Affiliation:
1. Department of Production and Systems Engineering, School of Engineering, University of Minho, Braga, Portugal
2. ALGORITMI Research Centre, University of Minho, Braga, Portugal
Abstract
<abstract>
<p>The importance of macroeconomic indicators on the performance of bankruptcy prediction models has been a contentious issue, due in part to a lack of empirical evidence. Most indicators are primarily centered around a company's internal environment, overlooking the impact of the economic cycle on the status of the company. This research brings awareness about the combination of microeconomic and macroeconomic factors. To do this, a new model based on logistic regression was combined with principal component analysis to determine the indicators that best explained the variations in the dataset studied. The sample used comprised data from 1,832 Portuguese construction companies from 2009 to 2019. The empirical results demonstrated an average accuracy rate of 90% up until three years before the bankruptcy. The microeconomic indicators with statistical significance fell within the category of liquidity ratios, solvency and financial autonomy ratios. Regarding the macroeconomic indicators, the gross domestic product and birth rate of enterprises proved to increase the accuracy of bankruptcy prediction more than using only microeconomic factors. A practical implication of the results obtained is that construction companies, as well as investors, government agencies and banks, can use the suggested model as a decision-support system. Furthermore, consistent use can lead to an effective method of preventing bankruptcy by spotting early warning indicators.</p>
</abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Development,Geography, Planning and Development
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献