Beyond bankruptcy: Does the US bankruptcy code provide a fresh start to entrepreneurs?

This paper assesses the extent to which the US bankruptcy system is effective in providing small businesses a “fresh start” after a bankruptcy filing. I use data from the 1993, 1998 and 2003 National Survey of Small Business Finances to explore how firms fare after a bankruptcy filing. On the positive side, previously bankrupt firms are not any more burdened than the average small firm by problems relating to profitability, cash flow, health insurance costs, or taxes. Further, the fact that these firms are surviving several years after the filing is itself a testament to the efficient functioning of the US bankruptcy system. It suggests that the bankruptcy system goes a long way toward helping businesses recover after a bankruptcy filing.     

Postbankruptcy Performance and Management Turnover

This article examines the performance of 197 public companies that emerged from Chapter 11. Over 40 percent of the sample firms continue to experience operating losses in the three years following bankruptcy; 32 percent reenter bankruptcy or privately restructure their debt. The continued involvement of prebankruptcy management in the restructuring process is strongly associated with poor post-bankruptcy performance. The substantial number of firms emerging from Chapter 11 that are not viable or need further restructuring provides little evidence that the process effectively rehabilitates distressed firms and is consistent with the view that there are economically important biases toward continuation of unprofitable firms.     

Predicting the outcome following bankruptcy filing: a three-state classification using neural networks

This paper uses artificial neural networks (ANNs), multi-state ordered logit and nonparametric multiple discriminant analysis (NPDA) for predicting the three-state outcome of bankruptcy filing. The study compares the classification accuracy of these procedures. It differs from previous studies on predicting financial distress by focusing on the firm after the filing of bankruptcy using accounting data, market data, and court-related information. Following the filing and through court approval the bankruptcy is resolved as firms are either acquired by other firms, emerging as independent operating entities, or liquidated. Distinguishing this three-state outcome is more complex than discriminating between healthy and financially distressed firms. Models suggested in previous studies for predicting the two-group financial distress perform poorly for our three-state scenario. Therefore, we develop models which focus on characteristics relevant for the bankruptcy resolution. We use a sample of 237 publicly traded firms which have complete data. For the entire sample and estimation samples, ANNs provide significantly better three-state classification than logit and NPDA. However, for some holdout samples the differences in classification accuracies are statistically insignificant. © 1997 John Wiley & Sons, Ltd.     

Predicting Bankruptcy Resolution

This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed.     

Predicting bankruptcy using the discrete-time semiparametric hazard model

The usual bankruptcy prediction models are based on single-period data from firms. These models ignore the fact that the characteristics of firms change through time, and thus they may suffer from a loss of predictive power. In recent years, a discrete-time parametric hazard model has been proposed for bankruptcy prediction using panel data from firms. This model has been demonstrated by many examples to be more powerful than the traditional models. In this paper, we propose an extension of this approach allowing for a more flexible choice of hazard function. The new method does not require the assumption of a parametric model for the hazard function. In addition, it also provides a tool for checking the adequacy of the parametric model, if necessary. We use real panel datasets to illustrate the proposed method. The empirical results confirm that the new model compares favorably with the well-known discrete-time parametric hazard model.     

Investing in Bankrupt Firms

We examine the investment characteristics of firms electing to enter bankruptcy, between 1973 and 1982. Comparisons are made before and after the Bankruptcy Reform Act of 1978. Our results indicate that the 1978 Act had no significant impact on bankruptcy decisions or resolutions for actively traded firms. Trading in bankrupt firms' securities is becoming more common, but no abnormal returns appear to be available. Systematic risk does not change significantly with the filing of bankruptcy, but there is a significant increase in return variance. The financial markets also react to various announcements of stages in the reorganization process.     

Bankruptcy and Institutions: Theory and Empirical Evidence from Korea and the United States

Using a simple z-score bankruptcy model, this article explores the relationship between bankruptcy threshold and institutions. The z-score threshold for bankruptcy is found to be higher in countries with stronger institutions. To test this claim, a cross-section data set of 86 Korean firms and 60 US firms from 1991 to 2001, extracted from a panel data set, is used. The empirical finding that the z-score bankruptcy threshold in the United States (which has better quality of institutions than does Korea) is higher than that in Korea is consistent with the prediction of the model. Additionally, having examined bankruptcy laws of the two countries, it is found that filing a petition for bankruptcy is easier and debtors rights are better protected in the United States than in Korea, which suggests that the bankruptcy laws of Korea and the United States may be partially responsible for the difference in the z-score threshold for bankruptcy.     

Empirical comparison of hazard models in predicting SMEs failure

This study aims to shed light on the debate concerning the choice between discrete-time and continuous-time hazard models in making bankruptcy or any binary prediction using interval censored data. Building on the theoretical suggestions from various disciplines, we empirically compare widely used discrete-time hazard models (with logit and clog-log links) and the continuous-time Cox Proportional Hazards (CPH) model in predicting bankruptcy and financial distress of the United States Small and Medium-sized Enterprises (SMEs). Consistent with the theoretical arguments, we report that discrete-time hazard models are superior to the continuous-time CPH model in making binary predictions using interval censored data. Moreover, hazard models developed using a failure definition based jointly on bankruptcy laws and firms’ financial health exhibit superior goodness of fit and classification measures, in comparison to models that employ a failure definition based either on bankruptcy laws or firms’ financial health alone.     

DOES FINANCIAL FLEXIBILITY REDUCE INVESTMENT DISTORTIONS?

The average U.S. firm has less leverage than one would expect based on the trade‐off between tax shields and bankruptcy costs. We focus on firms’ financial flexibility and examine whether firms preserve debt capacity to reduce investment distortions in the future. We find that firms with high unused debt capacity invest more in future years than do firms with low unused debt capacity. Furthermore, firms that are reluctant to borrow in unconstrained periods are more likely to issue debt in periods in which access to capital markets is more constrained.     

Strategic Bankruptcies and Price Reactions to Bankruptcy Filings

This study investigates whether the stock market differentiates between firms that file bankruptcy petitions for strategic reasons and firms that file bankruptcy petitions for financial reasons. We perform both univariate and regression tests on a sample of 245 firms that filed Chapter 11 bankruptcy petitions between 1981 and 1996. After controlling for bankruptcy outcome, probability of bankruptcy, firm financial condition, and firm size, we find that, in the period around bankruptcy filing, firms that file bankruptcy petitions for financial reasons have significantly larger stock price declines than firms that file bankruptcy petitions for strategic reasons.     

The Impact of Receiving Debtor-in-Possession Financing on the Probability of Successful Emergence and Time Spent Under Chapter 11 Bankruptcy

The ability to obtain financing is a critical element in attempting to successfully reorganise a firm which has declared Chapter 11 bankruptcy. Debtor-in-possession (DIP) financing has become an increasingly popular method in recent years. This paper examines whether receiving DIP financing is related to successful reorganisations and a shortened duration under Chapter 11 bankruptcy proceedings. This study finds that there is an increase in realised returns to equity at the announcement of DIP loan agreements which is positive and statistically significant. It is also found that DIP-financed firms have a reduced probability of liquidation, and shorter time spent under bankruptcy proceedings.     

Sources of gains to shareholders from bankruptcy resolution

Using a logistic regression model, we identify the characteristics of firms whose shareholders are likely to benefit from bankruptcy resolution. That is, winners (losers) are firms whose shareholders experience positive (negative) excess returns after bankruptcy filing. We find that winners are relatively smaller firms with higher proportions of convertible debt, tend to file for bankruptcy for strategic reasons, have low share-ownership concentration, and suffer comparatively larger pre-filing stock price declines. Among winners, shareholder returns are greater for firms that have higher levels of private debt and research and development (R&D) expenditures, and operate in more concentrated industries. In addition, our analysis indicates that an ex ante trading strategy of purchasing bankrupt stocks with a greater than 50% probability of being a winner on the day after bankruptcy filing and holding the stocks for a year, on an average, can generate average compounded and excess compounded holding-period returns of +71% and +42%, respectively.     

Prior Wall Street Journal Announcements of Possible Bankruptcy Filings and Price Reactions to Subsequent Bankruptcy Filings

This study examines the relation between prior Wall Street Journal (WSJ) announcements of possible bankruptcy filings and price reactions to subsequent bankruptcy filings for 336 firms that filed for bankruptcy between 1980 and 1993. Extant research indicates that price reactions to announcements of economic events are inversely related to the amount of surprise in the announcements. Prior WSJ anouncements of possible bankruptcy filings increase the markets a priori assessment of firms' probability of bankruptcy, thereby potentially reducing the surprise in subsequent bankruptcy filings. We hypothesize smaller price reactions to bankruptcy filings for firms where the WSJ previously published an article indicating that the firm may file for bankruptcy. Our results are consistent with this hypothesis. Specifically, we find smaller price reactions to bankruptcy filings for firms with prior WSJ announcements of possible bankruptcy filings. Our results hold after controlling for firm size, probability of bankruptcy, exchange listing, leverage, and predisclosure information.     

Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings

We examine whether the language used in 10‐K filings reflects a firm's risk of bankruptcy. Our sample contains 424 bankrupt U.S. companies in the period 1994–2015 and we use propensity score matching to find healthy matches. Based on a logit model of failing and vital firms, our findings indicate that firms at risk of bankruptcy use significantly more negative words in their 10‐K filings than comparable vital companies. This relationship holds up until three years prior to the actual bankruptcy filing. With our investigation, we confirm the results from previous accounting and finance research. 10‐K filings contain valuable information beyond the reported financials. Additionally, we show that 10‐Ks filed in the year of a firm's collapse contain an increased number of litigious words relative to healthy businesses. This indicates that the management of failing firms is already dealing with legal issues when reporting financials prior to bankruptcy. Our results suggest that analysts ought to include the presentation of financials in their assessment of bankruptcy risk as it contains explanatory and predictive power beyond the financial ratios.     

Asset Allocation in Bankruptcy

This paper investigates the consequences of liquidation and reorganization on the allocation and subsequent utilization of assets in bankruptcy. Using the random assignment of judges to bankruptcy cases as a natural experiment that forces some firms into liquidation, we find that the long‐run utilization of assets of liquidated firms is lower relative to assets of reorganized firms. These effects are concentrated in thin markets with few potential users and in areas with low access to finance. These findings suggest that when search frictions are large, liquidation can lead to inefficient allocation of assets in bankruptcy.     

Firms’ performance under different bankruptcy systems: a Europe–USA empirical analysis

This study empirically analyses the effect that the bankruptcy law has on firms’ performance based on its financial situation. To do this, we considered the different types of efficiency and their influence on firms’ value. The study was carried out for Germany, Spain, the United States, France and the United Kingdom. We applied System‐GMM estimation to dynamic panel data. The main results show that under creditor‐oriented systems, there is a decrease in the value of both financially distressed firms and those filing for bankruptcy.     

The Interaction of Solvency with Liquidity and its Association with Bankruptcy Emergence

Prior research has shown that accounting information available prior to a bankruptcy is associated with the likelihood of bankruptcy. We show that additionally, the accounting information available prior to bankruptcy is associated with whether or not a firm will emerge from bankruptcy. We predict that firms that exhibit low solvency risk and high liquidity risk are most likely to emerge from bankruptcy. Firms that exhibit high solvency risk and high liquidity risk are predicted to be least likely to emerge from bankruptcy. Cross–sectionally, our results support these predictions, but our findings differ across large and small firms.     

Earnings Management in Chapter 11 Bankruptcy

We study the impact of earnings management prior to bankruptcy filing on the passage of firms through Chapter 11. Using data on public US firms, we construct three measures of earnings management: a real activities manipulation measure (abnormal operating cash flows) and two accounting manipulation measures (discretionary accruals and abnormal working capital accruals). We find that, controlling for the impact of factors known to influence earnings management and firm survival in bankruptcy, earnings management prior to bankruptcy significantly reduces the likelihood of Chapter 11 plan confirmation and emergence from Chapter 11. The results are driven primarily by extreme values of earnings management, characterized by one or two standard deviations above or below the mean. The findings are consistent with creditors reacting positively to unduly conservative earnings reports and negatively to overly optimistic earnings reports. We also find that the presence of a Big 4 auditor is associated with a higher incidence of confirmation and switching to a Big 4 auditor before filing increases the incidence of emergence.     

Employee Costs of Corporate Bankruptcy

An employee's annual earnings fall by 13% in the first full calendar year after her firm's bankruptcy, and the present value of lost earnings from bankruptcy to six years following bankruptcy is 87% of pre-bankruptcy annual earnings. More worker earnings are lost in thin labor markets and among small firms. Ex ante compensating wage differentials for this “bankruptcy risk” are up to 2% of firm value for a firm whose credit rating falls from AA to BBB, comparable in magnitude to debt tax benefits. Thus, wage premia for expected costs of bankruptcy are sufficiently large to be an important consideration in capital structure decisions.     

The Impact of Corporate Governance and Audit Quality on the Cost of Private Loans*

The objective of this paper is to examine whether banks discriminate between firms on the basis of their financial condition when assessing the credit default risk, and to what extent corporate governance and auditor quality mitigate such risks in the pricing of new bank loans. The results indicate that, depending on the probability of bankruptcy, banks rely on different monitoring devices. For firms with a low probability of bankruptcy, banks do not rely on the quality of corporate governance or the auditor's industry specialization. However, auditor tenure and a change in auditor affect the spread. For firms with a high probability of bankruptcy, the spread is adjusted for the quality of corporate governance and the auditor's specialization. These results are robust to alternative specifications and measures.