Insolvency regimes and firms' default risk under economic uncertainty and shocks

Gopalakrishnan, Balagopal; Mohapatra, Sanket

doi:10.1016/j.econmod.2020.06.005

Cited by 25 publications

(18 citation statements)

References 72 publications

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“…The increased usage of digital technologies constantly generates new industrial growth points, providing tremendous force for the long-term development of new energy enterprises (Jabłoński, 2018). Besides, scholars also investigate how the digital economy impacts enterprise business models (Tan et al, 2007), organizational structures (Nuryaman, 2015), governance mechanisms (Gopalakrishnan and Mohapatra, 2020), Etc.…”

Section: Open Access Edited Bymentioning

confidence: 99%

The digital economy and corporate credit risk: An empirical study based on Chinese new energy enterprises

Yu²,

Cui³

2023

Front. Energy Res.

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The integration of digital technologies is exhibiting an upward trend in Chinese enterprises, and the degree of corporate credit risk is directly proportional to their financial sustainability. Based on panel data of new energy enterprises from 2012 to 2020, this article makes an empirical study on the direct effect, mediating effect, and moderating effect of the digital economy (DE) on the new energy enterprises’ credit risk. It is found that the digital economy could significantly mitigate the credit risk of new energy enterprises by improving total factor productivity and amplifying the potential default cost. When the digital economy affects corporate credit risk, the development of the new energy industry acts as an intermediary, and knowledge spillover acts as a moderator. Furthermore, considering knowledge spillover as the threshold variable, the digital economy has a double-threshold effect. The marginal impact fluctuates from dropping to increasing as the knowledge spillover level increases. As for the region’s heterogeneity, the digital economy has benefited eastern China more than central and western China, possibly due to the differences in economic structure, capital intensity, and policy institutions. In view of these findings, this study provides a reference for China to mitigate corporate credit risk in the digital economy era.

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Section: Open Access Edited Bymentioning

confidence: 99%

The digital economy and corporate credit risk: An empirical study based on Chinese new energy enterprises

Yu²,

Cui³

2023

Front. Energy Res.

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“…Using a large cross-country firm-level dataset, Gopalakrishnan and Mohapatra [31] demonstrated that companies with higher cash flows and higher growth often have higher Z-scores, indicating a lesser propensity to default. Asset tangibility is linked to default risk because businesses with more tangible assets have lower Z-scores.…”

Section: Firm Specific Determinants Of Probability Of Defaultmentioning

confidence: 99%

“…Fama et al [46,47] found that economic conditions significantly affect the probability of default. Gopalakrishnan and Mohapatra [31] found that that firms in countries with higher GDP growth tend to have a lower likelihood of default. Schuermann et al [48] showed that the interrelationship between the condition of the economy and firms is the main driver of defaults.…”

Section: Macroeconomic Factors Affecting Probability Of Defaultmentioning

confidence: 99%

Firm Specific and Macroeconomic Determinants of Probability of Default: A Case of Pakistani Non-Financial Sector

Hamid¹,

Siddiqui²

2023

IJSDP

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This study extends the literature on the capital structure by examining the effect of firm specific and macroeconomic factors on probability of default using 2385 firm year observations of Non-financial firms listed on Pakistan Stock Exchange (PSX) for the period 1998 to 2021. This is the first study that used a large dataset to analyze the default risk of Pakistani listed non-financial companies. This study follows Bharat and Shumway (2008) methodology to calculate expected default probability, which is a simplified version of the Merton (1974) structural default model. Fixed effect model has been used for data analysis. The empirical results of firm specific variables show that growth, operating cash flow ratio, liquidity, and performance is negatively related with the probability of default while leverage and tangibility of assets are positively related with the probability of default. Size of the company has no relationship with the probability of default. Macroeconomic variables economic conditions measured by GDP growth rate and index return have negative while short term interest rate have positive impact on probability of default. This study may be beneficial to the managers of non-financial companies since it may help them become more aware of the consequences of default risk and may also help them build effective policies linked to managing default risk. The board of directors of non-financial companies can extract valuable information from this study which is required to conduct control measures related to default risk management. The study excluded financial firm because those have different capital structure as compared to non-financial firms. Further studies can also investigate the effect of firm-specific factors and macroeconomic factors in different sectors to check is there any difference in results on sector basis.

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“…The marketing aspects of credit risk management were emphasized by E. Webb & S. Shu (2018), the influence of borrowers' default on the level of credit risk of banking institutions was studied by B. Gopalakrishnan & S. Mohapatra (2020). Estimation of credit risks in agriculture in terms of natural and climatic conditions is rather specific, which was outlined in papers by O.…”

Section: Introductionmentioning

confidence: 99%

Credit Risk Management: Marketing Segmentation, Modeling, Accounting, Analysis and Audit

Косова¹,

SMERICHEVSKYI²,

YAROSHEVSKA³

et al. 2022

Scientific Horizons

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The relevance of the research is determined by the urgency of implementing the systems of credit risk management in bank activities based on the international accounting and reporting standards. The high level of complexity of the mentioned problem is related to a significant number of credit market segments and a variety of credit forms. The aim of the research paper is to identify the risk level of individual segments in the loan portfolio at the microeconomic level taking into account macroeconomic factors. The research methods used to identify the credit risk are migration matrices, nonlinear approximation, correlation-regression analysis, statistical distributions, and forecasting. The main research results are as follows: credit segmentation of the loan portfolio was performed, a matrix of credit risk sources was constructed, default probability and default losses were quantified to reflect the expected credit losses in accounting, and the audit of construction of credit risk models was performed. The significance of the research results is determined by the possibility to measure the factors of non-stable macroeconomic situation in Ukraine while estimating the risks of functioning of banking establishments. The proposed approaches to solving the problem of credit risk management allow decreasing the volume of non-operating credits and increasing the profitability of the loan portfolio of a bank. It can be considered that the merits of the research are determining the causal relations between the separate components of credit risk, which can be effectively used to neutralize and decrease them. The emphasis was made on the tools of credit risk management represented by marketing segmentation, modeling, accounting, analysis, and audit. The prospects of further studies include clarification of the methodical approaches to credit risk management in part of the separate market segments

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Insolvency regimes and firms' default risk under economic uncertainty and shocks

Cited by 25 publications

References 72 publications

The digital economy and corporate credit risk: An empirical study based on Chinese new energy enterprises

The digital economy and corporate credit risk: An empirical study based on Chinese new energy enterprises

Firm Specific and Macroeconomic Determinants of Probability of Default: A Case of Pakistani Non-Financial Sector

Credit Risk Management: Marketing Segmentation, Modeling, Accounting, Analysis and Audit

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