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Bootstrap Replacement to Validate the Influence of the Economic Cycle on the Structure and the Accuracy Level of Business Failure Prediction Models
Author(s) -
Manzaneque Montserrat,
GarcíAPérezDeLema Domingo,
Antón Renart Marcos
Publication year - 2015
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.2327
Subject(s) - business cycle , recession , business failure , econometrics , predictive modelling , stability (learning theory) , computer science , economics , financial crisis , macroeconomics , machine learning
The aim of this study was to answer the question of how the economic cycle affects the stability and efficiency of business failure prediction models, using bootstrap replacement method for validation. We analyse 2228 Spanish small and medium‐sized enterprises for the period 2001–2009, and divide it into three different phases of the economic cycle (growth, crisis, recession). We find that the structure and the ability of business failure prediction models are different according to the economic cycle. These findings are relevant for the debate on the most suitable financial ratios when developing business failure prediction models and to pose their accuracy level in these prediction models. Copyright © 2015 John Wiley & Sons, Ltd.