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Authors
Abstract(s)
A evolução do desempenho empresarial das pequenas e médias empresas é crucial para o sucesso do processo de ajustamento da economia Ibérica. De acordo com dados divulgados pelo Banco de Portugal, na sua Nota de Informação Estatística (março de 2015), o setor da metalurgia e metalomecânica apresenta uma elevada abertura ao exterior, o que significa que uma parte significativa do seu volume de negócios resulta das exportações. Nesse contexto, o nosso objetivo foi desenvolver um modelo empírico que identificasse os fatores considerados determinantes no processo de previsão de uma situação de insolvência, utilizando para o efeito um painel longitudinal de dados analisado recorrendo a diferentes metodologias, como é o caso da Análise Discriminante Múltipla, Análise Logística e Análise de Matching. Este estudo pioneiro, baseado numa amostra de pequenas e médias empresas de Portugal e Espanha pertencentes ao ramo de atividade da indústria transformadora e do setor da metalurgia e metalomecânica. Os dados que utilizados estão compreendidos entre os exercícios económicos 2010 a 2018 e a fonte dos dados é a base de dados SABI. As variáveis selecionadas para o modelo final foram a Rentabilidade Económica, o Imposto / Ativo, a Solvabilidade, o Endividamento Global e a Rotação Ativo. Após ter sido sujeito a diferentes testes de robustez, o comportamento do modelo final manteve-se estável. A capacidade preditiva do modelo final prevê corretamente mais de 99% das observações. Este comportamento é semelhante quando se testa o modelo para um, dois e três anos antes da situação de insolvência. Conclui-se também que o modelo é estatisticamente significativo e que apresenta uma percentagem de classificação correta de 71,87%.
The evolution of the business performance of small and medium companies is crucial for the success of the process of adjustment of the Iberian economy. According to data released by Banco de Portugal in its Statistical Information Note (March 2015), the metallurgy and metalworking sector is highly open to the outside, which means that a significant part of its turnover results from exports. In this context, our objective was to develop an empirical model that identified the factors considered determinants in the process of forecasting an insolvency situation, using a longitudinal panel of data analysed using different methodologies, as is the case of Multiple Discriminant Analysis, Logistic Analysis and Matching Analysis. This pioneering study based on a sample of small and medium-sized companies from Portugal and Spain belonging to the manufacturing sector of the metallurgy and metalworking sector. The data used are comprised between the financial years 2010 to 2018 and the source of the data is the SABI database. The variables selected for the final model were the variables Economic Profitability, Income Tax / Asset, Solvency, Global Debt and Asset Rotation. After being subjected to different robustness tests, the behaviour of the final model remained stable. The predictive capacity of the final model correctly predicts more than 99% of the observations. This behaviour is similar when testing the model for one, two and three years before the insolvency situation. It is also concluded that the model is statistically significant and that it presents a percentage of correct classification of 71.87%.
The evolution of the business performance of small and medium companies is crucial for the success of the process of adjustment of the Iberian economy. According to data released by Banco de Portugal in its Statistical Information Note (March 2015), the metallurgy and metalworking sector is highly open to the outside, which means that a significant part of its turnover results from exports. In this context, our objective was to develop an empirical model that identified the factors considered determinants in the process of forecasting an insolvency situation, using a longitudinal panel of data analysed using different methodologies, as is the case of Multiple Discriminant Analysis, Logistic Analysis and Matching Analysis. This pioneering study based on a sample of small and medium-sized companies from Portugal and Spain belonging to the manufacturing sector of the metallurgy and metalworking sector. The data used are comprised between the financial years 2010 to 2018 and the source of the data is the SABI database. The variables selected for the final model were the variables Economic Profitability, Income Tax / Asset, Solvency, Global Debt and Asset Rotation. After being subjected to different robustness tests, the behaviour of the final model remained stable. The predictive capacity of the final model correctly predicts more than 99% of the observations. This behaviour is similar when testing the model for one, two and three years before the insolvency situation. It is also concluded that the model is statistically significant and that it presents a percentage of correct classification of 71.87%.
Description
Versão final (Esta versão contém as críticas e sugestões dos elementos do júri)
Keywords
Insolvência Metalomecânico Ibéricas PME Insolvency Metal-mechanic Iberian SME