Macroeconomic determinants of credit risk: Evidence from the Eurozone

Carvalho, Paulo Viegas de; Curto, José Dias; Primor, Rodrigo

doi:10.1002/ijfe.2259

Cited by 11 publications

(20 citation statements)

References 59 publications

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“…Macroeconomic information improves the accuracy of models anticipating non-financial business credit default. These findings are supported by previous studies on Oman, Sri Lanka, Nigeria, and Zambia (Kharusi and Ada, 2018;Madhuhansi and Shantha, 2021;Carvalho et al, 2020). The present study confirms the positive and negative links between total gross external debt, GDP, and non-performing loans, emphasizing the importance of monitoring external debt levels for economic stability.…”

Section: Macroeconomic Cyclical Indicatorssupporting

confidence: 91%

Macroeconomic cyclical indicators and bank non-performing loans: does country governance matter in African countries?

Ahiase,

Andriana,

Agbemava

et al. 2023

IJSE

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PurposeThe purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.Design/methodology/approachData was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.FindingsThe findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.Research limitations/implicationsThe focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.Practical implicationsPolicymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.Originality/valueThis paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

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Section: Macroeconomic Cyclical Indicatorssupporting

confidence: 91%

Macroeconomic cyclical indicators and bank non-performing loans: does country governance matter in African countries?

Ahiase,

Andriana,

Agbemava

et al. 2023

IJSE

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“…The goal is to increase the understanding of underlying macroeconomic causes of credit risk and predict the macroeconomic variables to which credit risk is most sensitive with accuracy (high-and low-credit-risk zones). This will enable beneficiaries to deploy control mechanisms to prevent projected credit losses and maintain adequate reserves to comply with UK regulatory norms [4]. This section discusses the credit risk predictive model's development and comparison to select the most accurate model using measures like the confusion matrix and receiver operating characteristic curve (ROC).…”

Section: Discussionmentioning

confidence: 99%

“…The 2008 global crisis revealed the interwoven nature of banking and macroeconomic indicators such as unemployment, inflation, etc. Also, it showed that a negative shift in macroeconomic indicators such as the unemployment rate, inflation, GDP, etc., initiates a vicious cycle, causing financial stress in the ecosystem [4]. Since COVID-19, global financial circumstances have deteriorated and are becoming worse because of the Russia-Ukraine war.…”

Section: Introductionmentioning

confidence: 99%

Analysing the Influence of Macroeconomic Factors on Credit Risk in the UK Banking Sector

Sharma,

Andhalkar,

Ajao

et al. 2024

Analytics

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Macroeconomic factors have a critical impact on banking credit risk, which cannot be directly controlled by banks, and therefore, there is a need for an early credit risk warning system based on the macroeconomy. By comparing different predictive models (traditional statistical and machine learning algorithms), this study aims to examine the macroeconomic determinants’ impact on the UK banking credit risk and assess the most accurate credit risk estimate using predictive analytics. This study found that the variance-based multi-split decision tree algorithm is the most precise predictive model with interpretable, reliable, and robust results. Our model performance achieved 95% accuracy and evidenced that unemployment and inflation rate are significant credit risk predictors in the UK banking context. Our findings provided valuable insights such as a positive association between credit risk and inflation, the unemployment rate, and national savings, as well as a negative relationship between credit risk and national debt, total trade deficit, and national income. In addition, we empirically showed the relationship between national savings and non-performing loans, thus proving the “paradox of thrift”. These findings benefit the credit risk management team in monitoring the macroeconomic factors’ thresholds and implementing critical reforms to mitigate credit risk.

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“…Brunel [10] provided a comprehensive survey of PD analytics methodology. To explore the impact of GDP growth on PD, Carvalho et al [11] observed that with a negative effect on the PD, GDP growth is the most significant among the key macroeconomic predictors of default. However, they also report that reduced PD due to economic growth mostly occurs in economies more exposed to conditions of financial stress.…”

Section: Literature Reviewmentioning

confidence: 99%

Goodness-of-Fit of Logistic Regression of the Default Rate on GDP Growth Rate and on CDX Indices

Lin

Ching³

et al. 2021

Mathematics

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Under the Basel II and Basel III agreements, the probability of default (PD) is a key parameter used in calculating expected credit loss (ECL), which is typically defined as: PD × Loss Given Default × Exposure at Default. In practice or in regulatory requirements, gross domestic product (GDP) has been adopted in the PD estimation model. Due to the problem of excessive fluctuation and highly volatile ECL estimation, models that produce satisfactory PD and thus ECL estimations in the context of existing risk management techniques are lacking. In this study, we explore the usage of the credit default swap index (CDX), a market’s expectation of future PD, as a predictor of the default rate (DR). By comparing the goodness-of-fit of logistic regression, several conclusions are drawn. Firstly, in general, GDP has considerable explanatory power for the default rate which is consistent with current models in practice. Secondly, although both GDP and CDX fit the DR well for rating B class, CDX has a significantly better fit of DR for ratings [A, Baa, Ba]. Thirdly, compared with low-rated companies, the relationship between the DR and GDP is relatively weak for rating A. This phenomenon implies that, in addition to using macroeconomic variables and firm-specific explanatory variables in the PD estimation model, high-rated companies exhibit a greater need to use market supplemental information, such as CDX, to capture the changes in the DR.

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Macroeconomic determinants of credit risk: Evidence from the Eurozone

Cited by 11 publications

References 59 publications

Macroeconomic cyclical indicators and bank non-performing loans: does country governance matter in African countries?

Macroeconomic cyclical indicators and bank non-performing loans: does country governance matter in African countries?

Analysing the Influence of Macroeconomic Factors on Credit Risk in the UK Banking Sector

Goodness-of-Fit of Logistic Regression of the Default Rate on GDP Growth Rate and on CDX Indices

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