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Publication
Os determinantes das empresas que entram no processo especial de revitalização: evidência nas empresas do setor do turismo em Portugal
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Abstract(s)
O distress financeiro sentido pelas empresas em virtude da competitividade existente nos mercados económicos, torna urgente dotar os gestores de princípios que lhes
permitam tomar decisões mais eficazes. De facto, o distress financeiro está associado a conceitos como falência, insolvência ou incumprimento financeiro, os quais têm
significados diferenciados (Habib, Costa, Huang, Bhuiyan e Sun, 2020; Altman e Hotchkiss, 2006). Os modelos de previsão de falência (e.g., Altman, 1968 e Beaver, 1966)
representam um marco importante na investigação nesta área ao iniciarem a discussão sobre os determinantes do distress financeiro.
A reestruturação de empresas surge, neste contexto, como um tópico menos explorado em que ainda não existe evidência sobre os determinantes que levam algumas empresas em forte dificuldade financeira a estratégias que lhes permitem reorganizar-se estando protegidas das ações judiciais que podem ser intentadas pelos seus credores. Esta dissertação explora esta lacuna considerando unidades empresariais do setor do turismo que aderiram ao Plano Especial de Revitalização (PER) entre 2014 e 2022. Para tal, são estimados modelos logit com base em indicadores contabilísticos (rentabilidade, dimensão, liquidez e alavancagem) e macroeconómicos para os três anos anteriores ao evento. Os resultados divulgam que a capacidade preditiva destes modelos é relevante uma vez que as percentagens de classificações corretas obtidas são de 83,3%, 75,3% e 69,5% para os anos N-1, N-2 e N-3, respetivamente. Ainda assim, a principal conclusão é que a Taxa de Juro é a única variável significativa para os três anos analisados, com o seu aumento a estar diretamente ligado à probabilidade de as empresas estudadas aderirem ao PER.
The financial distress felt by companies because of the competitiveness of the economic markets makes it urgent to equip managers with principles that enable them to make more effective decisions. In fact, financial distress is associated with concepts such as bankruptcy, insolvency, or financial default, which have different meanings (Habib, Costa, Huang, Bhuiyan and Sun, 2020; Altman and Hotchkiss, 2006). Bankruptcy prediction models (e.g. Altman, 1968 and Beaver, 1966) represent an important milestone in research in this area, as they began the discussion on the determinants of financial distress. In this context, corporate restructuring is a less explored topic in which there is still no evidence on the determinants that lead some companies in severe financial difficulty to strategies that allow them to reorganize while being protected from lawsuits that may be brought by their creditors. This dissertation explores this gap by considering business units in the tourism sector that joined the Special Revitalization Plan (PER) between 2014 and 2022. To this end, logit models are estimated based on accounting indicators (profitability, size, liquidity and leverage) and macroeconomic indicators for the three years prior to the event. The results show that the predictive capacity of these models is relevant since the percentages of correct classifications obtained are 83.3%, 75.3% and 69.5% for years N-1, N-2 and N-3, respectively. Even so, the main conclusion is that the interest rate is the only significant variable for the three years analyzed, with its increase being directly linked to the likelihood of the companies studied joining the PER.
The financial distress felt by companies because of the competitiveness of the economic markets makes it urgent to equip managers with principles that enable them to make more effective decisions. In fact, financial distress is associated with concepts such as bankruptcy, insolvency, or financial default, which have different meanings (Habib, Costa, Huang, Bhuiyan and Sun, 2020; Altman and Hotchkiss, 2006). Bankruptcy prediction models (e.g. Altman, 1968 and Beaver, 1966) represent an important milestone in research in this area, as they began the discussion on the determinants of financial distress. In this context, corporate restructuring is a less explored topic in which there is still no evidence on the determinants that lead some companies in severe financial difficulty to strategies that allow them to reorganize while being protected from lawsuits that may be brought by their creditors. This dissertation explores this gap by considering business units in the tourism sector that joined the Special Revitalization Plan (PER) between 2014 and 2022. To this end, logit models are estimated based on accounting indicators (profitability, size, liquidity and leverage) and macroeconomic indicators for the three years prior to the event. The results show that the predictive capacity of these models is relevant since the percentages of correct classifications obtained are 83.3%, 75.3% and 69.5% for years N-1, N-2 and N-3, respectively. Even so, the main conclusion is that the interest rate is the only significant variable for the three years analyzed, with its increase being directly linked to the likelihood of the companies studied joining the PER.
Description
Keywords
PER Modelo logit Reestruturação Distress financeiro Turismo