On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece

Evangelos Charalambakis and Ian Garrett ()
Additional contact information
Ian Garrett: University of Manchester

Review of Quantitative Finance and Accounting, 2019, vol. 52, issue 2, No 5, 467-491

Abstract: Abstract Using a large dataset that includes nearly 31,000 Greek private firms we examine the determinants of the probability of corporate financial distress. Using a multi-period logit model, we find that profitability, leverage, the ratio of retained earnings-to-total assets, size, the liquidity ratio, an export dummy variable, the tendency to pay out dividends and the growth rate in real GDP are strong predictors of the probability of financial distress for Greek private firms. A model including these variables exhibits the highest in-sample and out-of-sample performance in terms of correctly classifying firms that went bankrupt as more likely to go bankrupt. The predictive ability of the model remains when we increase the forecast horizon, suggesting that the model works well over short and longer time horizons.

Keywords: Corporate financial distress; Bankruptcy prediction; Private firms; Discrete hazard (multi-period logit) model; Financial statements; Greek debt crisis (search for similar items in EconPapers)
JEL-codes: C41 G13 G17 G33 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://link.springer.com/10.1007/s11156-018-0716-7 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:rqfnac:v:52:y:2019:i:2:d:10.1007_s11156-018-0716-7

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/11156/PS2

DOI: 10.1007/s11156-018-0716-7

Access Statistics for this article

Review of Quantitative Finance and Accounting is currently edited by Cheng-Few Lee

More articles in Review of Quantitative Finance and Accounting from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().