It takes two to tango: An empirical tale of distressed firms and assisting banks

International Review of Law and Economics 26 (2006) 429–454

It takes two to tango: An empirical tale of distressed firms and assisting banks Oscar Couwenberg a,∗ , Abe de Jong b a

University of Groningen, Faculty of Law, Department of Law and Economics, P.O. Box 716, 9700 AS, Groningen, The Netherlands b RSM Erasmus University, The Netherlands

Abstract We study the restructuring process of small and medium-sized firms in financial distress. We have a unique dataset with firms in the Netherlands that are assisted in their restructuring effort by banks. Part of our dataset consists of firms that successfully restructure their operations and obligations with the help of their bank. Another part consists of firms that, despite the assistance of their bank, did not succeed in reorganizing their operations and finances. Our empirical test predicts success and failure in restructuring. We find that banks play a role in the firms’ restructuring efforts and that this assistance is of crucial importance to the success of the restructuring. We conclude that the harsh bankruptcy rules in the Netherlands support private negotiations between financially distressed firms and their banks. © 2007 Elsevier Inc. All rights reserved. JEL classification: G21; G33; K22; K33 Keywords: Bankruptcy; Debt restructuring; Financial distress; Reorganization

1. Introduction Situations of financial distress have a major impact on a firm and on its stakeholders. In order to prevent further wealth-dissipation, the firm’s managers need to undertake substantial corrective action. This corrective action can be taken informally, where, among others, firms aim to renegotiate the terms of debt contracts with creditors without using a bankruptcy ∗

Corresponding author. E-mail addresses: [email protected] (O. Couwenberg), [email protected] (A. de Jong).

0144-8188/$ – see front matter © 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.irle.2007.01.001

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procedure. A second possibility for the firm’s management or its creditors is to petition for bankruptcy, in which the process of restructuring is partially defined by legal procedures. It is obvious that the expected behavior of a firm’s management and its creditors in the formal procedure has a strong impact on the incentives of both parties to reach an informal agreement. In harsh, or creditor-oriented, bankruptcy systems the possibility to reorganize is limited. This implies that the pressure on informal reorganization is high, because of the threat of liquidation. In soft, or debtor-friendly, systems reorganizations are part of the formal procedure, which limits the incentive to strive for a settlement outside the procedure. In this paper we provide empirical evidence on informal reorganizations under a harsh regime. Bankruptcy systems and legal procedures differ between countries. Most studies of firms in bankruptcy concern the United States (US), which has a soft, debtor-oriented, system. Its reorganization procedure, Chapter 11, shields the firm from its creditors. A harsh creditororiented system prevails in the United Kingdom (UK) and its main objective is the repayment of creditors’ claims (Franks & Torous, 1996).1 Most other systems, either resemble the US or the UK system, or mix these two extremes. For example, in Germany and France new systems have been implemented recently that are less harsh than the UK system, but still not so debtor friendly as Chapter 11 in the US (Couwenberg, 2001; Kaiser, 1996; White, 1996). In Japan, a procedure similar to Chapter 11 exists, extended with a screening of cases for viability (Eisenberg & Tagashira, 1994). Our analysis concerns distressed firms in the Netherlands where Dutch firms face a harsh bankruptcy system. The institutional setting makes only two outcomes of a restructuring process possible: firms restructure successfully and stave off bankruptcy, or firms end up in the formal bankruptcy procedure. Because the Dutch setting – together with the UK system – is on the other side of the continuum with the often-studied US system, our study provides an interesting experiment of the value of a harsh system in reorganizations. We study the process of restructuring in financially distressed small to medium-sized Dutch enterprises. Our sample is unique in that it contains small and medium-sized, nonquoted, firms that are successful in their restructuring efforts and firms that are not. We are able to compare their characteristics and identify the factors that contribute to their success, or failure, in restructuring the business. For the firms in our sample, banks play a crucial role in covering their financing needs and thus, presumably, also play an important role in resolving financial distress. Our study resembles Franks and Susmann (2005). They study financial distress and bank debt restructuring of small and medium-sized enterprises in the UK and find that the contingent control rights associated with legal security rights put banks in nearly full control over the firm in the event of default. Banks make very limited concessions, but cannot be characterized as lazy in their efforts. Our sample consists of 73 firms that were monitored by their main bank. Out of this sample, 51 firms (69.9%) restructured successfully, while 22 firms (30.1%) failed and went bankrupt. We study the characteristics before reorganization, the measures taken in the process of reorganization, and we discriminate between factors that do or do not distinguish success from failure. Our main findings are that banks appear to be informed about 1 The recently enacted Enterprise Act 2002 changed the UK system. It imposes the duty upon the administrator to attempt a business rescue if this is in the interest of creditors. It also limits the possibilities of secured creditors to control the bankruptcy process. See http://www.insolvency.gov.uk/.

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the pre-distress indebtedness and choose to restrict their lending to unsuccessful firms. The analysis of the restructuring measures shows that many firms take operational measures and effectuate measures that banks advice, together with measures related to restructuring the bank’s debt. We find that the success of restructuring efforts depends mainly on operational measures that are induced by banks. Our findings illustrate that under the Dutch harsh rules the threat of bankruptcy is present, which puts pressure on both bank and firm to restructure privately. We conclude that harsh bankruptcy rules support the private negotiations between financially distressed firms in our sample and their banks. However, the success of restructuring is not simply dependent on the bankruptcy threat. Both the firm’s management and the main bank have to agree on the restructuring plan, i.e. “it takes two to tango”. The paper is structured as follows. In Section 2 we describe the institutional characteristics of the Dutch setting and discuss the different incentives that can be discerned in a financial distress situation. In Section 3 we describe our dataset. Section 4 presents our results. Section 5 summarizes the empirical results and relates the findings to the theoretical discussion. Section 6 concludes.

2. Restructuring small firms in financial distress In this section we discuss the Dutch institutional setting and the current literature. We first describe and characterize the Dutch bankruptcy system in order to understand the influence it has on the incentives to restructure privately (Section 2.1). Next, we describe the practice of banks in assisting failing firms (Section 2.2). We discuss the theoretical views on the incentives in restructuring processes and the related empirical evidence (Section 2.3). Finally, we discuss the specifics of small firms in financial distress (Section 2.4). 2.1. The Dutch bankruptcy system The Dutch bankruptcy system can be characterized as an auctioning system, with a rudimentary reorganization provision (Couwenberg, 2001).2 The system is similar to the Swedish code (see Thorburn, 1999) and the pre-1993 Finnish procedures (see Sundgren, 1998). Within the bankruptcy system a suspension of payments procedure is included, which aims at firms in financial distress with sufficient prospects to recover in short time. The firm is sheltered from its creditors by an automatic stay provision of up to 2 months. Apart from the automatic stay, the suspension procedure applies only to ordinary creditors and suspends all individual debt collection procedures. Secured and preferred creditors are not bound by this procedure. As a result, write-downs on the secured and preferred claims by these creditors are voluntarily. In the suspension procedure, the firm has the option to offer a composition (i.e. settlement) to the ordinary creditors (other than secured and preferred creditors). The procedure ends in case the creditors accept the terms of the composition. In comparison with the bankruptcy procedure, the suspension procedure is less intrusive in the 2 At the beginning of 2005 changes to the Act have come into force, which are aimed at a strengthening of the restructuring potential. We do not discuss these rules because we study financially distressed and bankrupt firms before these changes took effect.

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operational activities and in the rules by which creditors are bound. In case the composition in the suspension procedure fails, firms cannot opt again for this procedure and firms can also not opt for the identical composition procedure in bankruptcy. For firms that do not use the suspension of payment procedure, only the bankruptcy procedure remains. Both firms and creditors may petition for bankruptcy. The aim of the procedure is to satisfy the claims of creditors. At the start of the bankruptcy proceedings, an independent trustee is appointed by the court and replaces the incumbent management team. This trustee has a fiduciary responsibility to creditors. The procedure offers the trustee the possibility to continue operations for some time. As in the suspension procedure the firm is sheltered from its creditors by an automatic stay provision of up to 2 months. During this period a trustee may continue daily operations, but is not allowed to sell important assets in order to fund the operations. Debtor-in-possession financing is obtainable, but can only be secured with unencumbered assets available to the estate. If a composition is not attainable, then the trustee organizes a sale of all assets, either piecemeal or as a going concern. This sale may take the form of a private sale of assets or a public auction. The proceeds of this sale are distributed according to absolute priority. Administrative costs, estate-financing and taxes accrued during the period of continuation in bankruptcy have super-priority. Secured claims are entitled to receive the proceeds of the sale of the collateral, while any unpaid part is treated as an unsecured claim. Next in line are audit claims, tax claims, wage claims, and finally, unsecured claims. In the Netherlands, despite the facilities in a suspension of payments procedure, almost all suspension proceedings end in formal bankruptcy proceedings. Apparently, the procedure is ineffective in reorganizing firms. A key reason for the ineffectiveness is that the procedure only applies to ordinary creditors. Furthermore, buyers of assets from firms in a suspension procedure have to accept all employee contracts associated with the assets, which is not the case in bankruptcy. Therefore, the reorganization of firms via an asset sale is normally postponed until the firm enters the bankruptcy procedure (Couwenberg, 1997). From this description of the Dutch legal and institutional setting it becomes evident that when firms desire to continue their activities in their present form, it is paramount to stay out of bankruptcy proceedings. Although bankruptcy does not necessarily lead to the demise of the firm, it leads to a loss of control – and the associated benefits thereof – and often to a diminished scale of activities. In comparison with the Chapter 11 procedure in the US bankruptcy code the Dutch code can be classified as a harsh system for three reasons. First, given the loss of control, the management of Dutch firms has no incentive to file for bankruptcy in order to restructure the firm. This is not the case under the American procedure of Chapter 11, in which management retains control initially for at least 120 days in order to draft a restructuring plan. Second, Dutch bankruptcy rules provide for an automatic stay for a maximum of 2 months. Chapter 11 stays individual creditors collection efforts for 6 months and this period may be extended by the court. Management continues to control operations, which includes asset deployment decisions, although approval of the court is in some instances needed. Debtor-in-possession financing may obtain different levels of preferential treatment in Chapter 11. The third difference between the two codes lies in the rules concerning the composition. A firm offering a composition to ordinary creditors still has to pay the claims of preferred and secured creditors in full, or has to reach a bilateral agreement with those creditors. These

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non-ordinary creditors may hold out, jeopardizing the entire restructuring. In Chapter 11, all creditors (secured, preferred, ordinary and subordinated) and shareholders vote on a restructuring plan. Only impaired creditors may vote on the plan. A creditor is considered unimpaired if the plan, from a legal and equitable perspective, leaves its contractual claim intact. A plan is deemed to be accepted by a class of creditors if a qualified majority of the creditors in that class vote in favour of the plan. In case one class votes against, the court may still confirm the plan, in case it is deemed fair and equitable (“cram down” provision). The rules in Chapter 11 make it possible to mitigate strategic behavior by participants.3 To summarize, in comparison with the US, the Dutch system gives the trustee the option to continue operations for up to 2 months, while management loses control over the firm, has limited possibility to keep secured creditors at bay and cannot force other than ordinary creditors to comply with a restructuring plan. These differences show that the Dutch bankruptcy rules are creditor-oriented, where Chapter 11 in the US is debtor-oriented. In comparison with the UK procedures, the Dutch systems seems slightly less harsh. Before the Enterprise Act 2002 was enacted, secured creditors in the UK had the possibility to convert control over the most important reorganization procedure – administration – towards themselves by appointing a (administrative) receiver. Secured creditors had every incentive to do so, because such a strategy gave them more control rights than they could obtain in an administration.4 Especially this aspect of a take-over of control by the secured creditor makes the UK system harsher than the Dutch system. The UK system resembles the Dutch system in other aspects, for instance the availability of an automatic stay and cram down provision in other but not often used reorganization oriented procedures. 2.2. Dutch banks Banks in the Netherlands have specialized departments, i.e. work-out departments, which deal with firms in financial distress.5 These offices are hierarchically organized. The smallest firms in distress remain under the surveillance of local offices. The small to mediumsized debtors in financial distress are transferred from local offices to headquarter-based work-out departments. The departments are enlisted when the loan size passes a threshold and (combinations of) additional criteria are met, e.g. firms do not meet debt covenants, profitability is too low, or equity is insufficient. Specialized employees in these work-out departments deal with the largest and exchange-listed firms in financial distress. All the firms in our study have been assisted by bank employees of the work-out departments located at the headquarters of Dutch banks. The employees of work-out departments take over the tasks of local offices with respect to these firms. They advise firms on restructuring activities 3 In Chapter 11 some participants have relatively strong negotiation power over the terms of the reorganization plan. Evidence for this is the deviation from the absolute priority rule in Chapter 11 cases. See, among others, Franks and Torous (1994) and Tashijan, Lease, and McConnell (1996). 4 The administrative receivership procedure makes up the better part of “reorganization” cases under the UK code. The liquidation procedure accounts for the majority of the bankrupcty cases (86%). See Couwenberg (2001) for these figures. See Franks and Torous (1996) for instance for a comparison of the US and the UK system. 5 These departments have euphemistic names, such as ‘special loans’ (bijzondere kredieten). The departments also have nicknames that plainly indicate their activities, e.g. ABN-AMRO’s special loan department is called ‘the wreck station’ (de wrakkencentrale). See NRC Handelsblad of June 5, 2003.

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and propose debt-restructuring arrangements, which have to be approved by internal credit committees in the bank. The advice is not to be taken lightly, because banks are in the position to extend additional financing contingent upon operational and financial adjustments. Firms have to respond either by following the brunt of the advised measures, look for other ways to obtain credit from new financiers, or prepare to be taken over. When distressed firms do not manage to renegotiate with the bank and to restructure, the bank will strive to end the financing relationship with the firm. In many instances this will imply bankruptcy. 2.3. Literature on banks and restructuring A key question in debt restructuring processes concerns the behavior of banks. Restructuring situations confront banks with a multitude of incentives. These incentives are associated with security arrangements, anticipated strategic behavior by entrepreneurs, and bankruptcy rules. Security by means of collateral may lead to a lazy attitude of the bank, which implies that too little effort will be expended to help firms restructure.6 Banks do not need to undertake corrective actions, as long as the value of the assets securing a loan exceeds this bank debt. Corrective actions may be primarily focused on the value of the bank debt. For example, banks can demand partial repayment, lower their credit ceilings, and demand additional collateral. This lazy attitude is in contradiction with the advantageous position of the bank concerning the quality and timeliness of information. Banks are better informed and equipped than other creditors to monitor borrowers and may thus be expected to react timely to adverse economic developments. Thus, banks’ laziness is not optimal from a firm’s perspective. If banks are indeed lazy ex post, the hypothesis follows that banks do too little, too late, i.e. they do not react timely to a financial distress situation and their reaction is not sufficient to help the firm restructure successfully. In contrast to the incentive to be lazy in restructuring processes, two incentives for banks work in the opposite direction. One of these comes from the literature on incomplete financial contracting. The argument is that secured debt is a necessary tool to mitigate strategic asset deployment by the entrepreneur, or claim dilution (Gorton & Kahn, 1993; Hart, 1995; Hart & Moore, 1998). Secured debt gives credence to the threat to take the assets from the entrepreneur. As a result it is efficient that banks hold collateral. However, banks remain vulnerable to expropriation down to the level of the liquidation value of the assets. In this case a firm might force the bank to forgive part of the principal of a loan. Franks and Susmann (2005) call this the “soft bank effect”. The empirical implication of this theory is that banks in some cases will be forced to forgive part of the principal of a loan, or roll over loans. 6 Laziness may be the result of a risk-return trade-off. Senior/secured creditors have an incentive to opt for low risk liquidation instead of high-risk continuation via new financing (Myers, 1977). Such creditors thus hold out on the restructuring effort. We consider laziness and holdout as synonyms. Hart (1995) models such behavior in an incomplete financial contracting setting. Manove, Padilla, and Pagano (2001) develop another argument to explain laziness. In their model well-secured banks under-invest in project screening activities. However, laziness at the project-screening phase does not necessarily imply laziness at the restructuring phase. The authors suggest that laziness is one of the prime elements in the argument to limit the possibility to contract for collateral.

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The second incentive for banks to actively help restructure firms is associated with dispersed debt and harsh bankruptcy rules.7 Bolton and Scharfstein (1996), Berglof and von Thadden (1994) and Berglof, Roland, and Von Thadden (1999) show that dispersing debt among many creditors disciplines management and reduces strategic behavior. The collective-action problem, which is raised by dispersing debt, creates such costs that it becomes impossible to organize a collective (out-of-court) debt restructuring. Dispersed debtholders have no incentive to credibly commit to renegotiation, due to the fact that a creditor who moves first can recoup more of her claim than if she waits for the others in order to equally share the proceeds.8,9 If each creditor possesses the right to liquidate the firm, then management needs to avoid renegotiation with these creditors in order prevent the loss of any going concern surplus value. Empirically, when collective action costs are sufficiently high, this would mean that one would not observe out-of-court renegotiations with dispersed debtholders. One of the assumptions associated with the analysis of the effects of dispersed debt is the type of bankruptcy rules that is present in a country. Harsh bankruptcy rules, i.e. rules that do not incorporate the possibility of reorganization, imply that reorganization needs to be done privately. Such rules enforce the liquidation rights of individual creditors, effectively inducing costs of overcoming collective-action problems ex ante. Ex post, harsh rules do not give the firm a viable option to re-contract with all its creditors, effectively blocking a restructuring attempt. However, if one includes a large lender among the multitude of creditors, i.e. a bank, the collective-action costs force the firm to start private renegotiations with the bank in order to stay out of bankruptcy and prevent the loss of any going surplus value. Such harsh rules may thus strengthen the incentive for banks to privately renegotiate due to the collective-action problem among dispersed debtholders. Soft bankruptcy rules, with reorganization provisions, as in Chapter 11, on the other hand provide firms and debtholders a costly procedure to eliminate collective action problems associated with debt that is both public and dispersed. Firms then, apart from turning to their bank, have the option to restructure financial claims in a bankruptcy procedure. Theoretical research shows that in these systems bank debt will be senior and secured and shorter in maturity than public debt. Furthermore, banks will not reduce the value of their claim, although super-priority status makes it attractive for banks to provide new funds (see Bulow & Shoven, 1978; Diamond, 1993; Gertner & Scharfstein, 1991; John & Vasudevan, 1995; White, 1980). From this it follows that firms face a trade-off in choosing between a private restructuring and a formal reorganization, i.e. cost savings associated with a private restructuring, mainly by preventing a destruction of going-concern firm value versus the costs associated with creditors holding out on a restructuring proposal (see Gilson, John, & Lang, 1990). High costs relative to the savings will drive the firm into a Chapter 11 procedure. The holdout 7 In our sample, most firms have a bank as dominant creditor. Therefore, we do not investigate situations with multiple creditors, in which coalition problems between creditors and the firm arise. See Bigus (2002) for recent work on conflicts between creditors and formation of coalitions. 8 The situation is further complicated by the costs of acquiring information, information asymmetries and strategic behavior by the firm or its associated insiders. These factors make it difficult for individual small creditors to accept any restructuring plan at face value. 9 Especially, trade creditors have the right to individually collect debts the company owes them. The position of these creditors contrasts with dispersed public debtholders, who normally need to act via a trust office.

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problem may be especially severe in private restructurings which are characterised by a large number of creditors, a high degree of heterogeneity in the debt claims, and information asymmetries between the different classes of claimholders. In the empirical part of their paper, Gilson et al. (1990) find that private renegotiation is most likely to succeed when more of the assets of the firm are intangible, more debt is owed to the bank and the debt structure is relatively homogeneous. Asset intangibility proxies for the costs associated with (potential) destruction of firm value in bankruptcy. Bank debt proxies for the effect that private renegotiation is easier when debt is privately placed instead of dispersed among many (trade) creditors, while the number of debt contracts proxies for heterogeneity of the debt. Other empirical evidence on firm restructuring mostly line up with the theoretical arguments above. For instance, Asquith, Gertner, and Scharfstein (1994) find that for distressed junk bonds issuers, banks do not forgive principal payments outside Chapter 11 and take only rarely equity.10 Furthermore, the provision of additional financing to these firms occurs only in Chapter 11 procedures. In contrast, though, Gilson (1990) finds that banks receive stock in debt restructurings and Chapter 11 reorganization plans. Covenants in bank lending agreements also change, because banks claim additional collateral and veto power over investment and financing decisions. James (1995) finds that only when public debtholders restructure their claims, banks are willing to take a relatively large stake of equity. 2.4. Distress in small firms For small firms, the role of banks must be – out of necessity – even more important than the research on large firms reveals. Shareholders in small firms are most likely cashconstrained, because otherwise the firm would not be in financial distress. Up till distress, banks are not particularly focused on the performance of borrowers, due to monitoring costs and liquidation rights associated with the collateral. Furthermore, illiquid equity markets for small firm equity stakes and regulatory capital requirements, make that banks will not be very interested in becoming shareholders of small firms. However, without the upside potential associated with a successful restructuring, banks have limited incentives to assist small distressed firms to recover (Hart, 1995). In small firm’s lending relationships we thus expect collateral to induce the incentive for banks to be lazy. The empirical implication is that no economically significant differences exist in restructuring activities supported or proposed by banks, between firms in or outside bankruptcy. One may argue that trade creditors in small firms play the role of public, dispersed debtholders in large quoted firms. Trade creditors might be unwilling to extend credit by lengthening the credit period, because of a lack of information and free riding by the others. If a small firm lends from one bank and a large number of trade creditors, then the situation arises where the firm can only turn to the bank for help to restructure out-of-court. Two incentives point in the opposite direction of the incentive for banks to be lazy, i.e. the incentives associated with the “soft bank effect” and with dispersed trade creditors. The empirical implication of this reasoning is that both incentives point in the opposite direction 10 Bergstr¨ om, Eisenberg, and Sundgren (2002) find that in Finland well-secured creditors also are most likely to oppose reorganizations.

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of lazy banks, because banks forgive debt if debt levels are higher than liquidation values and aim to assist in restructuring the firm, especially in case trade creditors are difficult to control. Of course, if banks are able to correctly discriminate beforehand between firms with and without good prospects of recovery, they will focus their efforts on potentially successful restructurings. The only large-scale empirical evidence about restructuring efforts of small firms is provided by Franks and Susmann (2005). They find for small UK firms that banks do not forgive or scale down principal payments and only rarely provide additional financing, but frequently succeed in reducing their outstanding loans. In their sample the additional financing comes from trade creditors. In this manner the banks in their sample are tough, even though the UK does not seem to have any soft bankruptcy rules to counteract the tendency to over-liquidate.

3. Data The dataset in this study consists of Dutch firms that encountered financial distress and received assistance from banks. Part of the firms in our sample managed to restructure successfully, while others failed. We obtained files about bank assistance of restructuring firms directly from banks. The data in this study is provided by the three largest banks in the Netherlands, i.e. ABN-AMRO, ING Bank and Rabobank. All firms in our samples have been assisted by employees of the work-out departments of the banks’ headquarters. The banks were prepared to fully disclose their files on the financially distressed firms. These files contain financial information, such as income statements and balance sheets. The bank’s files also contain detailed information about the restructuring measures by the bank, but also by other parties. The restructuring processes in our sample cover the period from 1981 until 2000.11 Our sample of successfully restructured firms is based on the following procedure. We obtained lists of distressed firms from the three banks. All firms that eventually ended up in bankruptcy or suspension of payment were removed from the list.12 Because the resulting list was still too long to cover completely, we picked 20 to 30 cases per bank and asked the banks to retrieve these files. Not all files were retrievable anymore and some were incomplete. Ultimately, we retrieved 51 files of firms in financial distress.13 Our sample of bankrupt firms has been selected in another way. This list was build from bankruptcy filing 11 Our data sampling procedure induces a bias in the distribution of cases over time. The information about unsuccessful firms is measured earlier in time, because the bankruptcy procedures of these firms had to be officially ended in order to be included in our sample. As a consequence, the data concerning successful restructurings is slightly more recent than the unsuccessful cases. The median years of the end of restructuring or bankruptcy are 1995 (unsuccessful) and 1998 (successful). 12 This does not guarantee that a firm on our list never entered bankruptcy proceedings. However, firms were not involved in bankruptcy while the bank was supplying any form of financing. If the firm changed banks, or was taken over, then the information on future performance was obviously not available. 13 We were not able to retrieve consistent time-series data on the firms, due to the fact that in nearly all the successful cases the borrower returned to the local branch and it proved too much effort and time to reclaim the files. In other instances change of bank and take-overs prevented us from collecting that data.

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records of different regional court jurisdictions in the Netherlands. Based upon this list, the appointed trustees were asked to provide case details. In this project 139 bankrupt firms have been included. The names and addresses of these 139 firms were matched with the names and addresses in the banks’ databases. This procedure yielded 22 firms on which enough data was available on the restructuring phase before these firms filed for bankruptcy.14 In total we have 73 firms of which 51 (70%) restructured successfully and of which 22 (30%) were not successful in their restructuring attempts and thus had to file for bankruptcy. It should be clear from the outset that our sample has a selection bias. All firms have been under surveillance by banks. This implies that our outcomes are conditional on bank involvement in the process of restructuring. Firms also become distressed and solve their problems without involvement by banks, or firms initiate bankruptcy proceedings without prior assistance by banks. These firms do not enter our sample selection procedure.

4. Results The dataset consists of two samples. The first set includes 51 “successful firms”, i.e. firms that restructured under the guidance of a bank and managed to stay out of formal bankruptcy proceedings. The second set includes 22 “unsuccessful firms”, i.e. those that ended in bankruptcy despite the banks’ assistance. In this section we first describe the size and activities of successful firms and their unsuccessful peers in order to test whether the groups are comparable (Section 4.1). Subsequently, we describe the reasons of the distress and the outcomes of the restructuring processes (Section 4.2). Both for the successful and unsuccessful firms we provide the firm characteristics (Section 4.3) and the measures taken in the restructuring process (Section 4.4). Finally, we present a set of logit regressions explaining the differences between the two sets of firms (Section 4.5). 4.1. Comparison of the samples We compare the two samples in order to test whether both groups contain comparable firms. The results are presented in Table 1. We construct four size groups. The smallest firms have total assets below 1 million Dutch guilders, while the largest firms have assets of over NLG 10 million.15 The results in Panel A of Table 1 indicate that in terms of size the firms in the two samples are comparable. In the group of successful firms the larger firms are slightly overrepresented (65% of the sample) in comparison with the unsuccessful group (41%), and based on a difference of means test this difference is significant at the 10% level. Overall, the differences between the samples are too small to bias our results. In Panel B we distinguish five industries. In both samples, most firms are in the manufacturing industry. However, relatively more unsuccessful firms are in this industry (the difference is significant at the 14 The reasons for this low retrieval rate are that cases were too small for the work-out department, that firms may have run into trouble so fast that assistance was not an option anymore, and that names and addresses did not appear in the banks’ databases. 15 One Dutch guilder (NLG) equals approximately 0.454 Euros.

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Table 1 Samples of successful and unsuccessful restructurings Successful firms

Unsuccessful firms

p-value difference

A: Total assets (×NLG 1000) 0–1000 1000–5000 5000–10000 >10000

0 9 9 33

0% 18% 18% 65%

2 5 6 9

9% 23% 27% 41%

0.16 0.63 0.39 0.07*

B: Industry Agriculture and construction Manufacturing Trade Services and transport Other/unknown

4 16 14 14 3

8% 31% 27% 27% 6%

1 17 3 1 0

5% 77% 14% 5% 0%

0.58 <0.01*** 0.16 <0.01*** 0.08*

C: Reasons of distress Market forces Cost level Restrictive contracts Overinvestment Underinvestment Excess financing Weak management Other

30 29 3 24 7 6 23 23

59% 57% 6% 47% 14% 12% 45% 45%

13 12 1 5 4 2 11 6

59% 55% 5% 23% 18% 9% 50% 27%

0.98 0.86 0.81 0.04** 0.65 0.73 0.71 0.15

D: Final outcome of restructuring Restructured Not restructured Repayment new financier Taken over Going-concern sale Piece-meal liquidation Composition

19 2 17 13 – – –

37% 4% 33% 25% – – –

– – – – 14 7 1

– – – – 64% 32% 5%

– – – – – – –

This table reports for 51 successful and 22 unsuccessful firms, size and industry distributions, the frequencies of reasons for distress and the outcomes of the restructurings. We report frequencies, the percentages of observations in a class and the p-value of a difference of means test on the percentage of observations in classes. A going concern sale occurs when a firm sells it asset-complex (or complexes) as a whole to another party. A piece-meal liquidation occurs when the assets are sold on a piece by piece basis to different buyers. (* ) Denotes significance at the 10% level, (** ) at the 5% level, (*** ) at the 1% level.

1% level). The results in Panels A and B indicate that although some differences exist, the two groups of firms are comparable in terms of size and activities. 4.2. Reasons for distress and outcomes of the restructuring processes In Panel C of Table 1 we present the reasons for the firms’ distress.16 In both samples, 59% of the firms indicate that market forces are a main reason for the distress. The second main reason is, in both samples, the cost level. Other important factors are overinvestment 16

The reasons for distress are taken from the descriptions in the firm’s files.

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– although more often in the successful group than in the unsuccessful group – and weak management. Note that, with respect to these reasons, there is a large similarity between the two samples. Panel D of Table 1 explains how the restructuring ends. For the group of successful restructurings the following resolutions can ultimately be discerned: restructured (37%), not restructured but “successfully” turned around (4%),17 restructured and repayment of loans through new financier (33%), restructured and taken over (25%). In the first two outcomes the firm keeps its relationship with the assisting bank, while with the latter two the firm – as a customer – leaves the assisting bank. The group of unsuccessful firms ends up in bankruptcy. In bankruptcy they may sell assets in a going concern sale (64%), liquidate piece-meal (32%), or complete a composition (5%). 4.3. Firm characteristics Table 2 presents the financial characteristics of the firms in the last available book year before the restructuring. We report mean, median, minimum and maximum values. The results show that average firm size does not differ significantly between the two samples. The average size of successful firms is NLG 25.4 million, while unsuccessful firms have a mean size of 14.4 million. The difference of 11 million has a p-value of 0.12, which is not significant at the 10% level. We include the return on assets (the ratio of operating income and total assets) as a measure for firm profitability, in order to control for the viability of firms before the start of the restructuring. We find that profitability in the year preceding the distress is not significantly different between successful and unsuccessful firms. In our view, this variable also picks up business cycle effects, because changes in macro-economic and/or industry conditions would affect a firm’s viability through their profitability.18 The indebtedness, however, differs strongly between successful and unsuccessful firms. Firms that manage to stay out of bankruptcy have an 89.6% debt ratio, defined as debt relative to the total (book) asset value. For the bankrupt firms this percentage is 134.3%, which implies that the nominal debts are larger than the book value of the assets. In other words, these firms have on average a negative book value of equity. The structure of the debt also differs between the two groups of firms. Successful firms have significantly less short-term debt, i.e. 36.0% versus 51.0%. This result implies that the short-term claims threaten the success of a restructuring. The inverse is found for interestbearing debt. It should be noted that much of the short-term debts are not interest-bearing and thus a negative correlation between these two variables exists. The amount of bank debt divided by total debt differs between the two groups. Unsuccessful firms have 39.8% bank debt, while their successful peers have 55.1%. The difference is significantly different from zero at the 1% significance level. This result implies that banks provide a smaller portion of total debt to unsuccessful firms. We also have information on 17 In the group without restructuring in the set of successful firms no restructuring activities were undertaken, but the operational results improved to such an extent that assistance was not longer indicated. 18 During the restructuring the condition of the economy and the industry may change also, and because the observations of unsuccessful restructurings are slightly earlier, we cannot measure whether the conditions during the restructuring have remained constant.

Successful firms

Total assets (×NLG 1000) Return on assets Total debt/total assets Short-term debt/total debt Interest-bearing debt/total debt Bank debt/total debt Number of collaterals Collateral value/bank debt Average length in months

Unsuccessful firms

Mean

Median

Minimum

Maximum

Observations

25442

15368

1828

187100

51

Mean 14346

Median 8712

p-value difference in means

Minimum

Maximum

Observations

447

65639

22

0.12

−0.003 0.896 0.360 0.649

0.027 0.895 0.366 0.654

−0.283 0.266 0.041 0.203

0.135 1.682 0.796 0.959

50 51 51 51

0.001 1.343 0.510 0.541

−0.032 1.218 0.526 0.585

−0.398 0.550 0.093 0.202

0.588 3.142 1.000 0.906

20 22 22 21

0.90 <0.01*** <0.01*** 0.04**

0.551 2.98 2.046

0.534 3.00 1.544

0.159 1.00 0.351

0.927 5.00 7.117

51 51 51

0.398 3.00 2.338

0.408 3.00 1.870

0.076 0.00 0.976

0.696 4.00 5.836

20 22 20

<0.01*** 0.94 0.41

6.00

0.00

20

0.92

24.57

20.00

1.00

88.00

51

23.63

129.00

This table reports mean, median, minimum and maximum of firm characteristics for 51 successful and 22 unsuccessful firms. The definitions are in the first column. The right-hand column has the p-value of a difference of means test on the mean values of observations in classes. (** ) Denotes significance at the 5% level, (*** ) at the 1% level.

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Table 2 Firm characteristics

441

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the collateral that banks have obtained. For purposes of this study, we distinguish five types of collateral. Firms may provide banks a mortgage on real estate, they may pledge tangible fixed and current assets, pledge receivables, acquire equipment via a lease contract, and the firm owners may personally guarantee debts.19 In both groups, the number of collaterals that firms have pledged out of the set of five is similar, about three. Finally, we compare the nominal value of the collateral with the nominal bank debt. If the collateral, when repossessed and sold, should yield the nominal value, a ratio of collateral value and bank debt of 1 is sufficient to recover all of the bank debt. In our successful restructuring sample the collateral is 2.046 times the bank debt, while in the unsuccessful sample the ratio is 2.338. The finding that bank debt is on average about half of the total assets and the collateral is twice the bank debt implies that on average banks have the entire total assets as collateral. The average length of the restructuring period is approximately 24 months in both samples. In comparison, Franks and Susmann (2005) find for small UK firms an average of 9.2 months for firms that restructure successfully and 5.2 months for firms that end in bankruptcy proceedings. These results show that the Dutch restructuring processes take much longer. Remarkably, our findings are more in line with the period that US firms stay in Chapter 11 procedures (see Franks & Torous, 1994; Gilson et al., 1990). Our descriptive statistics lead to two observations. First, banks seem to be able to discriminate between successful and unsuccessful firms before the restructuring starts. Banks have relatively less debt in unsuccessful firms, in comparison with other providers of debt. Moreover, banks have obtained more collateral in firms that turn out to be unsuccessful. This gives some credence to the observation that banks are able to anticipate bankruptcy, because banks predict bankruptcy better than other debtholders. The second observation is that bank debt seems to be “over-collateralized”. Of course, the book value of collateralized assets is likely to overstate the value in case of distress and bankruptcy. Research on the firm recovery rates in other countries shows that bankruptcies of small firms on average yield 35–45% of the total nominal debt value (Franks, Nyborg, & Torous, 1996; Ravid & Sundgren, 1998; Sundgren, 1998; Thorburn, 1999). This implies that a large fraction of the book value of assets is lost in bankruptcy. The available evidence on recovery rates in bankruptcy proceedings with respect to secured credit shows that these are much higher than firm recovery rates, but on average do not reach the 100% ratio. Franks and Torous (1994) report an average percentage of 80%, Thorburn (1999) finds 69% for secured debt and Franks and Susmann (2005) 74% to 77%.20 Over-collateralization seems therefore to be necessary in order to secure debt in any meaningful way. 4.4. Restructuring measures Table 3 describes which measures are taken in the distressed firms. We distinguish seven categories of measures, dependent on which party initiates the measure and the characteristics of the measures: financial measures by the shareholders, banks, and nonbank creditors (Panel A–C), operational measures by the firm (Panel D), governance by 19

A floating charge security does exist in the UK, but not in the Netherlands. Tashijan, Lease, and McConnell (1996) find recovery rates of nearly 100% for secured creditors in prepackaged bankruptcies in Chapter 11 proceedings. 20

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Table 3 Restructuring measures Successful firms

Unsuccessful firms

p-value difference

A: Role of shareholders in financing Additional equity Junior debt Debt without collateral Total

3.9% 15.7% 2.0% 19.6%

13.6% 18.2% 4.5% 22.7%

0.14 0.80 0.54 0.77

B: Role of banks Extension repayment principal Extension interest payments Reduction interest rate Debt write down Ease credit conditions Hasten repayment principal Additional collateral

33.3% 2.0% 0% 0% 3.9% 33.3% 43.1%

22.7% 0% 0% 0% 0% 18.2% 4.5%

0.37 0.52 0.35 0.20 <0.01***

Additional debt under conditions: Fresh equity or junior debt Additional collateral Additional restrictive covenants Extra information Divestment Reinforcement of management Total

58.8% 13.7% 45.1% 76.5% 56.9% 37.3% 31.4% 90.2%

59.1% 22.7% 36.4% 31.8% 27.3% 4.5% 9.1% 59.1%

0.98 0.35 0.49 <0.01*** 0.02** <0.01*** 0.04** <0.01***

C: Role of other creditors in financing Extension principal/interest payments Additional funds Additional collateral Hasten repayment of principal Additional restrictive conditions Additional extension of trade credit Total

9.8% 21.6% 11.8% 7.8% 2.0% 17.6% 39.2%

13.6% 27.3% 9.1% 0% 0% 18.2% 50.0%

0.64 0.60 0.74 0.18 0.52 0.96 0.40

D: Operational measures Strategy Purchase Production Sales Financial control Sell assets Acquisitions Adjustment organization Adjust legal structure Rescue via take over Reduction work force Total

25.5% 2.0% 29.4% 7.8% 17.6% 56.9% 15.7% 7.8% 13.7% 29.4% 25.5% 86.3%

18.2% 4.5% 27.3% 9.1% 22.7% 9.1% 4.5% 9.1% 18.2% 27.3% 27.3% 50.0%

0.51 0.54 0.86 0.86 0.62 <0.01*** 0.19 0.86 0.63 0.86 0.88 <0.01***

E: Role of shareholders in governance Forced resignation of management Intervention via interim management Rescue attempt via take over Total

15.7% 9.8% 13.7% 51.0%

4.5% 0% 4.5% 27.3%

0.19 0.13 0.26 0.06*

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Table 3 (Continued ) Successful firms

Unsuccessful firms

p-value difference

F: Role of supervisory board in governance Forced resignation of management Intervention via interim management Rescue attempt via take over Total

7.8% 9.8% 2.0% 17.6%

9.1% 4.5% 0% 18.2%

0.86 0.46 0.52 0.96

G: Role of management in governance Voluntary resignation of management Total

15.7% 15.7%

18.2% 18.2%

0.80 0.80

H: Summary Average number of measures Average fraction of measures

8.84 0.201

6.09 0.138

0.04** 0.04**

This table reports restructuring measures taken by 51 successful and 22 unsuccessful firms. The definitions are in the first column. The second and third column reports the percentages of firms that choose a measure. The final column has the p-value of a difference of means test on the percentage of observations with a restructuring measure. (* ) Denotes significance at the 10% level, (** ) at the 5% level, (*** ) at the 1% level.

shareholders and the board (Panel E and F), and management leaving the firm voluntarily (Panel G). With the information available it was not always possible to pinpoint the exact measure taken, although the documents revealed that a measure in a specific category was chosen. Therefore, the “Total” score also comprises these observations, while the detailed measures are only included if specific evidence was found. We perform a comparison of means test on the difference between the percentages of firms with a measure between the two samples and we report the p-values, which represent the probability that the difference is not significantly different from zero. 4.4.1. Financial measures Panel A shows that 3.9% of the successful firms received additional equity from the shareholders, while in the unsuccessful firms the corresponding percentage is 13.6%. The p-values are the result of a difference test, which estimates whether the probability that a measure is taken is not significantly different between the two samples. The p-value is 14%, which implies that the difference is not significant at the 10% level or less. As the total score in the panel shows, shareholders do contribute new funds (either equity or debt) in approximately 20% of the cases and this finding is more or less the same in both groups. This lack of funding activities by shareholders is in conjecture with debt overhang problems and/or wealth constraints. Clearly, the role of shareholders does not make the difference between success and failure. Panel B shows the changes in firms’ financing provided by the bank. The total score beneath the panel indicates that in 90% of the successful firms, banks assisted by changing conditions. This is statistically significantly more at the 1% level than in the other group (59%). In other words, if banks induce more measures, the probability of survival increases. It is remarkable that extension of interest payments, reduction in interest rate, and an easing of credit conditions never or nearly never occur in both groups. We also find that debt write-downs never occur, which implies that banks do not help firms via a scale-down of

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445

their own positions. The extension of principal repayments occurs relatively frequently in both groups, although more so in the successful group (33% versus 23%). On the other side, banks also hasten repayments (33% versus 18%), but demand additional collateral only in the successful group (43% versus 5%). This latter difference is statistically significant at 1%. This is a curious finding because in both groups banks hold similar levels of collateral. The finding may be explained by the fact that the demand of additional collateral, when bankruptcy is imminent, may be considered as fraudulent behavior by the trustee. This presupposes though that banks are capable of an ex ante screening of the successful firms from the unsuccessful firms. Additional debt under (new) conditions is forthcoming in more than half of the cases in both groups (59%). Although additional debt is provided to the same fractions in each group, the conditions differ. We find four conditions that are significantly more often negotiated with successful firms: additional restrictive covenants (77% versus 32%; difference is significant on 1% level), additional information (57% versus 27%; difference is significant on 5% level), divestments of assets (37% versus 5%; difference is significant on 1% level), reinforcement of management (31% versus 9%; difference is significant on 5% level). The two other conditions are that new equity or junior debt is forthcoming from shareholders or other groups (14% versus 23%) and additional collateral (45% versus 36%). Thus, the successful group differs significantly from the unsuccessful group on four out of six conditions. The overall result for banks indicate that 90% of the successful firms are aided by banks, while only 59% of the unsuccessful firms receive assistance. The role of banks in resolving financial distress is thus more extensive in successful firms than it is in unsuccessful firms. Of course, the causation cannot be defined based upon this table. This difference in the role of banks may be due to the attitude of the firms, i.e. whether management is co-operative or not. Panel C shows the role of non-bank creditors in the restructuring of the firm. Among the various measures no significant differences occur between the two groups. With respect to the occurrence of the measures two stand out: additional funds (22% versus 27%) and extension of trade credit (18% both). Presumably, other creditors are sometimes prepared to keep a customer afloat, either by way of extension of credit or even additional funds. The overview of financial measures yields interesting conclusions with respect to the involvement of banks. We conclude that banks are not “lazy” in general, but selective in their efforts. Banks do not hold out on a restructuring effort, but actively participate by providing new funds, by easing certain conditions (especially extension of principal, a form of “softening”), as well as tightening others (hasten repayments, additional collateral). The tightening may be induced by the laziness incentive, but may also be attributable to the information the bank possesses, e.g. on management quality. We cannot separate these two conflicting explanations. In successful restructurings banks are more involved than other debtholders, while nearly the inverse holds for unsuccessful firms. This result has two potential reasons. On the one hand, banks may focus their effort on viable firms and provide help to successful firms, i.e. they discriminate effectively. On the other hand, the help of banks may be the key to success and firms are rescued because banks help them out. Of course, if firms are successful, partly due to the involvement of banks, the other creditors also benefit. Inasmuch their efforts are not needed, or only auxiliary to the success they benefit from the efforts of banks.

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4.4.2. Operational measures Panel D shows the operational measures taken in both groups of firms. They differ significantly (1% level) with respect to their total score. In the group of successful firms more firms take operational measures than in the unsuccessful group (86% versus 50%). Especially striking is the difference in the measure sell assets: 57% versus 9% (significant on 1% level), which seems to drive to overall difference. The other measures have more or less similar scores in both groups. Furthermore, it seems that some measures are more popular than others: Changing strategy, reorganizing production, stepping up financial controls, rescue via take over and reducing the work force. These measures are taken in approximately a quarter of the cases in both groups, while the other measures are below 15%. Although successful firms take more operational measures than unsuccessful firms, the scores seem fairly low, given the fact that the firms are all (severely) distressed. 4.4.3. Governance measures Data on the role of shareholders is provided in Panel E of Table 3. In the group of successful firms shareholders act more often, than in the unsuccessful group. And this difference is statistically significant at 10% level (51% versus 27%). The data for unsuccessful firms was in many instances not specific enough to be attributed to individual measures, which explains why such a result is not present for individual measures. The role of the board of supervisors in Panel F is even less pronounced. No differences between the groups occur and the frequencies of activities are fairly low. Finally, Panel G reports that management resigns voluntarily in 16% and 18% of the firms, respectively. The difference between the two groups is insignificant and the incidence is also fairly low. Given the characteristics of small firms, it is not so much of a surprise to find shareholders to be more active than the board. Small firms either do not have boards to monitor and control management, or boards play a different role, e.g. providing specific knowledge, giving access to a network of relations and maybe even image-building. Panel H reports the average number of measures taken and the fraction. In measures taken (absolute and fraction) the successful group differs significantly on 5% level from the unsuccessful group (9 versus 6 measures, or 20% versus 14% fraction). 4.5. Predicting the success of restructuring In the previous analyses we have documented several differences between successful and unsuccessful firms in uni-variate comparisons. An interesting issue is whether success can be predicted. We perform logit regressions, which explain the probability of success, and thus the differences between successful and unsuccessful firms in a multi-variate setting. A major advantage of the multi-variate framework is that we can control for factors as size and indebtedness. The results are reported in Table 4 and Panel A contains firm characteristics, while Panel B adds restructuring characteristics. Our regression models contain two types of explanatory variables, i.e. control variables and theory-based variables. Our first control variable is size (log of total assets), which controls for the effect that larger firms have a higher chance of restructuring successfully. The second control variable is return on assets. This variable controls for profitability, i.e. firms with a higher profitability before restructuring have a higher incidence of surviving.

Table 4 Logit regression predicting success

(1)

(2)

(3)

(4)

Intercept Log (total assets) Return on assets Dummy manufacturing Dummy trade Dummy service and transport Total debt/total assets Short-term debt/total debt Interest-bearing debt/total debt Bank debt/total debt Number of collaterals Collateral value/bank debt

0.257 (0.08) 0.633* (1.83) −3.459 (−1.39) −2.461* (−1.73) −0.045 (−0.03) 1.014 (0.56) −3.698*** (−3.01)

−3.471 (−1.15) 0.801** (2.43) −2.460 (−0.96) −2.462* (−1.71) −0.655 (−0.42) −0.074 (−0.04)

−5.682* (−1.76) 0.752** (2.42) −1.822 (−0.74) −2.396* (−1.85) −0.448 (−0.31) 0.225 (0.14)

−5.896 (−1.56) 0.730** (2.18) −2.676 (−0.99) −2.152 (−1.58) −0.511 (−0.34) 0.250 (0.15)

McFadden R2 Observations

0.409 70

−3.539* (−1.86) 1.726 (0.90) 3.366* (1.77) 0.084 (0.35) −0.153 (−0.41) 0.307 70

0.255 69

0.269 68

B: Restructuring characteristics

Intercept Log (total assets) Return on assets Dummy manufacturing Dummy trade Dummy service and transport Total debt/total assets Fraction of measures Shareholders/financing Bank

(5)

(6)

(7)

(8)

0.059 (0.02) 0.612* (1.71) −3.788 (−1.59) −2.444* (−1.69) −0.116 (−0.07) 1.152 (0.61) −4.191*** (−3.01) 4.849 (1.41)

−3.021 (−0.42) 1.922 (1.64) −3.796 (−0.66) −9.080** (−2.04) −6.100 (−1.33) −2.185 (−0.70) −9.668** (−1.99)

4.360 (0.82) 0.604 (1.28) −5.130 (−1.33) −2.495 (−1.25) 1.030 (0.42) −0.369 (−0.14) −8.854*** (−2.87)

0.131 (0.03) 0.676 (1.49) −3.924 (−1.36) −4.263** (−2.15) −0.800 (−0.38) 0.049 (0.02) −4.3690** (−2.64)

−4.094* (−1.72) 2.309* (1.92)

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A: Firm characteristics

447

448

B: Restructuring characteristics (5)

McFadden R2 Observations

(6)

(7)

(8)

−5.319* (−1.80) −0.805 (−1.02) 5.055 (1.49) 1.247 (0.77) −8.985 (−1.58)

Other creditors Operational Shareholders/governance Board/governance Management/governance Bank: divestment Operational: sell assets (-Bank: divestment) Bank: management Bank: additional collateral Bank: additional terms

7.953** (2.49) 1.779 (1.34) 1.771 (1.15) 3.292* (1.80) 2.257** (2.19) 0.436 70

0.744 70

0.625 70

0.596 70

This table reports the results of logit regression models that explain success in restructuring for a sample of 51 successful and 22 unsuccessful firms. We report the logit regression coefficients and z-statistics in parentheses. The McFadden R2 indicates the explanatory power of the model. The variables are in the first column and these variables are defined in Tables 2 and 3. (* ) Denotes significance at the 10% level, (** ) at the 5% level, (*** ) at the 1% level.

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Table 4 (Continued )

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Finally, we include three dummy variables to control for industry effects. The theorybased variables in our regression models are the debt structure, number of collaterals, ratio collateral value and bank debt, fraction of measures, and several specific measures. Debt structure is proxied by several variables, measuring the relative size of debt, maturity of the debt and lender type. We expect that leverage has a negative effect on the probability of success, due to the interest burden associated with this debt. We include short-term debt over total debt to measure debt maturity. We expect that the liquidity problems associated with short-term debt induce a higher probability of failure. The variable interest-bearing debt over total debt is a specific measure of the interest burden of leverage. We expect a negative relation with the probability of survival. We expect bank debt over total debt to have a positive effect on the probability of success for two reasons. First, the information advantage of banks may allow them to correctly discriminate between viable and non-viable firms and to provide (relatively) more debt to the successful firms. It also reduces the amount of information asymmetry between owner/directors and creditors in general and this lessens the holdout problem. Second, a higher bank debt ratio provides for an incentive for banks to actively participate in the restructuring of the firm and thus prevent a destruction of going concern value also due to holdout problems. The bank laziness incentive is proxied by the number of collaterals and the value of collateral over bank debt. The better secured the bank is and/or the higher the ratio collateral value and bank debt, the less the bank will be inclined to help the firm restructure. We expect a negative effect on the success of restructuring. Our data allows for a partial test of the theoretical arguments developed in Section 2.3. This is due to two limitations. First, some variables are simply non-existent in our data (asset intangibility). Second, some firm characteristics do not exhibit sufficient variation to be included in regression tests (the complexity of the debt structure is in all our firms very similar). These two limitations are the consequence of the type of firms in our sample. The remainder of our explanatory variables concern restructuring measures. The Dutch institutional setting with harsh bankruptcy rules in combination with our sample characteristics – firms have one strong creditor and dispersed other creditors – induce banks to take measures that have a positive effect on the probability of success (see Sections 2.3 and 2.4). Regression (1) contains the control variables and leverage. The results show that size is significant at the 10% level, with a z-value of 1.83. The coefficient for profitability is insignificant. The dummy manufacturing is significantly negative at the 10% level, which indicates that manufacturers are less likely to be successful in restructuring. Finally, regression (1) includes the relative amount of debt. As expected, the coefficient is negative and significant at the 1% level. Higher debts before restructuring reduce the probability of survival. McFadden’s R2 is the standard measure for the explanatory power of a logit regression and a value of 0.409 is acceptable. In order to test whether the effect of debt is driven by short-term debt, by interest-bearing debt or by bank debt, we add these characteristics and remove overall debt in regressions (2), (3) and (4). The significantly negative result for short-term debt in regression (2) shows that debt maturity has a positive effect on survival chances. On the other hand, as described in regression (3), interest-bearing debt does not affect the success of the restructuring. In regression (4) we investigate the role of banks and include bank debt and collateral. As expected, bank debt has a significant positive effect, which indicates that more bank

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debt in the total debt structure increases the probability of success. Our data does not make it possible to test whether this is due to the information advantage of banks, the holdout problem or both. This result is in line with the uni-variate results. In contrast with our hypothesis on lazy banks, the number and value of collateral over bank debt do not significantly affect the probability of survival, although the variable has the correct sign (negative). The laziness effect is dominated by the bank debt effect. Based on our data, Dutch banks are not lazy in helping firms restructure, i.e. they do not hold out on firms. Bank debt has a correlation of −0.39 with total debt. In unreported additional regressions we include both the debt ratio and the relative amount of bank debt. We find that bank debt turns insignificant, which indicates that the total debt effect dominates the bank debt effect. The importance of total debt is also illustrated by the high R2 in regression (1). In Panel A, we include the characteristics describing the firm before restructuring, while in Panel B we add the restructuring activities. First, in regression (5) we include the fraction of measures. The resulting coefficient is positive, suggesting that more activities are better. However, the coefficient is insignificant. Unreported additional tests show that the number of months also has no significant effect (the coefficient is −0.009 with a z-statistic of −0.63). Next, in regression (6) we include the total scores for each of the seven categories in Table 3. The results partly confirm our earlier results. Banks have a positive impact, significant at the 10% level. Shareholders and other creditors exhibit a negative coefficient, significant at the 10% level. All other measures yield insignificant coefficients. This contrasts with some of the uni-variate results. Table 3 shows that, in contrast with our multi-variate result, the score on other creditors does not differ significantly between the two groups. For operational activities, the uni-variate results led to a highly significant difference. But this result is lost in regression (6). To find out why this happens we specify two additional regressions. Regressions (7) and (8) include several individual specific measures in order to learn more about the influence of banks. In the discussion on the role of banks, significant univariate differences were found on the conditions that were attached to the provision of additional debt. In regression (7) we include a dummy for banks that induce firms to divest. We also include divestment in general, minus bank-induced divestments. Thus, the latter variable measures all divestments that are not “forced” by banks. The result clearly shows that divestments have their positive effect only in the case that banks attach divestments as a condition for the provision of additional debt. The three other individual measures as conditioned upon additional debt also improve the chances of survival. Regression (7) yields the result that banks that induce reinforcement of management increase the probability of success, but this effect is insignificant. Due to high correlations among variables, the two other measures are included in regression (8). Both the additional collateral and the additional covenants, in combination with extra debt, affect survival positively.

5. Discussion Our results suggest a complex picture of bank-firm relationships in situations of financial distress. In this discussion we first summarize our main findings. In addition we interpret these findings in relation to theory and the institutional setting.

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Our first finding is that the ratio of debt to assets before restructuring is lower in successful firms than in unsuccessful firms (see Table 2, total debt over total assets). When we split up the debt we find that successful firms have less short-term debt and more interest-bearing and bank debt (see the corresponding entries in Table 2). Based on the latter result, it seems that banks owe less debt when failure is more likely. This implies that banks are well-informed and choose to restrict their lending to indebted unsuccessful firms. Our second finding concerns the measures taken. In both of the groups, many firms take operational measures and many firms effectuate measures that banks advise (or induce), together with measures related to bank debt (see Table 3, panels B and D). Our analyses show that the measures in this latter category make the difference between success and failure. Two things stand out. First, successful firms pledge additional collateral, at least more so than unsuccessful firms (see Table 3, panel B, Additional collateral). This may reduce banks’ downside risk and consequently let them take a more lenient attitude towards these firms.21 Second, from an operational perspective, the success of restructuring efforts depends on measures that are induced by banks (see Table 4, panel B, regression models 7 and 8). This finding sheds an interesting light on the role of banks. Banks have a powerful say in the restructuring activities of firms. This power arises to the circumstance that they are knowledgeable concerning the state of affairs and are in a position to offer some debt relief and additional funds under conditions. Nevertheless, it is the firm’s management that has to respond to this approach. Especially the fact that unsuccessful firms divest less, do less to reinforce management and do not accept additional restrictive covenants point in the direction that these firms have not been able to secure, or were not willing to accept the support of the bank. Even in financial distress situations “it takes two to tango”. Overall our conclusion is that the role of banks is crucial in discriminating between success and failure. On the one hand, banks screen firms and as a result they are less involved as creditors in the highly levered unsuccessful firms. On the other hand, banks help firms they are more involved in. There are two likely, and related, reasons for their involvement. First, banks have larger portions of debt in these firms. Second, these firms are less indebted and thus the measures taken are more likely to yield the desired results. The major finding of this paper is that banks are not lazy in offering support to failing firms. Banks will not be overly generous, but they help by providing additional financing coupled with a tightening of the conditions. It can be considered as an intensification of the monitoring effort (see Table 3 panel B). The other side of the coin is that this support is only forthcoming when firms act on their predicament and in a manner as advised by their bank. In a creditor-oriented system, private renegotiations are facilitated by a constellation with one strong creditor and dispersed small creditors. In order for such renegotiation to be successful it will be extremely beneficial to have an active bank that may provide additional capital. As our data shows the private renegotiation phase can be rather lengthy (see Table 2, average length). But if this restructuring process fails, firms are most likely not sufficiently viable. Firms have not been able to capitalize on the support of the bank in order to reorganize to be at least marginally profitable. It will become very hard for firms to 21

We thank an anonymous referee for pointing this out.

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start the process all over again. The implication is that firms that end up in bankruptcy will predominantly be sold, either (partly) as going concern or in piece-meal liquidation. With little value left and most or all of the assets in security with banks, little remains for other creditors. In successful renegotiation cases it is the other way around. Although the bank possesses the liquidation rights to the most important assets, it is not only the bank but also the group of dispersed non-secured creditors that benefit from a successful restructuring. Therefore, the dispersed creditors win when private renegotiation succeeds and lose when it fails. In other bankruptcy systems, where soft bankruptcy rules prevail, an important part of the private activities are driven into bankruptcy. The main motivation for this may be that banks do not want to give in twice. Banks will become lazier, i.e. will not be as active as compared to a situation in which harsh bankruptcy rules are present. Furthermore, they will ask more concessions from other creditors, before they give in on their secured position. It means though that firms will enter a bankruptcy procedure sooner, generate higher payouts and will be monitored by an outside trustee. But it does not automatically mean that such a system is to be considered as more efficient as a harsh system. Most importantly, the benefits of private renegotiation are lost, i.e. lower costs and higher pay-outs for all creditors in successful firms.

6. Conclusion This paper studies the restructuring process of small Dutch firms in financial distress. We obtained a unique dataset with firms that are assisted in their restructuring by banks, which includes all restructuring measures taken by the firm, the bank and other stakeholders. Our dataset consists of firms that successfully restructured and firms that did not succeed in reorganizing. We run empirical tests that aim to predict success and failure in restructuring. The main result is that banks are willing to assist firms in restructuring. We also find that this assistance is of crucial importance to the success of the restructuring. However, some firms do not benefit from this assistance. We conclude that firms do not fail in the case that they are prepared to undertake radical operational changes and bank assistance is forthcoming. Our results have interesting implications about bankruptcy systems. The Dutch firms in our sample reorganize under harsh bankruptcy rules. The analysis shows that private reorganization occurs and that it crucially depends on bank involvement. Furthermore, trade creditors seem to fill in a role that is similar to widespread debtholders. With harsh bankruptcy rules these creditors benefit from the private involvement of banks. This is in contrast to soft systems where these debtholders have to give in first before senior/secured creditors give in. The efficiency of harsh systems thus depends on facilitating private reorganization. If such private reorganization in harsh systems fails then small firms do not have much of an ex post alternative to avoid bankruptcy.

Acknowledgements We thank Anton Duizendstraal, N.E. Dennis Faber, S. (Bas) C.J.J. Kortmann and two anonymous referees for helpful comments. The empirical part of this research has been

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conducted when Couwenberg was a researcher to the Business and Law Research Centre of the Radboud University Nijmegen.

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