Insolvency administration as a strategic response to financial distress

Routledge, James; Morrison, David

doi:10.1177/0312896211428494

Cited by 7 publications

(8 citation statements)

References 73 publications

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“…2 While other statistical models analyse an event’s probability using variables based on data at one time point (e.g. logistic regression), survival analysis accommodate changes in the probability of the event due to changes in the values of variables over time (Routledge and Morrison, 2012). That is, it provides the probability that financial distress will occur at a time T that lies beyond the time horizon t , for a range of values of t .…”

Section: Advances In Bankruptcy Prediction Modelsmentioning

confidence: 99%

Dynamic forecasts of financial distress of Australian firms

Kim

Partington

2014

Australian Journal of Management

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Dynamic forecasts of financial distress have received far less attention than static forecasts, particularly in Australia. This study, therefore, investigates dynamic probability forecasts for Australian firms. Novel features of the modelling are the use of time-varying variables in forecasts from a Cox model. Not only is this one of relatively few studies to apply dynamic variables in forecasting financial distress, but to the authors' knowledge it is the first to provide forecasts of survival probabilities using the Cox model with time-varying variables. Forecast accuracy is evaluated using receiver operating characteristics curves and the Brier Score. It was found that the dynamic model had superior predictive power, in out-of-sample forecasts, to the traditional Cox model and to the logit model. Graham PartingtonBusiness School, The University of Sydney, Australia AbstractDynamic forecasts of financial distress have received far less attention than static forecasts, particularly in Australia. This study, therefore, investigates dynamic probability forecasts for Australian firms. Novel features of the modelling are the use of time-varying variables in forecasts from a Cox model. Not only is this one of relatively few studies to apply dynamic variables in forecasting financial distress, but to the authors' knowledge it is the first to provide forecasts of survival probabilities using the Cox model with time-varying variables. Forecast accuracy is evaluated using receiver operating characteristics curves and the Brier Score. It was found that the dynamic model had superior predictive power, in out-of-sample forecasts, to the traditional Cox model and to the logit model.

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Section: Advances In Bankruptcy Prediction Modelsmentioning

confidence: 99%

Dynamic forecasts of financial distress of Australian firms

Kim

Partington

2014

Australian Journal of Management

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“…Prior Australian evidence on corporate decline has focused on examining factors discriminating between failing (bankruptcy) and non-failing firms. This includes studies by Castagna and Matolcsy (1981), Crapp and Stevenson (1987), Izan (1984), Kim and Partington (2014) and Yim and Mitchell (2007) developing corporate failure prediction models, and Al-Hadi et al (2017), Chapple and Routledge (2018), Magee (2012), Miglani et al (2015), Routledge and Gadenne (2000) and Routledge and Morrison (2012) which relate corporate governance attributes and other corporate decision-making with financial distress or voluntary administration outcomes. While predicting or identifying firm failure or termination is important, particularly from the perspective of shareholders, it is arguably more useful if intervention action or influences can be identified prior to the ultimate failure stage being reached.…”

Section: Introductionmentioning

confidence: 99%

Corporate governance and turnaround: Evidence from Australia

Miglani¹,

Ahmed

Henry

2020

Australian Journal of Management

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We examine the relationship between ownership and outside director attributes and corporate turnaround outcomes using matched samples of 99 turnaround and 99 non-turnaround listed Australian firms during the 2004–2015 period. Based on agency theory principles, we propose that key shareholder groups (block ownership, director ownership, institutional ownership) and outside directors are related to firm-level turnaround outcomes, and particularly changes in these attributes across decline to turnaround periods. Our results provide evidence that turnaround and non-turnaround firms differ in terms of their ownership and board composition structures, and that changes in director ownership and the degree of board independence are important in determining the likelihood of turnaround success. JEL Classification: G33, G34, M40

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“…(); Nartea et al . (), Bugeja and Sinelnikov (); Jian and Xu (); Routledge and Morrison (); Nguyen and Rahman ().…”

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confidence: 99%

Investment–cash flow sensitivity measures investment thirst, but not financial constraint

Deng

Ding

Zhu

et al. 2015

Accounting & Finance

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Literature streams disagree about the capacity of investment-cash flow sensitivity (ICFS) to measure both investment thirst and financial constraint. We argue that ICFS measures the former but not the latter. Therefore, we use Fazzari et al. 's study (1988) to develop a model to test the relationship between ICFS and financial constraint, but extend that model using Kornai (1979) to include investment thirst. We demonstrate: because the ICFS-financial constraint relationship varies, ICFS cannot measure financial constraint. Conversely, using a natural experiment of China's Four Trillion Stimulus policy, we show ICFS significantly and positively correlates with investment thirst after controlling for financial constraint.

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Insolvency administration as a strategic response to financial distress

Cited by 7 publications

References 73 publications

Dynamic forecasts of financial distress of Australian firms

Dynamic forecasts of financial distress of Australian firms

Corporate governance and turnaround: Evidence from Australia

Investment–cash flow sensitivity measures investment thirst, but not financial constraint

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