 Development and testing of an augmented distress prediction model: A comparative study on a developed and an emerging marketSumaira Ashraf, Elisabete Félix and Zélia Serrasqueiro Journal of Multinational Financial Management, 2020, vol. 57-58 Abstract: This study presents a financial distress (FD) prediction model that utilizes accounting, market-based, and financial reporting quality (FRQ) measures. We use a panel logit framework to analyze data for developed market firms from the UK and emerging market firms from Pakistan during the period 2001-2015. Obscured portions of financial reports, such as that created by management tactics employing income smoothing, can be measured with FRQ proxies. Our results find that such FRQ measures have significant influence on the accuracy of distress prediction modeling, in both the UK and Pakistani markets. Further, we validate the performance of our models through a fully non-linear classifier known as random forest methodology. Our robustness checks reveal that the predictive accuracy of our model remains high during different tranches of the business cycle and across different econometric techniques. Keywords: Financial distress; Panel logit analysis; Random forest methodology; Financial reporting quality; Earning management (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:mulfin:v:57-58:y:2020:i::s1042444x20300487 DOI: 10.1016/j.mulfin.2020.100659 Access Statistics for this article Journal of Multinational Financial Management is currently edited by I. Mathur and G. G. Booth More articles in Journal of Multinational Financial Management from Elsevier |
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