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We build a dynamic capital structure model to study the link between firms' systematic risk exposures and their time-varying debt maturity choices, as well as its implications for the term structure of credit spreads. Compared to short-term debt, long-term debt helps reduce rollover risks, but its illiquidity raises the costs of financing. With both default risk and liquidity costs changing over the business cycle, our calibrated model implies that debt maturity is pro-cyclical, firms with high systematic risk favor longer debt maturity, and that these firms will have more stable maturity structures over the cycle. Moreover, pro-cyclical maturity variation can significantly amplify the impact of aggregate shocks on the term structure of credit spreads, especially for firms with high beta, high leverage, or a lumpy maturity structure. We provide empirical evidence for the model predictions on both debt maturity and credit spreads.

The tax laws of most developed countries are debt biased since firms can deduct interest on debt but not on equity. This bias is known to distort investment decisions. However, less is known about how the debt tax shield affects the ownership of assets when bidders differ financial expertise and thus in optimal use of leverage. We show that the debt tax shield need not always distort ownership efficiency. Assets end up with the socially preferred owner when differences in financial and productive expertise between bidders are small and better financial expertise reduces expected bankruptcy costs.

Bankruptcy is an essential screening mechanism for developing economies. This paper focuses on the way bankruptcy is managed in Tunisia, a country characterized by the importance of its banking sector. We hand collected data on a set of Tunisian firms that went bankrupt between 1995-2009. We gathered original and unique information on the firms’ characteristics, the causes of default, the values of assets, the structure of claims, the recovery rates, and the bankruptcy costs. We use this information to answer several questions (those questions being investigated both directly, and by controlling for any risk of selection bias): 1) are the Tunisian bankruptcy procedures able to generate high total recoveries? 2) Are the secured creditors (mostly banks) well-enough protected under bankruptcy? 3) Do the secured creditors influence the choice between liquidation and reorganization? 4) To what extent the recoveries of the secured creditors compete (or not) with the ones of the other classes of creditors? We find that the Tunisian reorganization procedures are able to generate substantial recoveries, but those are mainly captured by the preferential claims (employees and public claims). This is coherent with the authorities’ willingness to improve social protection, but this raises concerns as the Tunisian firms are mainly financed by bankers. Our analysis shows that the secured creditors are poorly protected under bankruptcy: they rank almost last in the priority order of repayment, and their recovery rate is similar to one of the unsecured creditors. We also find that the rather high level of recovery rate is mainly attributable to the reorganization procedures. We finally find that the court’s choice between reorganization and liquidation is not influenced by the structure of claims. Thus, in Tunisia, the creditors are losing hand once bankruptcy is triggered. The likely consequences on development are twofold: first, higher risks of capital misallocation and of credit rationing; second, stronger incentives for the banks to prioritize informal workouts.

The paper analyzes the welfare implications of a policy of mandatory disclosure of information on the value of directly held investments by banks. It is based on a model of payments in a network where the value of a bank’s equity depends on the value of directly held investment of its trading partners, i.e. there is “contagion”. Additionally banks have a profitable investment project for which they need funding from outsiders, but due to agency problems they can only obtain financing if their equity is large enough. Furthermore, banks can, at a cost, disclose the information of their directly held investments. We find that there are equilibrium with no disclosure and no funding for new investments projects. Yet when the disclosure costs are not too large, mandatory disclosure increases ex-ante welfare of banks and outside investors if and only if contagion is severe. The difference for the social and private benefits is that an individual bank’s disclosure of the value of its directly held investment can be uninformative due to counterparty default risk. Instead, mandatory disclosure of information by all banks allows outside investors to assess the financial architecture of the system and direct their funding to the solvent banks.

While the empirical literature has often documented a “default anomaly”, i.e. a negative relation between default risk and stock returns, standard theory suggests that default risk should be priced in the cross-section. In this paper, we provide an explanation for this apparent puzzle using a new approach. First we calculate monthly physical probabilities of default (PDs) for a large sample of European firms. Second we decompose these estimated PDs into systematic and idiosyncratic components; we measure the systematic part as the sensitivity of the physical PD to an aggregate measure of default risk. While sorting stocks based on physical PDs confirms a possible default anomaly, we find that the relation between the systematic default risk and stock returns is in fact positive. Our results therefore suggest that risker stocks, as measured by the physical PDs, will tend to underperform because they have on average lower exposures to aggregate default risk. Their riskiness is mostly idiosyncratic and can be diversified away.

We investigate whether and how business credit information sharing helps to better assess the default risk of private firms. Private firms represent an ideal testing ground because they are smaller, more informationally opaque, riskier, and more dependent on trade credit and bank loans than public firms. Based on a representative panel dataset that comprises private firms from all major industries, we find that business credit information sharing substantially improves the quality of default predictions. The improvement is stronger for older firms and those with limited liability, and depends on the sharing of firms’ payment history and the number of firms covered by the local credit bureau office. The value of soft business credit information is higher the smaller the firms and the lower their distance from the local credit bureau office. Furthermore, in spatial and industry analyses we show that the higher the value of business credit information the lower the realized default rates. Our study highlights the channel through which business credit information sharing adds value and the factors that influence its strength.

We analyze an exchange economy of unsecured credit where borrowers have the option to declare bankruptcy in which case they are temporarily excluded from financial markets. Endogenous credit limits are imposed that are just tight enough to prevent default. Economies with temporary exclusion differ from their permanent exclusion counterparts in two important properties. If households are extremely patient, then the first–best allocation is an equilibrium in the latter economies but not necessarily in the former. In addition, temporary exclusion permits multiple stationary equilibria, with both complete and with incomplete consumption smoothing.

In this paper we investigate the ability of a number of different ordered probit models to predict ratings based on firm-specific data on business and financial risks. We investigate models which are based on momentum, drift and ageing, and compare them with alternatives which take the initial rating of the firm and its previous actual rating into account. Using data on US bond issuing firms, as rated by Fitch, over the years 2000 to 2007, we compare the performances of these models for predicting the ratings both in-sample and out-of-sample using root mean squared errors, Diebold-Mariano tests of forecast performance and contingency tables. We conclude that both initial and previous states have a substantial influence on rating prediction.

A firm’s current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in the set of default risk drivers. The analysis is done with a discrete duration model. Out-of-sample analysis of default events two to five years ahead reveals that the discriminating power of the duration model increases substantially when leverage forecasts are included. We further document that credit ratings contain information beyond the one contained in standard variables but that this information is unrelated to forecasts of leverage ratios.

We provide novel evidence linking the level of creditor protection provided by law to the degree of usage of technologically older, vintage capital in the airline industry. Using a panel of aircraft-level data around the world, we find that better creditor rights are associated with both aircraft of a younger vintage and newer technology, as well as firms with larger aircraft fleets. We propose that by mitigating financial shortfalls, enhanced legal protection of creditors facilitates the ability of firms to make large capital investments, adapt advanced technologies, and foster productivity.

Credit rating agencies do not only disclose simple ratings but announce watchlists (rating reviews) and outlooks as well. This paper analyzes the economic function underlying the review procedure. Using Moody's rating data between 1982 and 2004, we find that for borrowers of high creditworthiness, rating agencies employ watchlists primarily in order to improve the delivery of information. For low-quality borrowers, in contrast, the review procedure seems to have developed into an implicit contract `a la Boot, Milbourn, and Schmeits (2006), inducing the companies on watch to abstain from risk-augmenting actions. The agencies' economic role hence appears to have been enhanced from a pure information certification towards an active monitoring function.

We propose a theory of financial intermediaries operating in markets influenced by investor sentiment. In our model, banks make loans, securitize these loans, trade in them, or hold cash. They can also borrow money, using their security holdings as collateral. We embed such banks in a stylized financial market, in which securitized loans may be mispriced, and investigate how banks allocate limited capital among the various activities, as well as how they choose their capital structure. Banks maximize profits, and there are no conflicts of interest between bank shareholders and creditors. The theory explains the cyclical behavior of credit and investment, but also accounts for the fundamental instability of banks operating in financial markets, especially when banks use leverage.

We evaluate the prediction accuracy of models designed using different classification methods depending on the technique used to select variables, and we study the relationship between the structure of the models and their ability to correctly predict financial failure. We show that a neural network based model using a set of variables selected with a criterion that it is adapted to the network leads to better results than a set chosen with criteria used in the financial literature. We also show that the way in which a set of variables may represent the financial profiles of healthy companies plays a role in Type I error reduction.

A firm's termination leads to bankruptcy costs. This may create an incentive for outside stakeholders or the firm's debtholders to bail out the firm as bankruptcy looms. Because of this implicit guarantee, firm shareholders have an incentive to increase volatility in order to exploit the implicit protection. However, if they increase volatility too much they may induce the guarantee-extending parties to "walk away". I derive the optimal risk management rule in such a framework and show that it allows high volatility choices, while net worth is high. However, risk limits tighten abruptly when the firm's net worth declines below an endogenously determined threshold. Hence, the model reproduces the qualitative features of existing risk management rules, and can account for phenomena such as "flight to quality".

L’ampleur des positions prises sur le marche des swaps de defaut de credit (CDS) a souleve des inquietudes sur la capacite du marche a regler les defauts lorsque ceux-ci concernent de tres gros emprunteurs. La quasi-faillite de AIG et la faillite averee de Lehman Brothers en 2008 ont revele l’exposition des acheteurs de CDS au risque de contrepartie et mis en evidence la necessite d’organiser le marche, ce qui a declenche un processus de reformes. Premierement, nous analysons les vulnerabilites du marche au moment de l’eclatement de la crise. Deuxiemement, pour comprendre sa resilience malgre des faillites majeures, nous analysons le processus d’encheres qui a permis de regler ces defauts, les strategies des acheteurs et des vendeurs, ainsi que le lien avec le marche des obligations. Nous etudions ensuite la facon dont ces encheres ont precisement fonctionne dans le cas de defauts majeurs, tels que Lehman Brothers, Washington Mutual, CIT et Thomson, ainsi que pour Fannie Mae et Freddie Mac. Troisiemement, nous analysons le processus de reformes en cours.Classification JEL : D44 ; G01 ; G15 ; G33.

This paper links banking with asset prices in a monetary macroeconomic model. The main innovation is to consider how falling asset prices affect the banking system through wide-spread borrower default, while deriving explicit solutions and balance sheet effects even far from the steady state. We find that the effect of falling asset prices is indirect, non-linear, and involves feedback from the banking system in the form of credit contraction. When borrowers repay, the effect ‘passes through’ the bank balance sheet; once borrowers default, asset prices drive bank capital, and constrained credit in turn drives asset prices. This interaction can explain capital crunches, financial instability, and banking crises, either as fundamental or as self-fulfilling outcomes. This model, unlike others, distinguishes between financial and macroeconomic stability, and makes precise the notion of balance sheet vulnerability. It also sheds some light on the role of asset prices in monetary policy and carries regulatory implications. The case studies apply the model to Japan’s Lost Decade, the Nordic Banking Crises, and the US Great Depression.

We examine how collateral affects the cost of debt capital. Theories based on borrower moral hazard and limited pledgeable income predict that collateral increases the availability of credit and reduces its price. Testing these theories is complicated by the very selection problem which they imply: creditors will demand collateral precisely from those borrowers who are riskier. This selection problem leads to a positive relation in the data between the presence of collateral and the loan yield. Analyzing the extensive margin of collateral use, therefore, masks the hypothesized negative impact that collateral exhibits on debt yields. In this paper, we alleviate this problem by focusing on a particular industry and examining its intensive, rather than extensive, margin of collateral use. Using a novel data set of secured debt issued by U.S. airlines, we construct industry-specific measures of collateral redeployability. We show that debt tranches that are secured by more redeployable collateral exhibit lower credit spreads, higher credit ratings, and higher loan-to-value ratios -- an effect which our estimates show to be economically sizeable. Our results suggest that the ability to pledge collateral, and in particular redeployable collateral, lowers the cost of external financing and increases debt capacity.

This paper shows how uncertainty about liquidity demand can lead to a high degree of dollarization in the banking system. I study a model where the demand for currency in each period is random, and where it is easier for banks to borrow in local currency in times of crisis than in dollars. Banks choose a portfolio composed of local currency, dollars, and real loans. Compared to the anticipated transactions demand for each currency, I show that the bank will hold a relatively large amount of dollars and a relatively small amount of local currency. I also show the existence of a dollarization multiplier : as the anticipated transactions demand for dollars increases, the dollarization of the banking sector increases more than proportionately.

A "shock therapy" might have different impacts between large and small firms. In this paper, we focus on the clients of two large failed Japanese banks - the Long-term Credit Bank of Japan (LTCB) and the Nippon Credit Bank (NCB). We first show that subsequent events after the bank failures allowed the new LTCB to adopt a "shock therapy" but kept the new NCB to face "soft budget constraints". We then show that the different therapies made performances of these two banks' customers very different. Under the shock therapy, large firms showed significant recovery of their profits but small firms did not. In contrast, under the soft budget constraints, large firms did not show recovery and small firms experienced significant decline in their profits when the new bank terminated the banking relationship.

Outright bank failures without prior indication of financial instability are very rare. Supervisory authorities monitor banks constantly. Thus, they usually obtain early warning signals that precede ultimate failure and, in fact, banks can be regarded as troubled to varying degrees before outright closure. But to our knowledge virtually all studies that predict bank failures neglect the ordinal nature of bank distress. Exploiting the distress database of the Deutsche Bundesbank we distinguish four different distress events that banks experience. Only the worst entails a bank to exit the market. Weaker orders of distress are, first, compulsory notifications of the authorities about potential problems, second, corrective actions such as warnings and hearings and, third, actions by banking pillar's insurance schemes. Since the four categories of hazard functions are not proportional, we specify a generalized ordered logit model to estimate the respective probabilities of distress simultaneously. Our model estimates each set of probabilities with high accuracy and confirms, first, the necessity to account for different kinds of distress events and, second, the violation of the proportional odds assumption implicit in most limited dependent analyses of bank failure.

In this paper we develop a contingent valuation model for zero-coupon bonds with default. In order to emphasize the role of maturity time and place of the lender's claim in a firm's debt hierarchy, we consider a firm that issues two bonds with different maturities and different seniorage. The model allows us to analyze the implications of both debt renegotiation and capital structure of a firm on the prices of bonds. We obtain that renegotiation brings about a significant change in the bond prices and that the effect is dispersed through various channels: increasing the value of the firm, reallocating payments, and avoiding costly liquidation. Moreover, the presence of two creditors leads to qualitatively different implications for pricing, while emphasizing the importance of bond covenants and renegotiation of the entire debt.

An evaluation problem exists when winding up executory contracts in case of insolvency. The trustee has difficulties in accurately considering the claim for damages that arises if he chooses to reject a contract instead of accepting it. An unequal treatment of creditors and inefficiencies follow. However, a simple reform can solve this problem. If an executory contract is accepted by the trustee, there should be the same claim for damages as if it had been rejected. Only the difference between this claim for damages and the initial claim should be paid directly out of the estate.

We develop a macroeconomic portfolio stress test that is specifically geared towards small and medium-sized banks. We combine a credit risk stress test which simulates credit impairments via a CreditMetrics type multi-factor portfolio model with an income stress test in the form of dynamic panel data regressions. Based on a stress scenario that extends experience of the financial crisis by integrating the current low interest rate environment, we analyse the stress impact on banks' capital ratios. Our results show that savings banks and cooperative banks prove to be very resilient to macroeconomic stress, while more than 6% of our sample's credit banks "fail" the stress test, mainly due to their lack of capital. The main stress drivers prove to be credit impairments rather than other net income components.

We show that the default event defined by endogenous credit-risk models (i.e. low asset values) can likewise be described in terms of low equity prices and negative net cash-flows (high debt service and/or negative earnings). Specifically, distance-to-default (DD), a volatility-adjusted measure of leverage, is given by the ratio of equity prices to negative net cash flows. This implies that the probability of default is the probability of this ratio becoming small, which then depends on the path of these two variables. This helps to explain why just equity prices (price per share, past return, and volatility) and firm’s debt and profitability are significant in reduced-form models that predict default while Merton’s DD becomes redundant if we control for them [Campbell et al. (2008)]. In endogenous models, default is triggered by depressed equity prices and a negative flow to shareholders (rather than low asset value). And, inversely, default concerns are readily lessened by easing refinancing costs (e.g. sovereigns for which default is costly and which regularly roll over their debts), lowering the principal (underwater mortgages or subprime consumer loans, which increases equity value), or raising equity (troubled banks).

The rescue of the US automobile industry amid the 2008–2009 recession and financial crisis was a consequential, controversial, and difficult decision made at a fraught moment for the US economy. Both of us were involved in the decision process at the time, but since have moved back to academia. More than five years have passed since the bailout began, and it is timely to look back at this unusual episode of economic policymaking to consider what we got right, what we got wrong, and why. In this article, we describe the events that brought two of the largest industrial companies in the world to seek a bailout from the US government, the analysis that was used to evaluate the decision (including what the alternatives were and whether a rescue would even work), the steps that were taken to rescue and restructure General Motors and Chrysler, and the performance of the US auto industry since the bailout. We close with general lessons to be learned from the episode.

The Russian banking sector experienced considerable turmoil in the late 1990s, especially around the Russian banking crisis in 1998. The question is what types of banks are vulnerable to shocks and whether or not bank-specific characteristics can be used to predict vulnerability to failures. In this study we employ a parametric logit model and a nonparametric trait recognition approach to predict failures among Russian commercial banks. We modify the trait recognition approach such that the default probabilities are calculated directly without preliminary classification of cells in the voting matrix as safe or unsafe. We test the predictive power of the models based on their prediction accuracy using holdout samples. All models performed better than the benchmark; the modified trait recognition approach outperformed logit and the traditional trait recognition approach in both the original and the holdout samples. As expected liquidity plays an important role in bank failure prediction, but also asset quality and capital adequacy turn out to be important determinants of failure.

In this paper we empirically study interactions between real activity and the financial stance. Using aggregate data we examine a number of candidate measures of the financial stance of the economy. We find strong evidence for substantial spillover effects on aggregate activity from our preferred measure. Given this result, we use a large micro-data set for corporate firms to develop a macro–micro-model of the interaction between the financial and real economy. This approach implies that the impulse responses of a given aggregate shock will depend on the portfolio structure of firms at any given point in time.

Starting from the structural model developed by Merton (1974) and the derived notion of distance-to-default, we study the determinants of credit default swap (CDS) spreads for a sample of European banks over a period from January 2006 to December 2011. In particular, we test variables that are specific to the banking industry and look at the possible interaction with CDS spreads for the related sovereigns. We confirm findings from the literature review regarding the low significance of the structural model and its breakdown in times of stress. We confirm the importance of macro-economic components such as the general level of interest rates and the general state of the economy, particularly in times of stress. We find that before the crisis period the micro- and macro-components are generally predominant in the determination of CDS spread variations while the influence of sovereigns’ CDS become more important when entering further into the crisis period. Interestingly, southern European countries are the first to become significant at the start of the crisis. Progressively, all CDS countries become increasingly significant, overweigh all other explanatory variables and remain so even after the crisis period, thereby suggesting the focused attention of market participants for the sovereign dimension.

In this paper, we examine the existence of a cross-monitoring effect between bank debt and public debt by exploring the effects that loan defaults have on the lead arranger's perceived monitoring ability in the public debt markets. Generating a sample of major loan defaults among U.S. firms between 2002 and 2010, we empirically test the effects that these loans had on the bond returns of publicly traded firms that had existing loans made by the same lead lender as the defaulting firm. We show that the abnormal returns of these "affected firms" are negative and statistically significant. Moreover, these abnormal returns are economically significant - with a mean about -1% when measured over an eleven day window surrounding the announcement of the defaulting loan. Interestingly, we find that these results are even stronger if the defaulting firm had a strong and/or long-standing relationship with its lead lender. We also find that the negative bond market effect is particularly strong if the defaulting loan is an important deal to the lender, if it is a recently originated loan, and if the borrower has better governance, higher profitability and higher firm value in the loan origination year. In contrast, the negative bond market effect is weakened if the affected firms have more intensive analyst coverage and higher firm values. Taken together, these results strongly confirm the existence of a cross-monitoring effect between bank debt and public debt.

We build a structural model of Chapter 13 bankruptcy that captures salient features of personal bankruptcy under Chapter 13. We estimate our model using a novel data set we construct from bankruptcy court dockets recorded in Delaware between 2001 and 2002. Our estimation results highlight the importance of debtor’s choice of repayment plan length on Chapter 13 outcomes under the restrictions imposed by the bankruptcy law. We use the estimated model to conduct policy experiments to evaluate the impact of more stringent provisions of Chapter 13 that impose additional restrictions on the length of repayment plans. We find that these provisions would not materially affect creditor recovery rates and would not necessarily make discharge more likely for debtors with income above the state median income.

This article presents a critical analysis of the principles behind the scope and forms of cooperation between EU Member States and third-country resolution authorities in the context of the 2014 Bank Recovery and Resolution Directive. The article also explores the future responsibilities of the prospective Single Resolution Authority regarding relations between the euro area and third-country resolution authorities.

The two recessions that have hit Italy since the end of 2008 have raised the share of non-performing loans to businesses in banks� portfolios substantially. In this paper we evaluate to what extent the deterioration of credit quality was due not only to the decline in firms� sales during the contraction of economic activity, but also to the level of firms� financial debt at the onset of the first recession. Our results show that, other things being equal, a ten percentage point increase in leverage is associated with a higher probability of default of almost one percentage point. Moreover, the adverse impact of a fall in sales on a firm�s solvency is almost four times greater for firms in the highest quartile of the leverage distribution than for firms in the first quartile. These findings confirm that firms� financial structure can be a powerful amplifier of macroeconomic shocks. A higher level of leverage reduces firms� resilience during a recession, and this in turn weakens the balance-sheets of banks and thus their ability to provide credit.

In spite of the widespread use of generalized additive models (GAMs), there is no well established methodology for simultaneous inference and variable selection for the components of GAM. There is no doubt that both, inference on the marginal component functions and their selection, are essential in this additive statistical models. To this end, we establish simultaneous confidence corridors (SCCs) and a variable selection criteria through the spline-backfitted kernel smoothing techniques. To characterize the global features of each component, SCCs are constructed for testing their shapes. By extending the BIC to additive models with identity/trivial link, an asymptotically consistent BIC approach for variable selection is proposed. Our procedures are examined in simulations for its theoretical accuracy and performance, and used to forecast the default probability of listed Japanese companies.

We are the first to show that the cost of personal bankruptcy filers traveling to their bankruptcy trustees affects bankruptcy choices. We use detailed balance sheet, income statement, and location data from 400,000 Canadian bankruptcies. To control for endogenous trustee selection, we use the location of local government offices as an instrument for the location of bankruptcy trustees (while filers interact with trustees, and trustees interact with local government, filers do not interact with the local government). We find that increased travel costs reduce the number of filings. Furthermore, for those individuals who do file, we find that their increased travel costs need to be compensated by increased financial benefits of bankruptcy. Filers without cars (higher travel costs), as well as those with jobs (higher opportunity costs), receive larger per-kilometer financial benefits from bankruptcy.

We derive an analytic approximation to the credit loss distribution of large portfolios by letting the number of exposures tend to infinity. Defaults and rating migrations for individual exposures are driven by a factor model in order to capture co-movements in changing credit quality. The limiting credit loss distribution obeys the empirical stylized facts of skewness and heavy tails. We show how portfolio features like the degree of systematic risk, credit quality and term to maturity affect the distributional shape of portfolio credit losses. Using empirical data, it appears that the Basle 8% rule corresponds to quantiles with confidence levels exceeding 98%. The limit law's relevance for credit risk management is investigated further by checking its applicability to portfolios with a finite number of exposures. Relatively homogeneous portfolios of 300 exposures can be well approximated by the limit law. A minimum of 800 exposures is required if portfolios are relatively heterogeneous. Realistic loan portfolios often contain thousands of exposures implying that our analytic approach can be a fast and accurate alternative to the standard Monte-Carlo simulation techniques adopted in much of the literature. © 2001 Elsevier Science B.V.

We investigate financial intermediaries' interest rate risk management as the simultaneous decision of on-balance-sheet exposure and interest rate swap use. Our findings show that both decisions are substitute risk management strategies. A higher likelihood of bank distress makes banks reduce their on-balance sheet interest rate exposure and simultaneously intensify their swap use. Exogeneity tests indicate that both decisions are only endogenous to each other for banks that start using swaps for the first time. For other banks, the maturity gap is endogenous to the decision to use swaps, but the reverse relationship is exogenous. For banks with trading activity, both decisions are exogenous to each other. We interpret these findings as the maturity gap being largely determined by customer liquidity needs, whereas the decision to use swaps relies on compliance with the interest rate risk regulation. Although hedging motives dominate, we find selective hedging behavior in swap use driven by the slope of the yield curve as well as by funding uncertainty.

Our paper addresses firm size as a driver of systematic credit risk in loans to small and medium enterprises (SMEs). Key contributions are the use of a unique data set of SME lending by over 400 German banks and relating systematic risk to the size dependence of regulatory capital requirements. What sets our sample apart is its comprehensive coverage of the particularly rich and well developed credit market for SMEs in Germany. We estimate asset correlations as the key measure of systematic risk from historical default rates. Our results suggest that systematic risk tends to increase with firm size, conditional on the respective rating category. We also compare the size of this effect with the capital relief that has been granted in Basel II for SMEs relative to large firms. For SME loans in the corporate portfolio of the Internal Ratings-Based Approach and also for SME loans treated under the revised standardized approach of Basel II, our asset correlation estimates suggest a significantly larger relative difference from large firms than reflected in the regulatory capital requirements.

Financial constraints are not directly observable, so empirical research relies on indirect measures. We evaluate how well five popular measures (paying dividends, having a credit rating, and the Kaplan-Zingales, Whited-Wu, and Hadlock-Pierce indices) identify firms that are financially constrained, using three novel tests: an exogenous increase in a firm's demand for credit; exogenous variation in the supply of bank loans; and the tendency for firms to pay out the proceeds of equity issues to their shareholders ("equity recycling"). We find that none of the five measures identifies firms that behave as if they were constrained: public firms classified as constrained have no trouble raising debt when their demand for debt increases, are unaffected by changes in the supply of bank loans, and engage in equity recycling. The point estimates are little different for supposedly constrained and unconstrained firms, even though we find important differences in their characteristics and sources of financing. On the other hand, privately held firms (particularly small ones) and public firms with below investment-grade ratings appear to be financially constrained.

This paper quantifies the “human costs of bankruptcy” by estimating employee wage losses induced by the bankruptcy filing of employers using employee-employer matched data from the U.S. Census Bureau’s LEHD program. We find that employee wages begin to deteriorate one year prior to bankruptcy. One year after bankruptcy, the magnitude of the decline in annual wages is 30% of pre-bankruptcy wages. The decrease in wages persists (at least) for five years post-bankruptcy. The present value of wage losses summed up to five years after bankruptcy amounts to 29-49% of the average pre-bankruptcy market value of firm. Furthermore, we find that the ex-ante wage premium to compensate for the ex-post wage loss due to bankruptcy can be of similar magnitude with that of the tax benefits of debt.

Theory predicts that information noise induces interactions between the degree of noise and default/bankruptcy determinants (Duffie and Lando [2001, Econometrica 69, 633–664]). Using well-known bankruptcy hazard models and over two million firm-months of data during 1979-2012, we demonstrate the existence of the noise-induced interactions. We also find strong evidence consistent with the important implications of the interactions on causality inference and prediction of credit risk. Empirically, covariates have complicated, non-monotonic causal effects on credit risk, and higher degree of noise markedly reduces predictability of hazard models. Additionally, incorporating the interactions within hazard specifications significantly improves in-sample model fit and out-of-sample forecasting accuracy. The improvements in empirical performance are persistent over time, robust to empirical choices, and more substantial when information quality is poor.

Can debt rescheduling decisions differ in multiple lenders’ versus a single lender loan? Do multiple lenders efficiently react to information? We show that the precision of information plays an essential role. Foreclosing by one lender is disruptive so that a lender can rationally wait for the decision of other lenders, rescheduling her loan, if she expects that other lenders receive more precise information. We develop a Bayesian game where signals of different precision are randomly distributed to lenders. Both, premature liquidation and excessive rescheduling are possible in equilibrium, according to the pattern of information. However this is a second-best outcome, given that private information cannot be optimally shared.

This paper presents a model where bank credit depends upon borrowers.product market structure. We show that a larger number of competitors in the industry may increase credit availability by enhancing the resale value of the collateralized productive assets. We also study how this bene.t of competition is affected by the existence of outsiders willing to bid for the collateralized productive assets of the insiders. Our model encompasses the standard case of Cournot competition either when the default probability goes to zero or when there are multiple outsiders bidding for the productive assets. We test the empirical implications of the theoretical analysis exploiting information on the access to finance of small and medium Italian firms and find supportive evidence.

This paper attempts to assess the economic significance and implications of collateralization in different financial markets, which is essentially a matter of theoretical justification and empirical verification. We present a comprehensive theoretical framework that allows for collateralization adhering to bankruptcy laws. As such, the model can back out differences in asset prices due to collateralized counterparty risk. This framework is very useful for pricing outstanding defaultable financial contracts. By using a unique data set, we are able to achieve a clean decomposition of prices into their credit risk factors. We find empirical evidence that counterparty risk is not overly important in credit-related spreads. Only the joint effects of collateralization and credit risk can sufficiently explain unsecured credit costs. This finding suggests that failure to properly account for collateralization may result in significant mispricing of financial contracts. We also analyze the difference between cleared and OTC markets., https://ia601508.us.archive.org/32/items/examining-collateralization-6/examining-collateralization-6.pdf

The two channels of default on unsecured consumer debt are (i) bankruptcy, which legally grants partial or complete removal of unsecured debt under certain circumstances, and (ii) delinquency, which is informal default via nonpayment. In the United States, both channels are used routinely. This paper introduces a model of unsecured consumer credit in the presence of both bankruptcy and delinquency. Our model yields three new findings: First, with respect to the choice between bankruptcy and delinquency, labor income shocks matter. Specifically, we find delinquency is readily used by borrowers with the worst labor market outcomes, even those with relatively minor levels of debt. In contrast, bankruptcy is used by households with relatively high debts, but whose long-run earnings prospects are high enough to make interest rate penalties from delinquency too large. Second, financial distress is persistent: households in poor financial conditions stay in that state for several quarters. Third, in broad terms, bankruptcy and delinquency are “substitutes,” with bankruptcy increasing as delinquency costs rise.

This paper investigates the information in corporate credit ratings. If ratings are to be informative indicators of credit risk they must reflect what a risk-averse investor cares about: both raw default probability and systematic risk. We find that ratings are relatively inaccurate measures of raw default probability - they are dominated as predictors of failure by a simple model based on publicly available financial information. However, ratings do contain relevant information since they are related to a measure of exposure to common (and undiversifiable) variation in default probability ('failure beta'). Systematic risk is shown to be related to joint default probabilities in the context of the Merton (1974) model. Empirically, it is related to CDS spreads and risk premia. Given the multidimensional nature of credit risk, it is not possible for one measure to capture all the relevant information.

We analyse the effect of differing uncertainty assumptions on the costs of shareholder-bondholder conflicts arising from partially debt-financed investments. A partial equilibrium model, valid for a large class of diffusion processes, is developed and then applied to the specific cases of a geometric Brownian motion (GBM) and a mean-reverting (MR) process. This allows for the comparison of the two scenarios and contributes to the ongoing discussion on the effects of mean reversion on investment and financing behaviour. We find that agency costs are much lower under MR dynamics and, through the application of a novel agency cost decomposition, we show that for a high expected growth in future profits (high growth GBM) agency costs are driven mainly by suboptimal financing decisions, as opposed to suboptimal (default and investment) timing decisions. The situation is reversed for lower growth assumptions and for an increase in the speed of mean reversion. Our results on the components and drivers of agency costs are valuable to both policy makers and regulators alike.

In CPB Discussion Paper 209 we study incentives of financial intermediaries to reserve liquidity given that they can rely on the interbank market for their liquidity needs. Intermediaries can partially pledge their assets to each other, but not to the rest of the economy. Therefore liquidity provision is endogenous. We show that if the probability of a crisis is large or if assets are slightly pledgeable, then all intermediaries reserve liquidity. However, if the probability of a crisis is small or if assets are highly pledgeable, then intermediaries segregate ex ante: some reserve no liquidity, others reserve to the maximum and become liquidity providers. This segregation arises, because in the latter case the crisis short-term rate exceeds the returns on long-term investments, while at the same time higher liquidity holdings also increase survival probability. Together, these two effects result in increasing marginal returns to liquidity in the crisis state, and, consequently, segregation ex ante. In either equilibrium, aggregate liquidity is too small if assets are not fully pledgeable. Minimum liquidity requirements only improve welfare in the symmetric equilibrium. Marginally lowering the interest rate causes a marginal crowding-out of private liquidity with public liquidity in the symmetric equilibrium, but a full crowding-out in the asymmetric equilibrium.

Banks hold liquid and illiquid assets. An illiquid bank that receives a liquidity shock sells assets to liquid banks in exchange for cash. We characterize the constrained efficient allocation as the solution to a planner's problem and show that the market equilibrium is constrained inefficient, with too little liquidity and inefficient hoarding. Our model features a precautionary as well as a speculative motive for hoarding liquidity, but the inefficiency of liquidity provision can be traced to the incompleteness of markets (due to private information) and the increased price volatility that results from trading assets for cash.

Private Equity restructuring of companies using debt finance has been criticised for increasing financial distress and bankruptcy in the corporate sector and this was especially so in the aftermath of the financial crisis. We build a unique data set comprising the population of over eight million company year observations and 153,000 instances of insolvency covering the period 1995-2010 and encompassing the recessionary cycle. We examine the whole spectrum of buyout ownership types (pre and post buyout) in comparison with the private and public corporate population and over time. We provide direct evidence relating to whether buyouts and buy-ins, private equity backed or not, are more or less likely to fail in terms of entering formal insolvency proceedings than other firms and how this varies over the economic cycle. Controlling for size, age, sector and macro-economic conditions (base hazard) we find that private-equity backed buyouts are no more prone to insolvency than the non-buyout population and pre-buyout credit risk. Conditioning on company performance and operational characteristics we show that PE-backed companies do not carry more insolvency risk than other (distressed) companies and other buyout types. We find that leverage does not distinguish buyouts that fail from those that survive.

I propose a new procedure for extracting probabilities of default from structural credit risk models based on model implied credit spreads (MICS) and implement this approach assuming a barrier option framework nesting the Merton (1974) model of capital structure. MICS are the increase in the payout to debt-holders necessary to oset the impact of an increase in asset variance on the option value of debt and equity. In contrast to real-world credit spreads, MICS do not contain risk premia for default timing and recovery uncertainty, thus yielding a purer estimate of physical default probabilities. Relative to a standard distance to default (DD) measure, my measure (i) predicts higher credit risk for safe rms and lower credit risk for rms with high volatility and leverage (ii) requires fewer parameter assumptions (iii) clearly outperforms the DD measure when used to predict corporate default.