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This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

This paper aims to demonstrate gender diversity in the structure of corporate governance and test the effect of diversity on the firm performance suffering from financial distress.

The paper is quantitative using a sample of 467 public firms in Indonesia. Data were analyzed into statistics descriptive and the hypothesis was tested using the test of logistic regression.

The preliminary results of the paper demonstrate the number of firms employing women and men in the structure of corporate governance of 13% on the commissioner board, 7% on the director board and 5% on the audit committee. Based on the test of effect, this paper further found that firms employing women and men (gender diversity) in the structure of the board of commissioners, tend to suffer from financial distress lower than firms only employing men (non-gender diversity).

This paper is not an effort to make the proportion of voices of women equal to men, however the representation of women at least exists in the structure of corporate governance as part of workforce diversity and inclusivity. In addition, this paper is considered not to use panel data with the purpose of avoiding repetitive data because of the use of a nominal scale in the logistic regression model.

The finding of the paper is addressed to deliver insights into the current conversation on the issue of women's day with the theme of Each for Equal and to firms in positioning women in the structure of boardrooms.

This paper extends the limited scholarly work on the nexus between gender diversity and financial performance. The framework of social identity theory and the tenet of corporate governance are elaborated to disclose the finding that firm shareholders tend to benefit from gender diversity in the structure of the commissioner board.

This paper examines whether financial distress is associated with tax avoidance and whether the COVID-19 pandemic moderates such association.

The sample covers 38,958 firm-year observations from 32 countries during the period 2015–2020. Financial distress is measured using the ZSCORE by Altman (1968), while tax avoidance is based on the book-tax difference.

Financially distressed firms exhibit low tax avoidance pre- and during the pandemic periods. The authors find higher tax avoidance during the pandemic compared to the pre-pandemic period, but the pandemic enhances the negative relationship between financial distress and tax avoidance.

The study offers evidence on how financial distress drives firms to engage in more tax avoidance when firms globally encountered various levels of financial difficulty sparked by the economic challenges of the COVID-19 pandemic.

The findings provide insights to policymakers on the need to monitor and incentivise financially distressed firms, especially during economic challenges due to pandemic.

This study adds to the limited, albeit important, evidence on the joint effect of the COVID-19 pandemic and financial distress on tax avoidance.

The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.

The concept of financial distress covers a range of different types of financial problems, in addition to bankruptcy, which is not common in the sector. The methodology used to predict financial problems was artificial neural networks using traditional financial variables according to the capital, assets, management, earnings, liquidity and sensibility system, as well as a series of macroeconomic variables, the impact of which has been proven in a number of studies.

The results obtained show that artificial neural networks are a highly suitable method for studying financial distress in Spanish credit institutions and for predicting all cases in which an entity has short-term financial problems.

This is the first work that tries to build a model of artificial neural networks to predict the financial distress in the Spanish banking system, grouping under the concept of financial distress, apart from bankruptcy, other financial problems that affect the viability of these entities.

This paper empirically examines whether the order of liability and preferred stock accounts presented on the balance sheet is consistent with how the stock market values their riskiness.

This paper measures a firm’s riskiness with idiosyncratic risk and employs the first-difference design to test the relation between idiosyncratic risk and the order of current liabilities, noncurrent liabilities and preferred stock, respectively. Further, the paper tests whether operating liabilities are viewed as riskier than financial liabilities. Finally, the authors partition their sample based on the degree of financial distress and investigate whether the results differ between the two subsamples.

The paper finds that current liabilities are viewed as riskier than noncurrent liabilities and preferred stock is viewed as less risky than current and noncurrent liabilities, consistent with the ordering on the balance sheet. Further, the paper finds that operating liabilities are viewed as riskier than financial liabilities. Finally, the authors find that total liabilities and preferred stock (redeemable and convertible classes) are viewed as riskier for distressed firms than for nondistressed firms.

The authors thoroughly investigate the riskiness of several classes of claims and document that the classification of liabilities and preferred stock classes is relevant to common stockholders for assessing their associated risk.

This study aims to adopt the Altman model in order to predict the performance of industrial companies listed on the Palestinian Stock Exchange during the period of time between 2013 and 2017.

The study sample consisted of 12 industrial companies listed on the Palestine Stock Exchange, and their financial disclosure period extended for 5 years. Multiple linear regression model was used in the analysis to determine the relationship between the independent variables and the dependent variable where the independent variables were (X₁, X₂, X₃). This study is based on one basic assumption, which is that the Altman's model cannot predict the performance of the Palestinian industrial sector.

The results of the analysis proved the negation of the zero main hypothesis. This means that Altman's model can predict the performance of the Palestinian industrial sector at the level of statistical significance (a = 0.05), as well as the existence of a statistically significant relationship between each of the independent variables (X₂, X₄, X₅) and the dependent variable (Log (Z-score)). Hence, the relationship of X₁ and X₃ with the dependent variable was not statistically significant.

This paper highlights different challenges that face the adaption of Atman's model and performance prediction in the Palestinian industrial sector. The findings of the analysis have the potential to help future researchers in examining and dealing with new challenges.

This paper presents a vital review of adopting Altman's model in the Palestinian industrial sector. A number of recommendations have been made, the most important of which is that most of the companies are located in the red zone. The Altman's model must be adapted in order to fit the Palestinian environment according to the results of statistical analysis and according to a proposed model, which is Log (Z) = −0.653 + 0.72X₂ + 0.18X₄ + 0.585X₅.

The purpose of this paper is to empirically explore the financial well-being (FWB) of Malaysian households and to construct a subjective FWB index with present and future time perspectives.

Data were collected from 1,867 respondents across five major regions in Malaysia. Adapting the InCharge Financial Distress/Financial Well-being (IFDFW) Scale by Prawitz et al. (2006) and the method of computing an index by Devlin (2009), this study develops an FWB index using subjective measures that include future time perspectives (retirement). The index was employed to measure the FWB across low-, middle- and high-income groups and socio-demographic characteristics.

This study finds evidence that Malaysians' FWB is at an average level (46.8). Middle-income households' FWB (46.1) flanks between the financial well-being index (FWBI) levels of the low-income (37.4) and high-income households (58.7). Across age groups, education levels and employment sectors, the FWB of Malaysians significantly varies, although not across different ethnics, religions, zones and residential areas. Overall, the results suggest that the detrimental effects of FWB are perceived by all Malaysian households nationwide regardless of their religion, ethnicity and residential areas.

The results of this study complement the other well-being indices used by policymakers and may serve as a useful input for government and policymakers for them to formulate appropriate strategies to promote higher FWB of Malaysian households based on their socio-demographic characteristics.

This study used primary data and developed a subjective FWB index that leverages on people's perceptions of their own financial well-being while including present and future time perspectives. The main contribution of this paper is to construct an index that is easily interpretable and that complements the existing FWB indices, and to identify the segments of society that have low vis-à-vis high FWB.

The purpose of this paper is to examine whether managers of bankrupt firms are more or less conditionally conservative in their financial reporting relative to non-bankrupt firms. The study further examines the cross-sectional differences in conditional conservatism among bankrupt and non-bankrupt firms.

The study employs a sample of US firms to investigate conditional conservatism in firms that experience financial distress and go bankrupt relative to non-stressed non-bankrupt firms. The study also uses switching regression models to identify the drivers of the cross-sectional difference in conditional conservatism among bankrupt and non-bankrupt firms.

Empirical results show that bankrupt firms are timelier in recognizing bad news than good news when compared to non-bankrupt firms. The higher level of conditional conservatism in bankrupt firms is mainly driven by their higher levels of leverage and tax-reduction incentives. The cross-sectional analyses show that these results largely hold for more leveraged firms and firms with higher tax costs. Taken together, these results suggest that the conservative tendency of managers of bankrupt firms can stem from the agency problem between lenders and managers and from tax-decreasing motivations.

The novelty of the authors’ research stands in studying the drivers of the cross-sectional differences in conditional conservatism between bankrupt and non-bankrupt firms and specifically, the demonstration that taxation also induces conditional conservatism in the setting of ex post bankrupt firms.

This study aims to investigate the link between audit quality and in-court debt restructuring. The aim is to understand whether the confirmation of debt restructuring plans is affected by audit quality, which, in the light of agency theory, reduces information asymmetries between outsiders (creditors and the court) and insiders (shareholders and managers) of the debtor company.

A logistic regression is performed to test whether higher audit quality is associated with an increased probability of successfully completing a debt restructuring proceeding (RP). Consistent with the literature, audit quality is assessed ex ante based on auditor size, which is used as a proxy for independence. The analysis considers private Italian companies.

Audit quality positively affects debt restructuring. Among financially distressed companies, those audited by an audit company are more likely to succeed in RPs than those audited by a single practitioner. There is no evidence of a Big N effect.

This study fills a gap in literature as, in contrast to other financial and governance characteristics, audit quality has never been studied before as a determinant of efficient restructuring. It contributes to the literature on auditing and governance by highlighting the importance of audit quality in complex situations such as RPs, and it expands on debt restructuring literature by considering the importance of the information exchanged during RPs.

Negative disclosure tone in 10-K annual reports has economic consequences, yet relatively little is known about how it is generated. Boards of directors play an important governance role with respect to mandatory disclosures and personally sign off on Form 10-K, leading us to expect directors to influence financial reporting narratives. This study investigates whether the negative tone of firms' narrative annual report disclosures is associated with the human and social capital of its board of directors.

Multivariate regression analyses of negative disclosure tone (Loughran and McDonald, 2011) on board members' average age, gender, education, financial expertise and turnover is performed. A host of supplemental tests to corroborate our primary analysis, including using Sarbanes-Oxley's financial expert mandate as an exogenous shock to board composition, impact threshold for a confounding variable, placebo analysis, portfolio tests of more and less negative disclosing firms and portfolio tests of “loud” versus “quiet” boards are conducted.

Evidence that directors' gender, education, financial expertise and board turnover are associated with more negative disclosure tone, while directors' age is associated with less negative disclosure tone is found. The study also looked within the board to differentiate whether these findings are driven by characteristics of inside directors or outside directors serving on the audit committee, or both, as these are the specific groups of directors we would expect to play a role in disclosure. It was found that negative disclosure tone is associated with a lower bid-ask spread, so this study interpreted more negative tone as containing more descriptive information.

This study helps decode the “black box” of annual report disclosure tone, which Loughran and McDonald (2011) show has important economic implications. The results help inform stakeholders such as policymakers, executives and capital market participants as to how board member traits are associated with disclosure. The findings are particularly important as this study bears witness to the increasing prominence of gender/diversity mandates (e.g. Israel, Norway, California) and financial expertise mandates (e.g. Sarbanes-Oxley).