Forecasting Bankruptcy for SMEs Using Hazard Function: To What Extent Does Size Matter?

Gupta, Jairaj; Gregoriou, Andros; Healy, Jerome

doi:10.2139/ssrn.2222626

Cited by 6 publications

(14 citation statements)

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“…In addition, we forecast the bankruptcy probabilities by developing discrete-time duration-dependant hazard models. Our paper is a continuation and improvement of three papers in the literature of SMEs failure: Altman and Sabato (2007), Holmes et al (2010), and Gupta et al (2014). We differ from Altman and Sabato's (2007) paper in two ways.…”

Section: Introductionmentioning

confidence: 97%

“…These categories are classified in terms of the firms' management style (Wager, 1998), access to finance (Beck et al, 2006), the number of employees (Gupta et al, 2014) etc. However, a limited literature in 3…”

Section: Introductionmentioning

confidence: 99%

“…The Effect of Size on the Failure Probabilities of SMEs 3 this area has been devoted to studying the credit risk behaviour of these different categories (see, for example, Gupta et al (2014)). In our study, we will address this research gap by classifying SMEs into three distinct categories (micro, small, and medium) while developing a bankruptcy prediction model using a set of financial ratios.…”

Section: Introductionmentioning

confidence: 99%

“…Second, from a methodological point of view, while applying discreet hazard models, the estimation of baseline hazard should be done using time dummies (Beck et al, 1998) or some other functional form of time (Jenkins, 2005). However, Gupta et al (2014) The analysis is carried out on a sample of 11,117 US non-financial firms from which 465 are defaulted firms, spanning the time period from 1980 till 2013. Our empirical findings show that significant differences exist between the bankruptcy attributes of micro and small firms on one hand and SMEs firms on the other.…”

Section: Introductionmentioning

confidence: 99%

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The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model

Kalak

Hudson

2016

International Review of Financial Analysis

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(2016) The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model. AbstractThis paper investigates the extent to which the size affects the SMEs probabilities of bankruptcy.Using a dataset of (11,117) US non-financial firms, of which (465) filed for insolvency under chapters 7/11 between 1980 and 2013. We forecast the bankruptcy probabilities by developing four discretetime duration-dependant hazard models namely SMEs, Micro, Small, and Medium. A comparison of the default prediction models for medium firms and SMEs suggest that almost an identical set of explanatory variables affect the default probabilities leading us to believe that there is no material impact on the decision-making process by treating each of these groups separately. However, comparisons between the micro and small firms with the SMEs firms strongly suggest that they need to be considered separately while modelling credit risk for them.JEL classification:

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model

Kalak

Hudson

2016

International Review of Financial Analysis

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“…Despite the fact that the companies in the database differ widely in their capital structure, firm size, access to external finance, management style, number of employees, the risk of financial failure can be modelled using the same set of independent variables for both prosperous and non-prosperous companies, which is confirmed by the study of Gupta et al [62]. This knowledge leads to the identification of factors, which are significant enough to manage financial risks, and to affect the profitability and prosperity of the company.…”

Section: Discussionmentioning

confidence: 68%

Financial Risk Measurement and Prediction Modelling for Sustainable Development of Business Entities Using Regression Analysis

et al. 2018

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Abstract:The issue of the debt, bankruptcy or non-bankruptcy of a company is presented in this article as one of the ways of conceiving risk management. We use the Amadeus database to obtain the financial and accounting data of Slovak enterprises from 2015 and 2016 to calculate the most important financial ratios that may affect the financial health of the company. The main aim of the article is to reveal financial risks of Slovak entities and to form a prediction model, which is done by the identification of significant predictors having an impact on the health of Slovak companies and their future prosperity. Realizing the multiple regression analysis, we identified the significant predictors in conditions of the specific economic environment to estimate the corporate prosperity and profitability. The results gained in the research are extra important for companies themselves, but also for their business partners, suppliers and creditors to eliminate financial and other corporate risks related to the unhealthy or unfavorable financial situation of the company.

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A change in the importance of mortality factors throughout the life cycle stages of small businesses

et al. 2016

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The aim of this paper is to describe the mortality factors and the change in the importance of these factors throughout the life cycle stages of small businesses. Research on mortality of small businesses ignores the characteristics of small businesses and the life cycle stage they are at the time of closure. A systematic mapping study was conducted to explore the literature on mortality factors in small businesses and understand the state of the art of the theme. The relevance of mortality factors distributed among three categories: owner-manager, business and environment have changed throughout businesses life cycle stages. Such variation states one of the main life cycle theory assumptions that a factor can have a beneficial influence during one specific stage and a negative influence during another stage. The attention given to the variation of importance of mortality factors during businesses life cycles results in implications for all those concerned in strengthening small businesses.

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Forecasting Bankruptcy for SMEs Using Hazard Function: To What Extent Does Size Matter?

Cited by 6 publications

References 0 publications

The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model

The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model

Financial Risk Measurement and Prediction Modelling for Sustainable Development of Business Entities Using Regression Analysis

A change in the importance of mortality factors throughout the life cycle stages of small businesses

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