financieras Modelo de dificuldades financeiras microempresas de criação recente micro-instituições financeiras América Latina variáveis não financeiras |
title_short |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
title_full |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
title_fullStr |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
title_full_unstemmed |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
title_sort |
Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study |
dc.creator.fl_str_mv |
Blanco-Oliver, Antonio Pino-Mejías, Rafael Lara-Rubio, Juan |
dc.contributor.author.spa.fl_str_mv |
Blanco-Oliver, Antonio Pino-Mejías, Rafael Lara-Rubio, Juan |
dc.subject.ddc.spa.fl_str_mv |
3 Ciencias sociales / Social sciences |
topic |
3 Ciencias sociales / Social sciences Financial distress model microenterprise start-ups microfinancial institutions Latin American non-financial variables modelo de dificultades financieras microempresas de nueva creación instituciones microfinancieras América Latina variables no financieras Modelo de dificuldades financeiras microempresas de criação recente micro-instituições financeiras América Latina variáveis não financeiras |
dc.subject.proposal.spa.fl_str_mv |
Financial distress model microenterprise start-ups microfinancial institutions Latin American non-financial variables modelo de dificultades financieras microempresas de nueva creación instituciones microfinancieras América Latina variables no financieras Modelo de dificuldades financeiras microempresas de criação recente micro-instituições financeiras América Latina variáveis não financeiras |
description |
Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack of research, nothing is known about whether non-financial information and non-parametric statistical techniques improve the predictive capacity of these models. Therefore, this paper provides an innovative financial distress model specifically designed for microenterprise startups via support vector machines (SVMs) that employs financial, non-financial, and macroeconomic variables. Based on a sample of almost 5,500 micro-entrepreneurs from a Peruvian Microfinance Institution (MFI), our findings show that the introduction of non-financial information related to the zone in which the entrepreneurs live and situate their business, the duration of the MFI-entrepre-neur relationship, the number of loans granted by the MFI in the last year, the loan destination, and the opinion of experts on the probability that microenterprise start-ups may experience financial problems, significantly increases the accuracy performance of our financial distress model. Furthermore, the results reveal that the models that use SVMs outperform those which employ traditional logistic regression (LR) analysis. |
publishDate |
2014 |
dc.date.issued.spa.fl_str_mv |
2014-02-01 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-03T01:11:42Z |
dc.date.available.spa.fl_str_mv |
2019-07-03T01:11:42Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.issn.spa.fl_str_mv |
ISSN: 2248-6968 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/65939 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/66962/ |
identifier_str_mv |
ISSN: 2248-6968 |
url |
https://repositorio.unal.edu.co/handle/unal/65939 http://bdigital.unal.edu.co/66962/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/innovar/article/view/47615 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Revista Innovar Journal Revista de Ciencias Administrativas y Sociales Revista Innovar Journal Revista de Ciencias Administrativas y Sociales |
dc.relation.references.spa.fl_str_mv |
Blanco-Oliver, Antonio and Pino-Mejías, Rafael and Lara-Rubio, Juan (2014) Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study. Innovar, 24 (1Spe). pp. 153-168. ISSN 2248-6968 |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Económicas - Escuela de Administración y Contaduría Pública |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/65939/1/47615-231295-1-SM.pdf https://repositorio.unal.edu.co/bitstream/unal/65939/2/47615-231295-1-SM.pdf.jpg |
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Repositorio Institucional Universidad Nacional de Colombia |
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spelling |
Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Blanco-Oliver, Antonio8b8593b6-5d41-4c24-af3f-39f11ed9756a300Pino-Mejías, Rafaeld3ef6522-4edc-4c21-9930-090d97b6c34c300Lara-Rubio, Juan78d4fb0c-00d7-4f83-bdb6-a0246cacfe7e3002019-07-03T01:11:42Z2019-07-03T01:11:42Z2014-02-01ISSN: 2248-6968https://repositorio.unal.edu.co/handle/unal/65939http://bdigital.unal.edu.co/66962/Despite the leading role that micro-entrepreneurship plays in economic development, and the high failure rate of microenterprise start-ups in their early years, very few studies have designed financial distress models to detect the financial problems of micro-entrepreneurs. Moreover, due to a lack of research, nothing is known about whether non-financial information and non-parametric statistical techniques improve the predictive capacity of these models. Therefore, this paper provides an innovative financial distress model specifically designed for microenterprise startups via support vector machines (SVMs) that employs financial, non-financial, and macroeconomic variables. Based on a sample of almost 5,500 micro-entrepreneurs from a Peruvian Microfinance Institution (MFI), our findings show that the introduction of non-financial information related to the zone in which the entrepreneurs live and situate their business, the duration of the MFI-entrepre-neur relationship, the number of loans granted by the MFI in the last year, the loan destination, and the opinion of experts on the probability that microenterprise start-ups may experience financial problems, significantly increases the accuracy performance of our financial distress model. Furthermore, the results reveal that the models that use SVMs outperform those which employ traditional logistic regression (LR) analysis.A pesar del destacado papel que desempeña el microemprendimiento en el desarrollo económico y de la alta tasa de quiebra que tienen las nuevas microempresas en sus primeros años de vida, muy pocos estúdios han diseñado un modelo para detectar las dificultades financieras de los microemprendedores Además, debido a la ausencia de investigaciones, no se conoce nada acerca de si la información no financiera y las técnicas estadísticas no paramétricas mejoran la capacidad predictiva de estos modelos. Por tanto, este artículo proporciona un innovador modelo para detectar las dificultades financieras específicamente diseñado para las microempresas de nueva creación mediante el uso de máquinas de soporte vectorial (MSV) y empleando variables financieras, no financieras y macroeconómicas. Basados en una muestra de casi 5.500 de una Institución Mi-crofinanciera (IMF) peruana, nuestros hallazgos muestran que la introducción de información no financiera relacionada con la zona en la que el emprendedor vive y localiza su negocio, la duración de la relación IMF-emprendedor, el número de préstamos concedidos por la IMF en el último año, el destino del préstamo y la opinión de los expertos sobre la probabilidad de que la nueva microempresa experimente problemas financieros, aumentan de manera significativa la precisión de nuestro modelo de detección de dificultades financieras. Además, los resultados revelan que los modelos construidos usando MVS superan los obtenidos por aquellos modelos que emplean el tradicional análisis de regresión logística.Apesar do destacado papel que o microempreendimento desempenha no desenvolvimento económico e da alta taxa de falências que as novas microempresas têm nos seus primeiros anos de vida, poucos estudos têm projetado um modelo para detectar as dificuldades financeiras dos microempreendedores. Além disso, devido à ausência de pesquisas, não se sabe nada sobre se a informação não financeira e as técnicas estatísticas não paramétricas melhoram a capacidade preditiva destes modelos. Portanto, este artigo proporciona um inovador modelo para detectar as dificuldades financeiras especificamente projetado para as microempresas de criação recente mediante o uso de máquinas de vetores suportes (MVS) e utilizando variáveis financeiras, não financeiras e macroeconómicas Baseados em uma amostra de quase 5.500 microempresas de uma micro-insti-tuição financeira (IMF) peruana, encontramos que a introdução de informação não financeira relacionada com a região na qual o empreendedor mora e localiza o seu negócio, a duração da relação IMF- empreendedor, o número de empréstimos concedidos pela IMF no último ano, a destinação do empréstimo e a opinião dos peritos sobre a probabilidade de a nova microempresa ter problemas financeiros aumentam significativamente a precisão do nosso modelo de detecção de dificuldades financeiras. Além do mais, os resultados revelam que os modelos construídos utilizando MVS ultrapassam os obtidos por aqueles modelos que utilizam a tradicional análise de regressão logística.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias Económicas - Escuela de Administración y Contaduría Públicahttps://revistas.unal.edu.co/index.php/innovar/article/view/47615Universidad Nacional de Colombia Revistas electrónicas UN Revista Innovar Journal Revista de Ciencias Administrativas y SocialesRevista Innovar Journal Revista de Ciencias Administrativas y SocialesBlanco-Oliver, Antonio and Pino-Mejías, Rafael and Lara-Rubio, Juan (2014) Modeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case Study. Innovar, 24 (1Spe). pp. 153-168. ISSN 2248-69683 Ciencias sociales / Social sciencesFinancial distress modelmicroenterprise start-upsmicrofinancial institutionsLatin Americannon-financial variablesmodelo de dificultades financierasmicroempresas de nueva creacióninstituciones microfinancierasAmérica Latinavariables no financierasModelo de dificuldades financeirasmicroempresas de criação recentemicro-instituições financeirasAmérica Latinavariáveis não financeirasModeling the Financial Distress of Microenterprise Start- Ups Using Support Vector Machines: A Case StudyArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL47615-231295-1-SM.pdfapplication/pdf424427https://repositorio.unal.edu.co/bitstream/unal/65939/1/47615-231295-1-SM.pdfef0e0405a20ba400bef98b6e30f42606MD51THUMBNAIL47615-231295-1-SM.pdf.jpg47615-231295-1-SM.pdf.jpgGenerated Thumbnailimage/jpeg7510https://repositorio.unal.edu.co/bitstream/unal/65939/2/47615-231295-1-SM.pdf.jpg7d25423166199e396100ca3bb27a2ad2MD52unal/65939oai:repositorio.unal.edu.co:unal/659392023-05-21 23:14:16.36Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |