The Sample of Firms in Business Failure Prediction Models: Influence on Classification Results
DOI:
https://doi.org/10.46661/revmetodoscuanteconempresa.2226Keywords:
Fracaso empresarial, ratios financieros, muestreo, regresion logística, predicción, business failure, financial ratios, sampling, logistic regression, predictionAbstract
This paper focuses on the development of both failure prediction models on a paired sample and a random sample of small and medium-sized firms with head offices located in the region of Castilla y León (Spain), in order to prove if the predictive power of the developed models is affected by the method used to derive the sample aim of each study. To estimate both models, we consider a set of financial ratios as independent variables in each one, which is first reduced by the application of a principal components analysis. Next, a logistic regression analysis is applied to identify those variables that best explain and predict failure in the two samples, where differences in the significant variables and the classification results are observed, which confirms the influence of the sampling method on the business failure prediction results.Downloads
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Alfaro, E., Gámez, M. y García, N. (2008) "Linear discriminant analysis versus adaboost for failure forecasting". Revista Española de Financiación y Contabilidad, XXXVII (137), pp. 13–32.
Altman, E.I. (1968) "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy". The Journal of Finance, XXIII (4), pp. 589–609.
Altman, E.I. (1984) "The success of business failure models: An international survey". Journal of Banking & Finance, 8, pp. 171–198.
Altman, E.I., Marco, G. y Varetto, F. (1994) "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)". Journal of Banking & Finance, 18, pp. 505–529.
Balcaen, S. y Ooghe, H. (2006) "35 years of studies on business failure: an overview of the classical statistical methodologies and their related problems". The British Accounting Review, 38 (1), pp. 63–93.
Beaver, W.H. (1966) "Financial Ratios as Predictors of Failure". Journal of Accounting Research, Supplement to Vol. 4: Empirical Research in Accounting: Selected Studies, pp. 71–111.
Bell, T.B. (1997) "Neural Nets or the Logit Model? A Comparison of Each Model's Ability to Predict Commercial Bank Failures", Intelligent Systems in Accounting, Finance and Management, 6, pp. 249-264.
Betts, J. y Belhoul, D. (1987) "The effectiveness of incorporating stability measures in company failure models", Journal of Business Finance & Accounting, 14 (3), pp. 323-333.
Blum, M. (1974) "Failing Company Discriminant Analysis". Journal of Accounting Research, Spring, pp. 1–25.
Calvo-Flores, A. y García, D. (2002) "Relación entre la posición económica y financiera de la empresa y los estados de fracaso empresarial". Doldán, F. y Rodríguez, M. (Coords.) La Gestión del Riesgo de Crédito. Métodos y Modelos de Predicción de la Insolvencia Empresarial. Madrid: Ed. AECA Monografías, pp. 47–71.
Charitou, A., Neophytou, E. y Charalambous, C. (2004) "Predicting Corporate Failure: Empirical Evidence for the UK". European Accounting Review, 13 (3), pp. 465–497.
Cybinski, P. (2001) "Description, Explanation, Prediction –the Evolution of Bankruptcy Studies?". Managerial Finance, 27 (4), pp. 29–44.
Deakin, E.B. (1972) "A Discriminant Analysis of Predictors of Business Failure". Journal of Accounting Research, Spring, pp. 161–179.
Dietrich. J.R. (1984) "Discussion of Methodological Issues Related to the Estimation of Financial Distress Prediction Models". Journal of Accounting Review, 22, Studies on Current Econometric Issues in Accounting Research, pp. 83–86.
Dimitras, A.I., Slowinski, R., Susmaga, R. y Zopounidis, C. (1999) "Business failure prediction using rough sets". European Journal of Operational Research, 114 (2), pp. 263–280.
Dimitras, A.I., Zanakis, S.H. y Zopounidis, C. (1996) "A survey of business failures with an emphasis on prediction methods and industrial applications". European Journal of Operational Research, 90 (3), pp. 487–513.
Edmister, R.O. (1972) "An empirical test of financial ratio analysis for small business failure prediction". Journal of Financial and Quantitative Analysis, 7, pp. 1477–1493.
Elam, R. (1975) "The Effect of Lease Data on the Predictive Ability of Financial Ratios". The Accounting Review, 50 (1), pp. 25–43.
Gómez, M.E., de la Torre, J.M. y Román, I. (2008) "Análisis de sensibilidad temporal en los modelos de predicción de insolvencia: una aplicación a las PYMES industriales". Revista Española de Financiación y Contabilidad, XXXVII (137), pp. 85–111.
Hossari, G. (2007) "Benchmarking New Statistical Techniques in Ratio-Based Modelling of Corporate Collapse", International Review of Business Research Papers, 3 (3), pp. 141–161.
Jones, F.L. (1987) "Current Techniques in Bankruptcy Prediction". Journal of Accounting Literature, 6, pp. 131–164.
Keasey, K. y Watson, R. (1991) "Financial Distress Prediction Models: A Review of Their Usefulness". British Journal of Management, 2 (2), pp. 89–102.
Labatut, G., Pozuelo, J. y Veres, E.J. (2009) "Modelización temporal de los ratios contables en la detección del fracaso empresarial de la PYME española". Revista Española de Financiación y Contabilidad, XXXVIII (143), pp. 423–447.
Laffarga, J., Martín, J.L. y Vázquez, M.J. (1985) "El análisis de la solvencia en las instituciones bancarias: Propuesta de una metodología y aplicaciones a la Banca española". ESIC–MARKET, 48, pp. 51–73.
Laffarga, J. y Mora, A. (1998) "Los modelos de predicción de la insolvencia empresarial: un análisis crítico". Calvo-Flores, A. y García, D. (Coords.) El riesgo financiero de la empresa. Madrid: Ed. AECA Monografías, pp. 11–58.
Laffarga, J. y Pina, V. (1995) "La utilidad del análisis multivariante para evaluar la gestión continuada de empresas". Revista Española de Financiación y Contabilidad, XXIV (84), pp. 727–748.
Laitinen, E.K. (1991) "Financial ratios and different failure processes". Journal of Business, Finance & Accounting, 18 (5), pp. 649–673.
Laitinen, E.K. y Laitinen, T. (1998) "Misclassification in bankruptcy prediction in Finland: human information processing approach". Accounting, Auditing & Accountability Journal, 11 (2), pp. 216–244.
Lizarraga, F. (2002) "La utilidad de los modelos de predicción de fracaso en la empresa española a lo largo de la última década". Doldán, F. y Rodríguez, M. (Coords.) La Gestión del Riesgo de Crédito. Métodos y Modelos de Predicción de la Insolvencia Empresarial. Madrid: Ed. AECA Monografías, pp. 219–252.
Mar-Molinero, C. y Ezzamel, M. (1991) "Multidimensional Scaling Applied to Corporate Failure", Omega, 19 (4), pp. 259-274.
Mora, A. (1994) "Limitaciones metodológicas de los trabajos empíricos sobre la predicción del fracaso empresarial". Revista Española de Financiación y Contabilidad, XXIII (80), pp. 709–732.
Mora, A. (1995) "Utilidad de los modelos de predicción de la crisis empresarial". Revista Española de Financiación y Contabilidad, XXIV (83), pp. 281–300.
Mures-Quintana, M.J. y García-Gallego, A. (2012) “On the non-financial information’s significance in the business failure models: A Spanish case study”. International Journal of Organizational Analysis, 20 (4), pp. 423–434.
O’Leary, D.E. (1998) "Using Neural Networks to Predict Corporate Failure". International Journal of Intelligent Systems in Accounting, Finance & Management, 7, pp. 187–197.
Odom, M.D. y Sharda, R. (1992) "A Neural Network Model for Bankruptcy Prediction". Trippi, R. R. & Turban, E. (Eds.) Neural Networks in Finance and Investing. Using Artificial Intelligence to Improve Real–World Performance. Cambridge: Probus Publishing Company, pp. 177–185.
Ohlson, J.A. (1980) "Financial Ratios and the Probabilistic Prediction of Bankruptcy". Journal of Accounting Research, 18 (1), pp. 109–131.
Palepu, K.G. (1986) "Predicting takeover targets. A Methodological and Empirical Analysis". Journal of Accounting and Economics, 8, pp. 3–35.
Peel, M.J., Peel, D.A. y Pope, P.F. (1986). "Predicting Corporate Failure – Some Results for the UK Corporate Sector". Omega, 14 (1), pp. 5–12.
Pina, V. (1989) "La información contable en la predicción de la crisis bancaria 1977-1985". Revista Española de Financiación y Contabilidad, XVIII (58), pp. 309–338.
Pulido, A. (1992) Estadística y técnicas de investigación social, 9ª edición. Madrid: Pirámide, D.L.
Rodríguez Osuna, J. (1991) Métodos de muestreo. Madrid: Centro de Investigaciones Sociológicas.
Scheaffer, R.L., Mendenhall, W. y Ott, R.L. (2007) Elementos de muestreo, 6ª edición. Madrid: International Thomson Editores Spain Paraninfo.
Scott, E. (1981) "The Probability of Bankruptcy. A Comparison of Empirical Predictions and Theoretical Models". Journal of Banking & Finance, 5, pp. 317–344.
Slowinski, R. y Zopounidis, C. (1995) "Application of the rough set approach to evaluation of bankruptcy risk". Cited in Zopounidis, C. & Dimitras, A. I. (1998). Multicriteria Decision Aid Methods for the Prediction of Business Failure. Dordrecht: Kluwer Academic Publishers.
Taffler, R.J. (1982) "Forecasting Company Failure in the UK using Discriminant Analysis and Financial Ratio Data". Journal of the Royal Statistical Society, Series A, 145 (3), pp. 342–358.
Theodossiou, P.T. (1991) "Alternative models for assessing the financial condition of business in Greece". Journal of Business, Finance & Accounting, 18 (5), pp. 697–720.
Trujillo-Ponce, A., Samaniego-Medina, R. y Cardone-Riportella, C. (2013) “Examining what best explains corporate credit risk: accounting-based versus market-based models”. Journal of Business Economics and Management, iFirst: pp. 1–24.
Zavgren, C.V. (1983) "The prediction of corporate failure: The state of the art". Journal of Accounting Literature, 2, pp. 1–35.
Zmijewski, M.E. (1984) "Methodological Issues Related to the Estimation of Financial Distress Prediction Models". Journal of Accounting Research, 22, pp. 59–82.
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