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Financial versus Non-Financial Information for Default Prediction: Evidence from Sri Lanka and the USA

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  • Jayasuriya Mahapatabendige Ruwani Fernando
  • Leon Li
  • Greg Hou

Abstract

We report the effectiveness of corporate governance variables (GOVs) in default prediction, in a comparative study between Sri Lanka and the USA. Twelve GOVs are tested in addition to the standard financial data. A panel logit model framework is employed to conduct empirical tests on 730 Sri Lankan and 3280 USA observations from 2000 to 2015. Whilst an integrated model provides overall stronger predictive value; financial information is more relevant for USA firms. GOVs appear more relevant in emerging markets than in mature markets, but the effectiveness of the individual GOVs differs between countries.

Suggested Citation

  • Jayasuriya Mahapatabendige Ruwani Fernando & Leon Li & Greg Hou, 2020. "Financial versus Non-Financial Information for Default Prediction: Evidence from Sri Lanka and the USA," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(3), pages 673-692, February.
    • Handle: RePEc:mes:emfitr:v:56:y:2020:i:3:p:673-692
    DOI: 10.1080/1540496X.2018.1545644
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