Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling

Abstract

Design/methodology/approach: Financial ratio data on 56 matched pairs of insolvent and solvent firms are analysed using logistic regression with best-subset selection criteria to identify significant ratios, and prediction accuracy is tested on an ex-ante sample. The main dimensions of ratios, and the weights that firms attach to them, are examined using 3-way Multidimensional Scaling (MDS).Findings: A parsimonious Logit model comprising one profitability, one leverage and two cash flow ratios has accuracy levels of 84.4% overall, 95.6% type I and 73.9% type II. Four financial-ratio dimensions are extracted from the MDS: (i) 'Non-strategic sales activities', (ii) 'Profitability and financial stability balance', (iii) 'Sales activities against capital conversion'; and (iv) 'Market value against cash generation'. Insolvent firms appear very specific and attach most salience to the 'Non-strategic sales activities' dimension; unlike solvent firms which attach more salience to the other three dimensions.Practical Implications: Results indicate profitability ratios should be included in GCC insolvency classification models. It is suggested that firms' managers should focus less on non-strategic sales activities to reduce susceptibility to insolvency. Originality/value:The study provides empirical evidence on insolvency in the GCC and introduces the application of 3-way MDS to insolvency research in the region.

A dimensional analysis of stakeholder assessment of project outcomes

“…It is usual to specify the number of dimensions to retain in the 3-way MDS model a priori. As in the case of prior studies such as Chipulu et al (2013) and Khoja et al (2016), we employed a separate, independent model to aid this decision. First, we extracted five samples from the dataset using bootstrapping.…”

“…These served as our primary identifiers for each dimension. Researchers such as Carroll and Green (1997) and Khoja et al (2016) tend to either use adjunct techniques such as clustering or theory to help them interpret the dimensions. We interpreted each dimension based on its similarity to the six dimensions we had earlier identified a priori from the literature.…”

How commuters’ motivations to drive relate to propensity to carpool: Evidence from the United Kingdom and the United States

“…Determining how many dimensions to retain is a critical part of MDS. This study adopted a strategy that other researchers (e.g., Chipulu et al, 2013;Khoja et al, 2014;Neophytou and Mar Molinero, 2004) have used. First we decided the number of dimensions to retain, independently, prior to the actual MDS analysis.…”

“…extracting a parsimonious solution with interpretable dimensions versus extracting maximal variance. It is dilemma common to all data reduction techniques and there are number of prior examples of the application of this compromise approach with MDS models (e.g., Chipulu et al, 2013;Khoja et al, 2014;Neophytou and Mar Molinero, 2004) because it is considered an appropriate way to handle this unavoidable problem.…”

Characterisation of survivability resilience with dynamic stock interdependence in financial networks

“…In the stock market, the survivability is termed to illustrate the ability of stocks/listed firms to prevent corporate failure/bankruptcy or being delisted from the market. Categorising and predicting corporate failure is essential in bankruptcy studies (Khoja et al 2016) because it is of great importance in providing early warnings about a company’s financial distress to stakeholders, business managers, policy-makers, and financial economists (Amendola et al 2017; Jones et al 2017) and it is hard to be characterised and predicted (Allen and Babus 2009). …”