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Investigating corporate insolvency in the Gulf Cooperation Council: multiple-perspective studies

Investigating corporate insolvency in the Gulf Cooperation Council: multiple-perspective studies
Investigating corporate insolvency in the Gulf Cooperation Council: multiple-perspective studies
This thesis focuses on the causes of corporate insolvency, and understanding the characteristics of insolvency risk in the Gulf Cooperation Council (GCC). Multiple studies are employed to address some of the gaps which have been identified in the literature. The first study analyses corporate insolvency in the GCC region between 2004 and 2011 using multiple methodologies: a Logit model, supplemented by a Probit model and a 3-way MDS model, which enables the visualisation of key differences between insolvent and solvent firms, supplemented by Hierarchical Cluster Analysis. The Logit regression with best-subset selection criteria suggests that profitability and leverage ratios, as well as cash flow-based ratios, can predict insolvency in GCC literature. MDS results indicate that insolvent firms attach most salience to the ‘Non-strategic sales activities', unlike solvent firms which attach more salience to the other dimensions: 'Profitability and financial stability balance’, ‘Sales activities against capital conversion’, and ‘Market value against cash generation’. Hence, the results suggest that firms’ managers should focus less on non-strategic sales activities to reduce susceptibility to insolvency. Taking a multilevel perspective, the second study attempts to contextualise the nature of corporate insolvency in the GCC, using samples of firms from the UK and the USA as comparators. MDS and cluster analysis reveal four dimensions of ratios across the samples: 'effectiveness of sales and cash-generating activities ', 'trade-off between debt management and cash generation/profitability', 'usage of debt versus usage of own assets', and 'trade-off between profitability and cash-generating activities'. Unlike solvent firms, insolvent GCC firms appear very specific in the third dimension, 'usage of debt versus usage of own assets’, which did not appear as associated with macroeconomic variables. The third study is to examine the dynamic causal relationships among macroeconomic indicators of the corporate failure rate in the GCC region by using the Autoregressive Distributed Lag model (ARDL) bound test, which use quarterly dataset. These results provide evidence that oil prices in the GCC region combined with other macroeconomic indicators have an impact on the failure rate in the long-run equilibrium. In terms of the short-run, the ARDL model confirmed that the corporate failure rate is mainly determined by the previous period’s failure rate.
University of Southampton
Khoja, Layla
fd10edc5-f537-41ac-a9f1-40ccb2e1b425
Khoja, Layla
fd10edc5-f537-41ac-a9f1-40ccb2e1b425
Chipulu, Maxwell
12545803-0d1f-4a37-b2d2-f0d21165205e

Khoja, Layla (2014) Investigating corporate insolvency in the Gulf Cooperation Council: multiple-perspective studies. University of Southampton, Southampton Business School, Doctoral Thesis, 167pp.

Record type: Thesis (Doctoral)

Abstract

This thesis focuses on the causes of corporate insolvency, and understanding the characteristics of insolvency risk in the Gulf Cooperation Council (GCC). Multiple studies are employed to address some of the gaps which have been identified in the literature. The first study analyses corporate insolvency in the GCC region between 2004 and 2011 using multiple methodologies: a Logit model, supplemented by a Probit model and a 3-way MDS model, which enables the visualisation of key differences between insolvent and solvent firms, supplemented by Hierarchical Cluster Analysis. The Logit regression with best-subset selection criteria suggests that profitability and leverage ratios, as well as cash flow-based ratios, can predict insolvency in GCC literature. MDS results indicate that insolvent firms attach most salience to the ‘Non-strategic sales activities', unlike solvent firms which attach more salience to the other dimensions: 'Profitability and financial stability balance’, ‘Sales activities against capital conversion’, and ‘Market value against cash generation’. Hence, the results suggest that firms’ managers should focus less on non-strategic sales activities to reduce susceptibility to insolvency. Taking a multilevel perspective, the second study attempts to contextualise the nature of corporate insolvency in the GCC, using samples of firms from the UK and the USA as comparators. MDS and cluster analysis reveal four dimensions of ratios across the samples: 'effectiveness of sales and cash-generating activities ', 'trade-off between debt management and cash generation/profitability', 'usage of debt versus usage of own assets', and 'trade-off between profitability and cash-generating activities'. Unlike solvent firms, insolvent GCC firms appear very specific in the third dimension, 'usage of debt versus usage of own assets’, which did not appear as associated with macroeconomic variables. The third study is to examine the dynamic causal relationships among macroeconomic indicators of the corporate failure rate in the GCC region by using the Autoregressive Distributed Lag model (ARDL) bound test, which use quarterly dataset. These results provide evidence that oil prices in the GCC region combined with other macroeconomic indicators have an impact on the failure rate in the long-run equilibrium. In terms of the short-run, the ARDL model confirmed that the corporate failure rate is mainly determined by the previous period’s failure rate.

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More information

Published date: September 2014
Organisations: University of Southampton, Southampton Business School

Identifiers

Local EPrints ID: 377723
URI: http://eprints.soton.ac.uk/id/eprint/377723
PURE UUID: 67cbf76e-5acf-4158-930b-15486e72b3b0
ORCID for Maxwell Chipulu: ORCID iD orcid.org/0000-0002-0139-6188

Catalogue record

Date deposited: 10 Jul 2015 16:05
Last modified: 15 Mar 2024 05:17

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Contributors

Author: Layla Khoja
Thesis advisor: Maxwell Chipulu ORCID iD

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