Measures Of Financial Distress Research Articles

Job Loss and Financial Distress During COVID-19: The Protective Role of Emergency Savings

Nearly a quarter of U.S. households experienced job or income losses related to the COVID-19 pandemic. Liquid assets mitigate financial distress amidst financial shocks such as job loss, yet this relationship concerning the COVID-19 pandemic is unknown. Using a nationally representative sample of U.S. respondents (N= 4,765) who completed a survey in the early days of the pandemic, we examined pre-pandemic liquid assets as a moderator of the relationship between COVID-19-related job and income loss and financial distress such as difficulty meeting financial obligations and the use of high-cost financial resources. Estimates from propensity score-weighted linear probability models indicated that greater liquid assets lessened the probability of experiencing all eight measures of financial distress and moderated the effect of COVID-19-related job/income loss on five out of eight measures. These results hold when examining financial distress specifically attributed to COVID-19 and controlling for public program participation and Coronavirus Aid, Relief, and Economic Security Act supports.

Financial distress, auditors’ going concern modification (GCM) and investors’ reaction in a concentrated ownership environment: new evidence from the Italian stock market

This paper feeds the literature about investors’ reaction to the release of going concern modified audit reports, which is abundant and controversial among scholars. Moving a step beyond the solely detection of abnormal stock returns at and around the event date, as done in the only two previous studies on the Italian setting, we perform an OLS multiple regression to test the informativeness of CARs and the influence of variables as selected firms’ accounts, auditor characteristics, the market capitalization and specific measures of financial distress to gather evidence whether investors react adversely to elements different from going concern modifications (GCMs). Based on our findings, investors react negatively to GCMs attached to qualified opinions and, surprisingly, positively to GCMs attached to clean opinions, reversing the prevailing evidence found out in the literature, especially in the USA. We attribute these results to the rough knowledge of Italian naïve investors of the going concern (GC) issue. The study detects how disclosure features conceived for large equity markets can lead to different investors’ behaviours in small ones on the one hand; on the other hand, it cannot lead to unequivocable generalization, even within similar countries, in light of sub-specific country features. The piece of evidence achieved suggests, for further research, to make an investors categorization to analyse market reactions, which takes more into account three main features stressed by the prevailing literature of small equity markets: high ownership concentration, the higher presence of institutional investors and the poorer reputation of BIG4 auditors.

Creeping COVID catastrophe: the impact of COVID-19 on nonprofits by sector

PurposeThis study aims to provide a timely “first look” at the impact of COVID-19 lockdown restrictions on the financial distress of nonprofits.Design/methodology/approachThis study uses Internal Revenue Service Form 990 returns, US census information, and Oxford COVID-19 workplace restriction data and utilizes logistic regression to analyze results.FindingsNonprofits with greater COVID-19 lockdown restrictions are more likely to experience financial distress, whether measured by a 30% reduction in total, program, management and general, or fundraising expenses. This paper also examines results by subsector using National Taxonomy of Exempt Entities data and finds that the Human Services and Public and Society subsectors drive the full sample results when the authors use total, program, or managerial and general expenses in the measure of financial distress, and the Education and Environment and Animals subsectors drive the results when using fundraising expenses in the measure of financial distress.Originality/valueBroadly speaking, this paper contributes to the limited research stream examining the impact of crises on nonprofits. More specifically, this study is among the earliest to rely on quantitative data to investigate such effects.

Accounting comparability and financial distress

PurposeThe purpose of this study is to present the evidence of the association between financial statement comparability and corporate financial distress.Design/methodology/approachThis is an empirical study, and this study uses multiple regression analysis to evaluate hypothesis.FindingsThe authors find a significant decrease in the probability of financial distress as accounting comparability increases. Findings of this study suggest that distressed firms tend to produce financial statements that compare poorly to those of peer firms; the effectiveness of predicting financial distress with accounting ratios may be conditional on comparability with peers; and financial statement comparability may be predictive of financial distress.Research limitations/implicationsFirst, this study only used publicly available financial data, which may not be representative of all countries and could differ because of differences in accounting practices. Second, although this study found a connection between accounting comparability and financial distress, it cannot prove a causal relationship, as other factors that were not controlled for may also have an impact. Third, this study used various measures of financial distress, but other measures could lead to different results. Finally, this study did not include all relevant variables, such as industry-specific factors and macroeconomic conditions, which could influence the relationship between accounting comparability and financial distress.Practical implicationsFor investors and financial analysts, the results imply that accounting comparability can serve as a useful signal for identifying companies that are more likely to remain financially stable in the long run. Thus, they may prefer to invest in or recommend highly comparable firms over their less comparable counterparts. For auditors, this study underscores the importance of promoting and enforcing accounting standards that improve comparability, as this can help mitigate the risk of financial distress among their clients. Regulators may also consider the implications of the study’s findings when designing policies and guidelines related to financial reporting and disclosure.Originality/valueTo the best of the authors’ knowledge, this is the first study investigating the association between financial statement comparability and corporate financial distress of the US firms. This study uses large, comprehensive and multi-year data. Furthermore, this is the only study that presents the evidence of negative association between comparability and firm financial distress.

Are key audit matter disclosures useful in assessing the financial distress level of a client firm?

This study examines the usefulness of new expanded audit report key audit matters (KAM) disclosures in assessing the level of financial distress present at a client firm. Using six years of KAM disclosures for U.K. Premium-listed firms beginning in 2013, we investigate the relation between firm financial distress and the number, risk level, financial statement impact, and individual nature of auditor-disclosed KAMs. We expand on literatures examining audit report disclosures in gauging financial distress assessments as well as the utility of expanded audit reporting. We find the greater the number of KAMs disclosed, the higher a firm's financial distress level. Additionally, results show entity-level KAMs, account-level KAMs with a primary impact on profitability and solvency, and certain types of individual KAMs are more likely to be disclosed when client firms face higher levels of financial distress. The results are robust to alternative measures of financial distress and to endogeneity tests. Our findings also indicate KAMs have predictive ability in assessing subsequent periods' financial distress levels. In all, evidence from this study suggests a way financial statement users can use independent auditor disclosures to assess one of the main risks associated with a firm - the risk of failure.

Comparison of two validated instruments to measure financial hardship in cancer survivors: comprehensive score for financial toxicity (COST) versus personal financial wellness (PFW) scale.

Financial distress and financial toxicity are recognized challenges in cancer survivorship. Financial toxicity includes both objective measures of hardship and subjective distress. We hypothesized that subjective financial distress is correlated to overall holistic financial toxicity. We compared two widely accepted instruments to measure financial distress and financial toxicity. Patients in the follow-up phase of care at a single institution were surveyed regarding demographic and economic status. Financial toxicity was measured using the comprehensive score for financial toxicity-functional assessment of chronic illness (COST-FACIT) and financial distress using the personal financial wellness (PFW) scale. Surveys were analyzed for correlation and internal consistency. Patient score distributions were compared. Associations between survey scores and patient factors were assessed using multivariable linear regression models. A total of 116 patients were included. Scores from the COST-FACIT showed a strong correlation with PFW scores (r = 0.90, p < 0.0001). Scale reliability was high for both the COST-FACIT (α = 0.92) and PFW (α = 0.97) surveys. Score distributions exhibited left skew for both surveys, with 9.5% of patient scores falling in the worst quartile of possible scores on each respective survey. The strongest predictors of financial distress and financial toxicity included young age, lower monetary savings, lower household income, and less perceived social support during cancer treatment. The COST-FACIT measure of financial toxicity correlated strongly with PFW measure of financial distress. Although these instruments were designed to assess different concepts (financial distress vs financial toxicity), they gave strikingly similar results. Either instrument may be used as a meaningful patient-reported outcome for study of financial distress in cancer survivors. However, the COST-FACIT construct of financial toxicity does not appear to add additional information beyond financial distress.

Do environmental regulations affect firm financial distress in China? Evidence from stock markets

ABSTRACT This study explores how environmental regulations affected firm financial distress in China from 1999 to 2018, when the national strategy experienced a major adjustment from economic development only to sustainable growth. Instead of targeting specific environmental policy, we divide environmental regulations for firms into two major types, including energy conservation and pollution reduction, and discuss the influences of the overall levels of Chinese environmental regulations in the last two decades. We find that these regulations were negatively associated with firm performance, positively related to the possibility of financial distress, and negatively associated with the length of distress time. Our additional tests also show that the two types of environmental regulations had different influences on firm financial distress for various firm characteristics, including state ownership and industries. The empirical results remain robust when alternative measures of financial distress and potential endogenous issues are controlled.

Measuring the effect of investor sentiment on financial distress

PurposeThis study examines the effect of firm-level investor sentiment on a firm's level of financial distress.Design/methodology/approachThe authors use Bloomberg's firm-level, daily investor sentiment scores derived from firm-level news and Twitter content in a beta-regression model to explain the variability in a firm's financial distress.FindingsThe results indicate that improvements (deterioration) in investor sentiment derived from both news articles and Twitter content lead to a decrease (increase) in the average firm's financial distress level. We also find that the effect of sentiment derived from Twitter on a firm's financial distress is significantly stronger than the sentiment derived from news articles.Research limitations/implicationsOur proxy for financial distress is Bloomberg's financial distress measures, which may be an imperfect measure of financial distress. Our results have important implications for market participants in assessing the determinants of financial distress.Practical implicationsOur sample period covers four years (2015–2019), which is determined by Bloomberg sentiment data availability.Social implicationsMarket participants are increasingly using social media to express views on firms and seek information that might be used to determine a firm's level of financial distress. Our study links investor sentiment derived from social media (Twitter) and traditional news articles to financial distress.Originality/valueBy examining the relationship between a firm's sentiment and its financial distress, this paper advances our understanding of the factors that drive a firm's financial distress. To our knowledge, this is the first study to link US firms' investor sentiment derived from firm-level news and Twitter content to a firm's financial distress.

Risk management and the cost of equity: evidence from the United Kingdom’s non-life insurance market

We investigate the effect of risk management (reinsurance) on the corporate cost of equity using panel data drawn from the United Kingdom’s (UK) non-life insurance industry. Our results show that use of reinsurance lowers the cost of equity but that the relation is non-linear. We find that the rate of reduction declines as the level of premiums ceded relative to total gross premiums written increases. We also find that the reinsurance-cost of equity relation is moderated by the risk of financial distress/bankruptcy. This moderating relation is robust to the use of three alternative measures of financial distress and bankruptcy risk.

On the determinants and prediction of corporate financial distress in India

PurposeThe 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.Design/methodology/approachIn 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.FindingsThe 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.Practical implicationsThe 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.Originality/valueThis 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.

Related party transactions and financial distress of Savings and Credit Cooperative Organizations (SACCOs) in Kenya

The widespread failure of DT SACCOs in Kenya is likely to lead to a loss of confidence among the current and potential members of the DT SACCOs in Kenya and eventually threatens to kill the sector. The study examined the effect of related party transactions on financial distress in DT-SACCOs in Kenya; the study adopted the following theories as to the basis of analyzing the collected data; wrecker’s financial distress theories and Agency theory. The target population was 176 Deposit-Taking SACCOs. Secondary data was obtained from SACCOs records as published by SASRA. The study used a systematic sampling technique based on the sampling formula by Taro Yamane (1967) to obtain the appropriate sample size of 68 DT SACCOs. Data were analyzed using STATA computer software. Data collection covered seven (7) year period from 2008 -2014, this period of 7 years was selected for the study because SASRA has enacted in 2010 therefore the justification for the choice of the study period, that is 3 years before and 4 years after SASRA enactment. The study established that related party transactions had a significant effect on financial distress in DT SACCOs in Kenya. The implications of the findings are that if the DT-SACCOs do not manage related party transactions then they will continue experiencing financial distress. The government through SASRA therefore should enact strict regulations in directors borrowing from SACCOs. The study has expounded on the body of knowledge on measures of financial distress in finance by introducing new relationships established. In terms of the contribution of the current study to innovation, the study used panel data analysis while other studies used OLS.

DETERMINANT OF FINANCIAL DISTRESS: THE CASE OF PULP &amp; PAPER COMPANIES REGISTERED IN INDONESIA STOCK EXCHANGE

The pulp and paper industry contributes to the Indonesian economy, especially to the non-oil and gas processing industry. Empirical research shows that pulp and paper companies listed on the Indonesia Stock Exchange (IDX) indicated financial distress. This study aims to find the effect of liquidity, leverage, profitability, and efficiency on pulp & paper companies' financial distress listed on the IDX. Using the Altman Z-score as a measure of financial distress, it was found that profitability, efficiency, and liquidity had a significant adverse effect on financial distress. In contrast, leverage had a significant positive effect on financial distress. Profitability has the greatest influence on financial distress, so it needs the primary intention of management. Keywords: financial distress, liquidity, profitability, leverage, efficiency

Income Loss and Financial Distress during COVID-19: The Protective Role of Liquid Assets

Nearly a quarter of U.S. households have experienced job or income losses related to the COVID-19 pandemic. Liquid assets mitigate financial distress in the face of financial shocks such as job loss, yet this relationship in the midst of the COVID-19 pandemic is unknown. Using a nationally representative sample of U.S. households (N = 4,383) who completed a survey in the early days of the pandemic, we examined pre-pandemic liquid assets as a moderator of the relationship between job and income loss and difficulty meeting financial obligations and use of high-cost financial resources. Estimates from propensity score-weighted linear probability models indicated that greater liquid assets lessened the probability of experiencing all eight measures of financial distress and most measures of distress among households experiencing job or income losses. Policy efforts to help households build emergency savings can help households better prepare for future pandemics while also supporting public health responses.

Marking to Market Corporate Debt

Models of capital structure and credit risk make predictions about market valuations of debt, but are routinely tested on the basis of book debt from common data sources. In this paper, we propose to close this gap. We construct a rich data set on firm level debt market valuations by carefully matching data on corporate bond and loan secondary market transactions. We document significant discrepancies between market and book values, especially for distressed firms. We use our dataset to i) provide novel rules of thumb on how to adjust leverage and unlever returns using standard datasets, and ii) to revisit a number of prominent empirical patterns involving corporate debt. Using a market-based measure of Tobin's Q, we find little evidence for investment cash-flow sensitivity in our data. We find that using market debt values significantly improves default prediction, and do not detect a credit spread puzzle. In asset pricing tests, we find a leverage premium, but no evidence for a value premium after controlling for market leverage. Moreover, a novel measure of financial distress, namely market-to-book debt, predicts stock returns positively in the cross-section, inconsistent with a financial distress puzzle.

The impact of tunnelling on financial distress and resolution: Evidence from listed firms in China

AbstractWe examine the impact of tunnelling on financial distress in Chinese stock markets, where the agency problem is common due to the weak legal system protecting minority shareholders' interests. Investigating the widespread financial distress among listed firms during the time period 1999–2015, we find that tunnelling is a determinant of financial distress–tunnelling not only leading to financial distress but also prohibiting distress recovery. Regulatory improvements aiming to reduce tunnelling behaviour contribute to the resolution of financial distress, but there is still room to improve. Our results show that state ownership has limited influence on firm operation before financial distress but tends to benefit recovery from periods of distress, which depicts the market economy mechanism in China. Our findings are robust to the potential endogeneity issue and various measures of financial distress.

Patient-physician communication about financial problems: A cross-sectional study among over-indebted individuals

About every tenth household across Europe is unable to meet payment obligations and living expenses on an ongoing basis and is thus considered over-indebted. Previous research suggests that over-indebtedness reflects a potential cause and consequence of psychosomatic health problems and limited access to care. However, it is unclear whether those affected discuss their financial problems with general practitioners. Therefore, this study examined patient-physician communication about financial problems in general practice among over-indebted individuals. We conducted a cross-sectional survey among clients of 70 debt advice agencies in North Rhine-Westphalia, Germany, in 2017. We assessed the prevalence of patient-physician communication about financial problems and its association with patient characteristics using descriptive statistics and logistic regression analysis. Of 699 individuals who returned the questionnaire (response rate:50.2%), we included 598 respondents enrolled in statutory health insurance with complete outcome data in the analyses. Conversations about financial problems with general practitioners were reported by 22.6% (n = 135) of respondents. Individuals with a high educational level were less likely to report such conversations than those with medium educational level (aOR 0.11; 95%CI 0.01-0.83) after adjustment for other sociodemographic characteristics, health status and measures of financial distress. Those without a migrant background(aOR 2.09; 95%CI 1.32-3.32), the chronically ill(aOR 1.90; 95%CI 1.16-3.13) and individuals who reported high financial distress(aOR 2.15; 95%CI 1.22-3.78) and cutting on necessities to pay for medications(aOR 1.86; 95%CI 1.12-3.09) were more likely to discuss financial problems than their counterparts. Few over-indebted individuals discussed financial problems with their general practitioner. Patients' health status, coping strategies and perception of financial distress might contribute to variations in disclosure of financial problems. Thus, enhancing communication and screening by routine assessment of financial problems in clinical practice can help to identify vulnerable patients and promote access to health care and social services and well-being for all.

Are Competitive Banking Systems Really More Stable?

This study replicates Schaeck et al. (2009), henceforth SCW. SCW conclude that (i) concentration and competition (as measured by Panzar and Rosse’s H-statistic) represent two separate dimensions of the banking sector, with (ii) greater competition being associated with greater financial stability. Using their data, we are able to exactly reproduce their original results. However, when we use current vintage data for the variables in their dataset, from both the same and alternative data sources, we find that H-statistic fails to attain significance at the 5% level. We obtain this result even though we use the same variables, estimation, and sample as SCW—just with more recent data instead of the earlier (later revised) numbers provided by the data vendors. Additional tests, such as expanding the timeframe from 1980–2005 to 1980–2011, employing more recent data for H-statistic and concentration, or using the z-score as an alternative measure of financial distress, further confirm this result. Further, not only are the estimates statistically insignificant, but they are economically insignificant, with small effect magnitudes. Our paper suggests that competition may not positively contribute to financial stability after all.

Repeated payment delinquency among young adults in the United States

AbstractThere is concern in the United States about young adults falling behind financially due to the increased use of student loans and low wages. This study investigates payment delinquency as a measure of financial distress to better understand how young adults might be struggling. Personality traits are incorporated into the model to determine the extent to which behavioural factors are correlated with financial behaviors and if they predict a habit trend of payment delinquency. The 1997 National Longitudinal Survey of Youth, a nationally representative longitudinal data set, is used in the study. A random effects probit model and a dynamic random effects probit model are used to examine late bill pay (harassed by bill collectors) and late rent or mortgage payments (more than 60 days late) over a period of 8 years (2007–2015). Results from the analysis indicate that payment delinquency in a previous period increases the likelihood of payment delinquency by 10 percentage points in a subsequent period. Conscientiousness decreases the likelihood by 2.1 percentage points, while neuroticism increases the likelihood by 1.6 percentage points.

Piloting a Financial Counseling Intervention for Patients With Cancer Receiving Chemotherapy

National organizations encourage communication about costs of cancer care; however, few data are available on health system models for identifying and assisting patients with financial distress (FD). We report the feasibility and acceptability of a financial counseling (FC) intervention for patients who receive chemotherapy at a comprehensive cancer center. Patients were randomly assigned 1:1 to FC or standard care. The FC arm received education, financial assistance screening, and an estimation tool with total billed charges and out-of-pocket (OOP) cost of one cycle of chemotherapy from a financial counselor through phone call and in-person visit. Participants completed measures of FD, health-related quality of life, and acceptability. Ninety-five participants enrolled (mean age, 61 years; 72% white; 50% commercially insured), with a 32% attrition rate between assessments. Rates of completion for the phone call, in-person, and entire intervention were 98%, 47%, and 30%, respectively. The OOP estimation tool was considered understandable and acceptable to the majority of participants. No significant changes in FD were found between arms. Emotional functioning was negatively associated with having high FD (95% CI, -0.13379 to -0.013; P = .0189). Being married was associated with a decrease in log-odds of having high FD (β = -1.916; 95% CI, -3.358 to -0.475; P = .0092). Implementation of an FC program that provides transparent cost data is feasible and acceptable. Incorporation of FC into clinical workflow, including phone counseling, is important to improve feasibility. Additional work is needed to develop tailored educational materials that are patient specific.

Looking Beyond the Financial Numbers: The Relationship Between Macroeconomic Indicators and the Likelihood of Financial Distress

The current article aims to identify important macroeconomic variables that could indicate the likelihood of financial distress among 294 Indian firms included in the BSE 500 index. Twelve years of financial data and macroeconomic indicators were analysed through a logit model. The study applied a synthetic measure of financial distress adopted from Bhattacharjee and Han (2014, China Economic Review, 30, 244–262.) which is based on the interest coverage ratio. A significant negative relationship is reported between the likelihood of financial distress among firms and three macroeconomic indicators, namely, the index of industrial production (IIP), exchange rate and a 10-year bond yield. Accordingly, the classification accuracy reported for the full, training and testing samples was 75.51, 79.49 and 70 per cent, respectively. With respect to theoretical contribution, the study has underlined the difference between financial distress and bankruptcy. An additional classification test was conducted wherein the harmonic mean based on the current dataset characteristics was the discriminating score. A prediction accuracy of 76.92 and 70 per cent with respect to the training and testing sample was reported.