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This paper investigates the financial risk factors associated with fiscal distress in local governments. We hypothesize that fiscal distress is positively correlated with revenue concentration and debt usage, while negatively correlated with administrative costs and entity resources. The regression model results in a prediction of the likelihood of fiscal distress, which correctly classifies up to 91% of the sample as fiscally distressed or not. The model also allows for an analysis of the impact of a change in a risk factor on the likelihood of fiscal distress. A decrease in intergovernmental revenues as a percent of total revenues and an increase in administrative expenditures as a percent of total expenditures have the biggest influences on reducing the likelihood of fiscal distress.

This study seeks to analyse if the adjustment towards the target short-term debt ratio of small and medium-sized firms (SMEs) is related to financial distress risk.

Data obtained for a sample of Portuguese manufacturing SMEs from 2010 to 2017 were analysed using the system-generalised method of moments (GMM-sys). Using the modified Z-Altman score, the authors classify SMEs according to their exposure to financial distress risk.

Manufacturing SMEs exposed to a high risk of financial distress rebalance their short-term debt ratio quicker. However, regardless of the financial distress risk level, SMEs distant from the target short-term debt ratio adjust more slowly, suggesting that transaction costs are greater than financial distress costs.

Policymakers should promote the access to external sources of finance with low transaction costs for SMEs, exposed to low levels of financial distress risk, to rebalance their short-term debt ratios quicker. Distressed SMEs far from their target short-term debt ratios, but with capacity to rebalance, need government programmes to access finance with low transaction costs to rebalance their short-term debt ratios.

This paper contributes to deepening our understanding of how SMEs, facing financial risk, rebalance their short-term debt ratios. SMEs, facing high financial distress risk, adjust towards their target short-term debt ratios more rapidly. However, SMEs, distant from the target short-term debt ratio face higher transaction costs than financial distress costs. These firms adjust towards their target short-term debt ratios more slowly, which may aggravate the refinancing risk and, ultimately, announce bankruptcy.

The main aim of the study is to identify some critical microeconomic determinants of financial distress and to design a parsimonious distress prediction model for an emerging economy like India. In doing so, the authors also attempt to compare the forecasting accuracy of alternative distress prediction techniques.

In this study, the authors use two alternatives accounting information-based definitions of financial distress to construct a measure of financial distress. The authors then use the binomial logit model and two other popular machine learning–based models, namely artificial neural network and support vector machine, to compare the distress prediction accuracy rate of these alternative techniques for the Indian corporate sector.

The study’s empirical results suggest that five financial ratios, namely return on capital employed, cash flows to total liability, asset turnover ratio, fixed assets to total assets, debt to equity ratio and a measure of firm size (log total assets), play a highly significant role in distress prediction. The study’s findings suggest that machine learning-based models, namely support vector machine (SVM) and artificial neural network (ANN), are superior in terms of their prediction accuracy compared to the simple binomial logit model. Results also suggest that one-year-ahead forecasts are relatively better than the two-year-ahead forecasts.

The findings of the study have some important practical implications for creditors, policymakers, regulators and other stakeholders. First, rather than monitoring and collecting information on a list of predictor variables, only six most important accounting ratios may be monitored to track the transition of a healthy firm into financial distress. Second, our six-factor model can be used to devise a sound early warning system for corporate financial distress. Three, machine learning–based distress prediction models have prediction accuracy superiority over the commonly used time series model in the available literature for distress prediction involving a binary dependent variable.

This study is one of the first comprehensive attempts to investigate and design a parsimonious distress prediction model for the emerging Indian economy which is currently facing high levels of corporate financial distress. Unlike the previous studies, the authors use two different accounting information-based measures of financial distress in order to identify an effective way of measuring financial distress. Some of the determinants of financial distress identified in this study are different from the popular distress prediction models used in the literature. Our distress prediction model can be useful for the other emerging markets for distress prediction.

This study aims to analyze the effect of cognitive load and social value orientation on managers’ preferences when they face with two types of restructuring choices in financially distressed firms: the first belonging to the family of organizational restructuring (massive layoffs) and the second to the family of financial restructuring (debt increases).

The authors investigate experimentally the impact of managers’ cognitive load and social value orientation on the decision to restructure leveraged buyout (LBO) firms in financial distress by using either massive layoffs or debt increases.

By investigating the impact of managers’ cognitive load and social value orientation on the restructuring decision of an LBO firm in financial distress, the research reveals that, on average, cognitively loaded managers prefer massive layoffs over increased debt levels. The massive layoffs seemingly provide a relatively easier way to avoid conflict with influential, residual claimants. In contrast, social value–oriented managers actively avoid massive layoffs and prefer to increase debt.

These results imply that the performance mechanisms emphasized to improve agency relations, for example, in LBOs, have their own limitations during periods of financial distress. This study shows that one of these limits is related to cognitive distortions and personality traits.

In this research, the originality lies in understanding how managers’ internal factors affect their restructuring decision-making, in the case of LBO firms in financial distress.

This paper analyzes the role of trade credit in financial crises. Using newly collected data, we investigate the impact of negotiated agreements between debtor and creditor countries on bilateral trade. Our results indicate that exports to creditor countries rise considerably after debt restructuring agreements in the period 1980–1997, while we find no effect for imports and for the more recent period. We identify trade credit as one key channel behind this positive effect. Apparently, crisis resolution efforts, in particular agreements to extend and roll over trade credits, play a crucial role for export recoveries. This gives some support to current worldwide efforts to sustain trade financing via coordinated policy interventions.

The unsustainable public debt of most African economies adversely affects their economic growth and stability. This study aims to explore the influence of cross-country indicators of governance from African countries on public debt accumulation.

The study deployed a quantitative research design technique. Secondary data was used in this study. The frequency of the data is annual, and it is available from 1996 to 2022 for 48 countries in Africa. The study deployed the system generalized method of moments for the estimation.

The study finds that countries with high regulatory quality standards, control corruption and ensure effective governance accumulate less government debt while countries that abide by the rule of law instead accumulate more government debt. The study also finds that economic growth and government revenue reduce government gross debt while government expenditure and investments increase public debt.

Due to data unavailability, other factors which are likely to influence government debt accumulation were not included in the study as control variables. This is the limitation of the study.

African governments should strive to maintain high regulatory quality standards through the formulation and implementation of sound policies and regulations that permit and promote private sector development, and ensure quality and accountability of public and civil services. Governments are also urged to control corruption and enact good laws so that the enforcement of these laws will not worsen the risk of becoming debt-distressed.

Recent studies on governance and public debt were focused on the Arabian Gulf countries, countries of the Middle East and North Africa (MENA) region and a combination of high and low-income countries. This study scrutinizes exclusively the effects of the quality of governance indicators on public debt accumulation, in the context of Africa.

This paper aims to investigate the determinants of choice between private and public debt for British and German listed companies.

The paper is based on three strands of theories: the “liquidation and renegotiation” hypothesis; the “moral hazard and adverse selection” hypothesis; the “flotation cost” hypothesis. The regression analysis was adopted to test these hypotheses. The specific econometric method used for panel data is generalised method of moments (GMM).

The evidence records a few similarities in debt‐mix structure of German and UK firms but it also detects some important differences. Therefore, the paper concludes that the relation between dependent and explanatory variables is country‐dependent. This can be attributed to the differences in corporate governance mechanisms and institutional features of the countries.

The limitation mainly has come from data unavailability for public debt. Future research could be to extend the number of countries to have a better idea for the impact of institutional factors on corporate debt‐mix.

The findings confirm that the debt ownership decision of listed firms is not only the result of their own characteristics but also the outcome of legal and financial environment and corporate governance traditions in which they operate. The way managers decide about the type of debt financing is not universal. Furthermore, the factors such as liquidation and renegotiation, moral hazard and adverse selection, flotation costs are found to be significantly relevant while deciding the mix of corporate debt.

This study offers a unique comparison of the evidence from a bank‐based economy (Germany) and a market‐based economy (UK) that should have direct implications on the choice between bank debt and public debt. Firms with a long‐run debt ownership target attain it through an adjustment process. The authors are not aware of any other study on debt ownership that controls for endogeneity using the GMM technique.

The purpose of the paper is to identify the determinants of the probability of living beyond one’s means. The paper also explores the coping mechanisms of those financially distressed as well as the debt taking behaviour of consumers.

The study uses data obtained from the OECD International Network on Financial Education pilot study on Measuring Financial Literacy in 2010 for the case of Malaysia. A logistic regression model is used to identify the main determinants of the probability that a consumer will live beyond his/her means. The analysis is carried out by using a set of socio-economic factors and the individual’s financial behaviour and attitudinal characteristics as explanatory variables.

The findings indicate that low income and seasonal income earners are more vulnerable to financial distress. Furthermore, having a higher education, higher financial knowledge and prudent financial behaviour and attitude do not necessarily translate into better financial management. Family and friends provide the main source of financial assistance in times of need.

The assessment of financial knowledge should go beyond individual’s knowledge on financial concepts and theories. Practical knowledge on financial and cash flow management should be assessed.

The study reiterates the importance of financial education. It is imperative to include financial education as part of the schools’ curriculum and also to be incorporated as part of the Continuous Professional Development modules for working adults.

The study is based on the first nationwide study of consumer finances in Malaysia. It contributes to the literature by integrating financial behaviour and attitudinal factors into the analysis of the ability of individuals to live within their means. The findings also show the limitations of the existing self-assessment of financial behaviour and attitude and the assessment of financial knowledge.