Foremost features affecting financial distress and Bankruptcy in the acute stage of COVID-19 crisis

Bozkurt İ., Kaya M. V.

Applied Economics Letters, vol.30, no.8, pp.1112-1123, 2023 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 8
  • Publication Date: 2023
  • Doi Number: 10.1080/13504851.2022.2036681
  • Journal Name: Applied Economics Letters
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, IBZ Online, International Bibliography of Social Sciences, ABI/INFORM, Business Source Elite, Business Source Premier, CAB Abstracts, EconLit, Geobase, Public Affairs Index, Veterinary Science Database, DIALNET
  • Page Numbers: pp.1112-1123
  • Keywords: Bankruptcy, financial distress, COVID-19 Crisis, random forest algorithm, PREDICTION
  • Ankara Haci Bayram Veli University Affiliated: No

Abstract

This paper investigates the foremost firm-specific factors having an impact on financial distress and bankruptcy in the acute stage of the Covid-19 crisis based on data from approximately 9,000 enterprises in 25 countries. Empirical results of a random forest algorithm with SHAP values show increased odds of both bankruptcy and financial distress for firms that have problems in accessing finance, younger firms and more indebted firms. In addition, the size of the firm and the years of experience of its managers also have an impact on financial failure. However, country features are more important than firm features in predicting bankruptcy and financial distress in the Covid-19 crisis.