Download Financial distress, reorganization and corporate performance

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Accounting and Finance 40 (2000) 233± 260
Financial distress, reorganization and corporate
performance
James Routledge a, David Gadenne b
b
a
Faculty of Business, University of the Sunshine Coast, Queensland 4556, Australia
Faculty of Business and Law, Central Queensland University, Queensland 4702, Australia
Abstract
Prospects for financially distressed companies in Australia have improved
since the introduction of voluntary administration (VA) as an alternative to
liquidation. This paper investigates whether companies that reorganise can be
distinguished from those that liquidate under VA. In addition, performance of
reorganised companies is examined to determine variables that distinguish
`successful' from `unsuccessful' reorganisations. Significant variables in the
logistic regression models developed differ between the analyses. The results of
the analyses have implications for policy makers regarding efficiency of the VA
procedure, as it appears the reorganisation decision is biased toward permitting
inefficient firms to reorganise.
Key words: Voluntary Administration; Reorganisation theory; Liquidation;
Corporate performance
JEL classification: M41; G33
1. Introduction
Before the introduction of voluntary administration (VA), Australia's
insolvency law offered little chance for distressed companies to reorganise
their affairs. The new law provides distressed companies with a relatively
simple, inexpensive and flexible procedure for addressing their problems
(Keay, 1996). Accordingly, many companies choose VA to deal with financial
distress. Over the first four years of operation (July1993 to June 1997) 5760
companies entered VA; during the 1996 ± 1997 financial year, 1764 companies
appointed an administrator (Australian Securities and Investments CommisThe authors would like to thank Margaret Abernethy (Editor), delegates from
the 1999 AAANZ conference, accounting staff at QUT, Donald Stokes
(Associate Editor) and two anonymous referees for their helpful comments and
constructive advice.
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sion (ASIC) 1998). Growth in use of VA presents significant opportunities and
challenges for accounting professionals, and it is important that accountants
understand the operation of the legislation and its suitability for particular
clients. For example, timely recommendation to initiate VA by professional
accountants may provide the company and its officers with important
advantages as the company attempts to formulate a plan for its survival
(Crutchfield, 1994). Moreover, distressed firms that reorganise will likely
require continued professional assistance. Therefore, decision making associated with the operation of VA has become increasingly important.
There is continuing interest in the development and refining of financial
distress prediction models. Introduction of reorganisation legislation in
Australia has provided an opportunity to develop and refine understanding
of the reorganisation decision process for distressed companies. Accordingly,
this paper adds to the scarce research in this area by developing a model of the
reorganisation decision under VA. The model examines the explanatory power
of historical accounting information in distinguishing Australian companies
that reorganise from those that liquidate. A further contribution of this paper
is its reference to reorganisation theory in model development. Prior studies in
other jurisdictions have demonstrated the usefulness of coalition behaviour
theory as a means of determining outcomes of financial distress decisions. The
coalition behaviour theory is drawn upon in selection of predictor variables for
the models developed, in addition to providing a reference to assist with
understanding the reorganisation decision process.
With the widespread use of VA, creditors are more often faced with a
decision as to whether they should support a company's reorganisation. In
making their decision regarding the company's prospects, creditors will
probably rely on the recommendation of the insolvency accountant appointed
as administrator. The insolvency accountant is required to assess the position
of the company and recommend a suitable outcome within a short time frame. 1
Decisions by creditors and administrators may often be made without
substantial or reliable information as to the company's future prospects. The
quality of these decisions will affect the efficiency of the legislation's operation.
Insolvency law provides an important filtering mechanism by providing the
opportunity for inefficient firms to be liquidated. Accordingly, where
insolvency legislation provides firms with the opportunity for reorganisation
as an alternative to liquidation it should be designed to ensure that only
efficient firms reorganise. This allows valuable resources to move to their
highest value use (White, 1994). In order to inform future decisions made in
VA, a second model developed in this paper examines the explanatory power of
historical accounting information in determining whether a company will
successfully reorganise.
1
See section 438A of The Corporations Law (Cth).
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2. Part 5.3A (Voluntary Administration)Ð an overview
The voluntary administration procedure was introduced as part of
Australia's corporate insolvency regime in June 1993. The new legislation
resulted from the Australian Law Reform Commission's General Insolvency
Inquiry (1988) (Report No 45, the `Harmer Report'). The Commission
recommended change to Australian insolvency law because of concern that
there was:
`little emphasis upon or encouragement of a constructive approach to corporate
insolvency by, for example, focusing on the possibility of saving a business (as distinct
from the company itself) and preserving employment prospects'. (Harmer Report,
par. 53).
The Explanatory Memorandum to the Corporate Law Reform Bill (1992,
par. 448) observed that liquidation was frequently embraced by companies which could have continued trading and which may well have
ultimately survived. Prior to the implementation of Part 5.3A, an insolvent
company had few viable options other than proceeding with winding up.
The company could attempt to institute a scheme of arrangement under
Section 411 of the Corporations Law as an alternative to winding up.
However, this provision was rarely used due to the time and cost involved in
obtaining the necessary court approvals and meeting onerous requirements
for scheme ratification (Crutchfield, 1994). Alternatively, the company
could appoint an official manager if the company was certain to repay
all creditors in full, which was an unlikely prospect for most distressed
companies.
The primary purpose of Part 5.3A is to provide a flexible and relatively
inexpensive procedure in which a company can attempt to formulate an
arrangement with its creditors. The objectives of administration are to save
the company's business or, if this is not possible, to improve the return to
creditors that would have resulted from an immediate winding up of the
company. 2 Central to the operation of the legislation is protection of the
company's property during the administration under the moratorium
provisions. 3 The moratorium prevents action by creditors against the
company or its property during the period of the administration. During
the moratorium period, the appointed administrator is to investigate the
company's affairs and formulate a proposal for a compromise arrangement
with creditors, which may include a reorganisation plan, or alternatively
recommend liquidation.
2
The objectives are outlined in s 435A of The Corporations Law (Cth).
3
Contained in Division 6 of Part 5.3A of The Corporations Law (Cth).
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The decision as to whether a reorganisation plan will be accepted is made by
a meeting of creditors. If creditors vote to approve reorganisation, the
company will enter into a deed of company arrangement. The deed of
arrangement is binding for the company and supporting creditors until its
terms are completed, or until the company fails to comply with its provisions
and winding up results.
3. Prior research and theoretical propositions
In model development, this paper draws on prior literature relating to the
coalition behaviour theory of the choice made by stakeholders regarding the
future of a firm in financial distress. In prior financial distress studies model
development is characterised by a lack of theoretical underpinning (Zavgren,
1983). This approach has been criticised as, in the absence of theory, the results
do not permit generalisation, and a sustained correlation between variables and
the event predicted cannot be expected (Ball and Foster, 1982; Blum, 1974). In
this study, we attempt to overcome this problem by drawing on coalition
behaviour theory and findings from other prior reorganisation studies in model
development.
3.1. Theoretical model Ðcoalition behaviour
Bulow and Shoven (1978) first applied coalition behaviour theory to
determine whether a firm would continue or liquidate under the United States
bankruptcy regime. They considered in their model three claimants to the cash
flows and assets of the firm: bondholders, bank lenders and equity. The
coalition that they described as driving decision making comprised the bank
(lender) and equity. The key assumptions of the theory's operation in their
analysis were (1) that the bank and equity holders have the bankruptcy
decision power, and (2) that these stakeholders act in their own joint interests
without considering the outcome for other claimants. Using coalition
behaviour theory, Bulow and Shoven were able to establish the precise
conditions under which bankruptcy would occur.
The work of Bulow and Shoven (1978) demonstrated how financial distress
decisions could be parsimoniously modelled by examining coalition behaviour.
The simplicity of the theory allows its application to be extended to other
financial distress decisions. Application of the model requires consideration of
(1) parties that could form coalitions, (2) identifying the coalitions that might
form to drive decision making, and (3) considering the decision that the
coalitions would arrive at Ð based on the theory's key assumption of selfinterested behaviour.
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White (1980, 1984, 1989) later applied coalition theory to investigate
decision making under the United States Chapter 11 reorganisation
procedure. 4 The coalition behaviour approach, and particularly White's
discussion of its application to firm reorganisation decisions, has since been
used in development of reorganisation prediction models. 5
The model presented by White (1984, 1989) of the United States Chapter
11 bankruptcy reorganisation procedure assumed that a subset of interested
parties, a coalition, controls the behaviour of the distressed firm. The
coalition assumption operates when the firm is failing; that is, when the firm
has insufficient assets to meet obligations due in the current period, and, to
avoid bankruptcy, the firm must obtain new finance. White showed that the
decision to reorganise or liquidate will be made by coalitions of equity
holders (with management as assumed agent), (secured) lenders and
unsecured creditors. She further suggested that the coalition would most
often be comprised of equity holders and some particular group of
creditors.
Importantly, White (1984, 1989) demonstrated that the choice between
reorganisation and liquidation is directly related to the firm's financial
position, as this impacts on the decision that will be arrived at by the
`coalitions' that arise. In summary, the following financial characteristics were
postulated by White (1984, 1989) as having an effect on the reorganisation
decision:
*
*
*
Equity commitment: owners' equity and managers' jobs will likely be
eliminated in liquidation thereby providing incentive to form coalitions to
avoid liquidation. Equity can also give up its claim to company assets to
secure further borrowing.
Leverage position: distressed firms that delay action will often have secured
liabilities that will equal the total value of assets, leaving few free assets to
secure borrowings or to pay unsecured creditors.
Pay-off in reorganisation compared to liquidation: unsecured creditors will
generally receive a zero or low return in liquidation, therefore, their
4
For extensive discussion of the coalition behaviour model and its application to US
bankruptcy and reorganisation law see White's (1984) chapter in The Handbook of
Modern Finance (revised 1989 and 1991).
5
John (1993), in summarising research in the area of financial distress, acknowledges
the important work of Bulow and Shoven (1978) and White (1980, 1984, 1989) in
modelling investment decisions by distressed firms. For discussion and recent reference
to the model and its application see Ang and Chua (1980), Casey et al. (1986), Gertner
and Scharfstein (1991), Hotchkiss (1995), Fisher and Martel (1995) and Campbell
(1996).
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*
*
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opportunity cost is low if the firm reorganises. Immediate pay-off to
unsecured creditors also provides debt forgiveness.
Future profitability: reorganisation will be worthwhile if the going concern
value of the company exceeds the liquidation value of its assets plus costs of
reorganisation.
The amount of secured debt in the firm's capital structure: secured creditors
are likely to oppose reorganisation if their security position is compromised,
and are in the best position to block reorganisation.
Concepts discussed by White in applying the theory to model the United
States Chapter 11 reorganisation decision can be readily adapted to the context
of reorganisation decisions under the Australian voluntary administration
regime. While the negotiation framework is different under the United States
legislation, similar parties are involved in deciding whether a company that has
entered VA should reorganise or liquidate. Importantly, consideration of the
model's application provides guidance as to the financial dimensions that
distinguish companies that reorganise from those that liquidate.
A summary of prior research relevant to firm reorganisation in various
jurisdictions is presented in Table 1. This table summarises the financial
dimensions that have been found useful in prior studies to distinguish firms
that reorganise from those that liquidate. Significant financial dimensions
(with the exception of firm size) are generally consistent with those that have
been highlighted as important under the coalition behaviour model. The
following section further discusses the coalition behaviour in the context of VA
decision-making, and refers to the findings in prior research to develop a
decision model for VA.
3.2. Development of propositions
Review of literature in the previous sections has 1) demonstrated the
usefulness of the coalition behaviour model as a means of analysing how
various parties will behave with respect to the reorganisation decision; and, 2)
identified variables that have been found in prior research to be useful
predictors of outcomes for distressed companies. In this section, we refer to
prior studies collectively, along with consideration of likely coalition behaviour
in VA, to develop propositions regarding the reorganisation decision.
Securing continued or additional funding for operations would be important
for a distressed company attempting to avoid liquidation. However, obtaining
the necessary funding may be difficult when the company has a high level of
debt and little or no unsecured assets available to offer as security. Casey et al.,
(1986) found the level of free assets to be a significant discriminator between
firms that liquidate and those that reorganise under the United States Chapter
11 procedure. Free assets were used as a proxy measure for the company's
ability to secure additional borrowings, and were measured as the ratio of
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uncollateralised assets (i.e. not given as security) to total assets. The coalition
behaviour model suggests that parties interested in pursuing reorganisation
may implement various strategies to secure additional funds. For example,
equity holders may give up their remaining claim over the company's assets to
secure support of major lenders. In addition, where unsecured creditors can be
coerced to accept less than the face value of their claims, the resultant debt
forgiveness will free up assets. However, as the level of debt in the company's
capital structure increases it would become harder for coalitions to successfully
implement these strategies to secure reorganisation. As leverage increases,
equity's claim over the company's assets will diminish, thereby reducing its
ability and incentive to have the company attempt reorganisation. Moreover,
debt forgiveness achieved by paying unsecured creditors less than the face value
of their claims may not be sufficient to secure additional funding if the
company's leverage is extremely high. Therefore, it is proposed that the
company's leverage will affect the reorganisation decision. Highly levered firms
are expected to have difficulty gaining support for reorganisation and funding
for continued operations from various creditor coalitions.
This discussion suggests there are two aspects of leverage that will affect the
reorganisation decision:
1. the amount of debt in the company's capital structure, which will affect its
ability to secure the cooperation of coalitions of creditors that might
provide additional funds in reorganisation; and
2. the level of equity in the company's capital structure, and the incentive for
the equity (and management) to avoid liquidation.
The following proposition summarises our expectation regarding the effect of
leverage on the likelihood of reorganisation:
Proposition 1: Highly levered companies are less likely to reorganise.
Fisher and Martel (1995) and Comerford (1976) identified liquidity as a
significant financial dimension affecting reorganisation. Fisher and Martel
(1995) examined the impact of a firm's liquidity on the creditors' decision as to
whether reorganisation should proceed. The level of return offered in
reorganisation was found to affect the decision of unsecured or under-secured
creditors. They suggested this was due to creditors recognising that liquidation
would provide the unsecured creditors with poor returns after claims with
priority were satisfied. The prospect of an improved cash payment under a
reorganisation plan, made possible by the firm's short-term liquidity, was likely
to secure creditors' acceptance regardless of the company's long term
prospects. Therefore, higher levels of short-term liquidity should increase the
likelihood that unsecured creditors will work to secure reorganisation in
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Study
Objective
Financial
Frost-Drury, Greinke
& Shailer (1998)
Australia 26
companies
Campbell (1996) 121
Closely Held Firms
United States
Develop statistical model that distinguishes distressed companies
entering voluntary administration that reorganise from those that
liquidate, and healthy companies.
Working Capital Total Assets
Natural Log of Total Assets
Develop prediction model to forecast probability of bankruptcy
reorganisation.
Return on Assets (Profitability)
Natural Log of Total Assets (Size)
Non Pledged Assets (Free Assets)
Fisher & Martel
(1995) 338 Firms
Canada
Determine factors that distinguished reorganisation plans accepted
from those rejected by creditors
Hotchkiss (1995)
197 Firms
United States
Jensen-Conklin
(1992)
45 Firms
United States
Liquidation= reorganisation payoff
rate
Cash Payments Total Payments
Secured Claims Total Liabilities
Examine post bankruptcy performance of firms that had undergone Larger firms (Natural Log of Total
reorganisation under U.S. Chapter 11 procedure.
Assets) associated with lower
probability of reporting negative
income (Size)
Successful plans were proposed by
Exploratory empirical analysis concerned with determining the
`existence of any indicia regarding the likelihood of a plan's potential larger firms (Total Liabilities)
for full consummation'
Nonfinancial
Number of
secured creditors
Number of
undersecured,
secured creditors
Type of business
Industry
performance
Retention of CEO
in bankruptcy
(continued)
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Significant Variables
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Table 1
Prior research
Capital structure: level of debt= equity
interest.
Examine the potential information value of accounting data in
distinguishing firms in bankruptcy that reorganise versus those that
liquidate.
Non Collateralised Assets Total
Tangible Assets (Free Assets)
Net income Total Assets (Earnings
Prospects)
Level of Free Assets positively related
to successful reorganisation
Distinguish firms that reorganise from those that liquidate or
continue operating
Exploratory study to determine the characteristics of firms that
Larger firms were significantly more
reorganised and continued to exist for up to three years from time of successful (Size)
bankruptcy filing
Develop a multivariate model based on financial characteristics to
MDA model included the following
distinguish firms that succeed in Chapter 11 reorganisation compared ratios:
to those that failed
Quick Assets Total Assets (Liquidity)
Quick Assets Current Liabilities
(Liquidity)
Total Debt Total Assets (Leverage=
Stability)
Net Income Total Assets
(Profitability)
Current Assets Current Liabilities
(Liquidity)
Net Income Stockholders Equity
(Profitability)
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To understand the institutional procedures of Chapter 11 from an
empirical examination of firms that have emerged from Ch. 11
proceedings.
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Franks & Torous
(1989)
30 Firms
United States
Casey, McGee &
Stickney (1986)
113 Firms
United States
Hong (1983)
99 Firms
United States
LoPucki (1983a,
1983b)
41 Firms
United States
Comerford (1976)
52 Firms
United States
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coalition with other claimants. Acceptance of an immediate payment of less
than the face value of unsecured creditors' claims also provides some amount
of debt forgiveness, improving the company's overall position. The following
proposition is therefore suggested:
Proposition 2: Companies with higher levels of short-term liquidity are more
likely to reorganise.
White (1984, 1989), in modelling the outcome of bankruptcy proceedings,
demonstrates firms that successfully reorganise have more attractive earnings
prospects. Casey et al., (1986, p. 252) noted that firms expected to operate
profitably in the future should be able to generate funds internally or obtain
funds from external borrowing in order to emerge successfully from
bankruptcy proceedings. In some circumstances, past profitability may be a
valid indicator of reasonable future earnings prospects. For example, a
company with a profitable underlying business operation may become
insolvent due to cash flow problems associated with rapid expansion. This
type of company would be an ideal candidate for reorganisation. The short
breathing space provided by the Part 5.3A moratorium provides an
opportunity for restructuring immediate obligations while preserving the
profitable underlying business.
Gilson et al., (1990), in examining features of firms that privately restructure
debt versus those that reorganise under Chapter 11, report that firms privately
renegotiating debt had significantly superior performance as measured by
stock returns. Their explanation for the difference was that superior
performance is associated with a smaller reduction in going concern value,
which results in a higher firm market value=firm liquidation value. This
increased the incentive to renegotiate debt privately, rather than risk asset sales
likely to result from a Chapter 11 reorganisation. Where a company can
demonstrate going concern value, various coalitions will form where parties see
the opportunity to share in this going concern value of the company. The
following proposition summarises our expectation:
Proposition 3: Companies with good earnings prospects (indicated by past
profitability) are more likely to reorganise.
Secured creditors play a significant role in coalition behaviour and
determination of the reorganisation decision. Campbell (1996) demonstrated
that the number of secured creditors was an important factor in distinguishing between firms that reorganise and those that liquidate under the United
States Chapter 11 procedure. Campbell's (1996) study involved 121 firms that
had reorganised under Chapter 11, and found that a greater number of
secured creditors increased the likelihood of liquidation. White (1984) had
previously posited this relationship on the basis that secured creditors are in
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the best position to block a reorganisation attempt. Chaterjee et al., (1996)
provide evidence that restructuring decisions depend, in part, on the extent of
the `creditors co-ordination' problem as reflected by the nature and
complexity of debt claims. Moreover, Giammarino (1989) suggests that
information asymmetries between debt holders reduces the likelihood of
reorganisation.
Clearly, secured creditors are faced with an important decision as to
whether they will attempt to block reorganisation with intent to realise their
security. In contradiction to the view that secured creditors hinder
reorganisation, Fisher and Martel (1995) found that firms with a larger
amount of secured claims were more likely to be reorganised. However, their
study involved firms that attempted to reorganise under Canadian bankruptcy law where secured creditors enjoy a veto power over reorganisation
attempts. They suggested that secured creditors, particularly banks, have a
greater amount of information about the viability of firms attempting
reorganisation. Fisher and Martel (1995) argued that where support of
secured creditors for reorganisation is obtained, a positive signal is sent to
other creditors. They suggested this signaling would minimise problems with
creditors withholding their support for a reorganisation plan Ð often referred
to as `hold-out' problems.
Under the VA regime, general secured creditors do not enjoy a similar veto
power, which may minimise `holdout' problems. However, one class of secured
creditors, those with a substantial charge over all the company's assets, do have
the option of avoiding administration by enforcing their charge within a
`decision period' of ten days from when they are notified of the administrator's
appointment. 6 We suggest the existence of a substantial chargeholder will be
important to the reorganisation decision, due to the ability of these creditors to
avoid the moratorium that is imposed on other classes of creditors. Coalitions
involving the substantial chargeholder are only likely to arise where it can be
demonstrated that their security position will be protected in reorganisation. In
addition, charge holders are likely to be large lending institutions which will
have a greater amount of information about the viability of firms attempting
reorganisation. Clearly, the support of a substantial chargeholder will have to
be obtained for the reorganisation plan to proceed, and will be actively sought
by potential coalition parties that prefer reorganisation to liquidation. As
suggested by Fisher and Martel (1995) support of this senior creditor will send
a positive signal to other creditors regarding reorganisation. The following
proposition is, therefore, suggested:
Proposition 4: Companies that have a substantial chargeholder are more likely to
reorganise.
6
See s 441A of The Corporations Law (Cth).
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3.3. Control variables
Based on a review of relevant literature, we expect that company size and the
economic environment in which a financially distressed company operates will
have an effect on the company's reorganisation prospects and performance.
Therefore, we control for both industry and company size in the models
studied here.
Hotchkiss (1995), in her study of firms reorganising under Chapter 11,
reports that poor industry performance in the post bankruptcy period had a
significant relation to the incidence of a second bankruptcy or the requirement
for a further reorganisation. Campbell (1996) reported that the type of business
was a significant predictor of a successful reorganisation outcome: arguably,
this finding may relate, inter alia, to industry conditions for similar business
types in his sample. D'Aveni (1989) provides evidence that an inefficient firm is
more likely to `linger' if it is in an industry with a higher growth rate of
demand. The firm, although inefficient, can survive because of its improving
environment. Based on evidence that industry classification will have some
effect on reorganisation prospects and performance for individual companies,
this variable will be controlled for by (1) using industry matched samples of
reorganised and liquidated companies in the reorganisation decision model,
and (2) by including industry classification as a control variable in the model
for successful=unsuccessful reorganisations.
Studies that have examined the effect of company size on reorganisation
prospects indicate that larger companies are more likely to reorganise. White
(1983) suggests larger firms are more likely to have previously raised unsecured
capital, and assets generated by such borrowing provides collateral for
additional borrowing when faced with financial distress. Previous research by
Warner (1977), Altman (1984) and Campbell (1996) indicate the existence of an
economy of scale with respect to bankruptcy costs for larger firms. Larger
firms' bankruptcy costs are less significant when measured as a ratio of size.
The above discussion suggests that larger firms are more likely to secure
additional funding in reorganisation and are less likely to be further distressed
by costs associated with bankruptcy. Company size is also included as a
control in the analyses by using matched samples of reorganised and liquidated
companies in the first model developed, including size as a control variable in
the analysis for successful=unsuccessful reorganised companies.
4. Model development
Based on the results of the prior studies and the coalition behaviour model,
selected variables are considered in two logistic regression analyses. The first
model tests the propositions developed in the preceding section. The second
model is developed as a comparative model that examines whether the same
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ful' reorganised companies. Success is determined by examining performance
(profitability) after reorganisation.
It should be noted that the coalition behaviour model specifically deals with
the reorganisation decision, providing a basis for discussion leading to
formulation of propositions relating to whether a company is likely to
reorganise or liquidate. However, coalition theory remains relevant to the
development of the second comparative model, as efficient decision making by
the various coalitions that exist in voluntary administration will mean that
companies likely to perform poorly in reorganisation will not attempt to
reorganise. The dependent variable in the second model developed separates
companies on an `efficiency' criterion, that is, whether or not the companies are
successful in reorganisation. The model's dimensions represent the underlying
constructs that would likely exist if coalitions made decisions based on securing
the most efficient administration outcomes. Comparison of the second
`efficiency' model with the reorganisation decision model will provide useful
insight into the efficiency of the VA decision process.
Each of the financial dimensions is operationalised by financial ratios or
proxy variables. While a number of financial ratios could be used to represent
the selected financial dimensions, the final choice was restricted to those ratios
that could be calculated from the available data. The approach suggested by
Chen and Shimerda (1981) is followed, in that each financial dimension is
generally represented by one selected ratio. This approach avoids analysis
problems associated with correlation between ratios. Independent variables are
summarised in Table 2. Measures for each independent variable were from the
company's most recent annual report prior to the appointment of the
administrator. 7 The profit measure excluded abnormal and extraordinary
items, so that the measure more reliably represented the company's underlying
performance.
Reorganisation and liquidation samples were matched for size and industrial
classification in the first model. 8 For the second comparative model, matching
was not possible due to sample size constraints, therefore size and industry
classification were included in the analysis as control variables.
7
Therefore, the only available asset and liability measures were generally at book value
(cost less depreciation expense). However, it is possible that some items could have been
re-valued either subsequent or prior to balance date, which may have been prompted by
audit recommendations. Due to non-public disclosure of these items, they could not be
controlled for in the analysis.
8
Matching to control for variables was undertaken to neutralise effects of industry and
size. This allowed the development of a parsimonious model, which included only those
variables related to the propositions developed. Re-testing of the model on the complete
sample with industry and size included as control variables showed little difference from
the reported model.
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Table 2
Variables used in logistic regression analyses
Category
Ratio or Measure
Earnings Prospects
Liquidity (pay-off rate)
Leverage (free assets)
Equity Commitment
Debt Structure
operating profit= total assets
current assets= current liabilities
total assets= total liabilities
positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
existence of chargeholder (0 ˆ no charge,
1 ˆ charge)
Natural log of total assets
Company Size
Variable
Descriptor
ROA
CA=CL
TA=TL
Shareholders' Equity
Charge
Size
The dependent variable for the first model was determined by whether the
company reorganised (coded as 1), or liquidated (coded as 0). A company was
considered a liquidation if 1) the administration ended in liquidation, or 2) the
administration ended with a deed of company arrangement that provided for
winding-up (a `liquidating deed').
For the second regression, the dependent variable was based on return on
assets after administration. To develop a logistic regression model that could
be compared with the reorganisation decision model it was necessary for the
dependent variable to be dichotomous. The dichotomous dependent variable
was assigned a value of 1 (successful) where return on assets was positive based
on the average for the administration year (the year in which the administrator
was appointed) and the two years subsequent to administration year.
Therefore, companies deemed to be `unsuccessful' (coded as 0) were those
that consistently failed to achieve a positive return on assets even after
implementing a reorganisation plan. 9
5. Data
Data availability is a considerable restriction for research in this area, as
there are no special reporting requirements for a company under administration. Problems for empirical research relating to voluntary administration
arise due to the lack of consistent financial data for many companies.
Moreover, the costly process of identifying companies that are likely to have
9
The sensitivity of the cut-off criteria was examined. For one company ROA was
marginally positive at 2 per cent. Accordingly, ROA was examined for each year. The
company had performed poorly in the year of administration, however, it had achieved
an average ROA of 4.9 per cent over the subsequent two years. The dependent variable
for this case was assigned a value of 1 (successful). The next lowest value of ROA for
companies in the sample was 7 per cent; the classification was therefore not sensitive to
the cut-off chosen.
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247
some available data, and subsequent collection of that data are major
obstacles. Annual returns lodged with the ASIC provided data for analysis.
These returns were characterised by missing information, and for many
smaller companies, the reported accounting data were limited to key financial
data required to be provided on the annual return. In this study, data for 40
companies were obtained for the matched sample analysis. The sample
included 20 reorganised and 20 liquidated companies. Matching was based on
size, measured by total assets, and industrial classification. 10 The procedure
for selecting the sample of companies and the matching process employed is
detailed below:
1. A listing of all companies that appointed an administrator under Part
5.3A for the calendar years 1993 to 1995 was obtained from the ASIC. 11
VA began operation in July 1993, therefore companies were selected from
those that commenced administration during the first two and a half years
of the operation of the voluntary administration legislation (mid 1993 to
1995). Company data available from Internet search facilities provided by
the ASIC (the `National Names Index', see http://www.asic.gov.au) were
reviewed for each company to determine 1) if the company was still
registered, 2) whether a liquidator had been appointed, and 3) the
likelihood of financial data being available for a relevant company. Key
financial data were available for most companies until 1996, when the
ASIC reporting rules no longer required inclusion of key data in the
company's annual return. Determination of whether financial information would be available for a company was based on the number of pages
included in the annual report lodged with the ASIC as indicated by
National Names Index data.
2. For companies selected, ASIC document numbers were obtained for
annual reports from the National Names Index. Annual Returns and
Annual Reports for years prior and after appointment of an administrator
were obtained from the ASIC where available.
3. To facilitate analysis, data were collected for companies that concluded
voluntary administration with a deed of company arrangement, and
companies that were liquidated following voluntary administration.
Liquidated companies were selected that had at least some financial data
available for the years prior to appointment of the administrator.
10
Coverage is retail trade(10), wholesale trade(6), services(16), manufacturing(6),
research and development(2).
11
ASIC records indicated that 2927 applications were lodged for appointment of an
administrator over this time.
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4. Annual reports were obtained for 110 different companies over a number
of years. After perusal of annual reports it was necessary to exclude those
companies from the sample if (a) they were trustee companies that had
not traded, or (b) financial data were not included in their annual returns.
The remaining 81 companies included 50 reorganisations and 31
liquidations.
5. For the reorganisation=liquidation decision model, it was necessary to
match companies for both industry and size. First, annual returns were
reviewed to determine each company's `principal activity. 12 Based on their
principal activity, companies were classified according to the Australia and
New Zealand Industrial Classification (ANZSIC). Second, companies were
classified based on their total assets. 13 Companies were matched that had
the same industry and size classification. 14 The validity of size matching
was tested by performing a t-test on group means, and the mean difference
was not significant (see Table 3).
6. The final sample for the reorganisation=liquidation model comprised 40
companies, consisting of 20 reorganised companies, and 20 liquidated
companies. Companies in the sample included 26 proprietary companies,
12 unlisted public companies and two listed public companies. Range of
size (measured by total assets) for companies in the final sample is reported
in Table 3. Year of appointment for companies in the final sample was
1993± 13 companies, 1994 ±21 companies and 1995± 6 companies.
7. The final sample for the successful=unsuccessful reorganisation outcome
model comprised 32 companies, consisting of 13 successful reorganised
companies, and 19 unsuccessful reorganised companies. 15 Companies in
this sample included 25 proprietary companies and seven unlisted public
companies. Range of size (measured by total assets) for companies in the
final sample is reported in Table 6. Year of appointment for companies in
12
This information is listed on all Annual Returns lodged with ASIC.
13
Classification groupings used were 1) less than $0.5 million; 2) $0.5 million ± $1
million; 3) $1 million to $5 million; 4) greater than $5 million.
14
Two large very liquidated companies fell within the `greater than $5 million'
classification. Due to the restricted sample size, these could only be matched with
relatively smaller companies that were just above the threshold of $5 million in assets.
However, these companies would enjoy similar economies of scale. A matched-pairs ttest performed on group asset means was not significant, indicating the matching
process was successful.
15
The sample included 18 of the 20 reorganised companies used in the liquidation=
reorganisation model.
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the final sample was 1993 ± 7 companies, 1994± 20 companies and 1995± 5
companies. 16
6. Results
6.1. Reorganisation=liquidation model
Descriptive statistics for predictor variables included in the reorganisation=
liquidation model are presented in Table 3. Mean values of predictor variables
for the two groups are similar with the exception of the Current Ratio and
Total Assets divided by Total Liabilities (TA=TL). The mean difference for
TA=TL is marginally significant ( p ˆ 0.095).
Correlations among independent variables are reported in Table 4.
Correlations between variables were not high enough to cause concern with
multicollinearity for the subsequent logistic regression analysis (Tabachnick
and Fidell, 1996).
6.1.1. Multivariate tests
Logistic regression analysis was conducted to examine the discriminatory
power of selected variables between reorganisations and liquidations. The
results of the logistic regression analysis are presented in Table 5 below. The
model was significant, and prediction success was impressive. Results
confirmed the ability of selected variables to distinguish reorganised from
liquidated firms.
Proposition 1 suggested that highly levered companies are less likely to
reorganise. Two measures of leverage were included in the analysis. Results
indicate the outcome of a VA is more likely to be reorganisation where the
company has positive owners' equity. However, while TA=TL is a significant
16
Data screening was performed for the final sample of companies. Examination of
box-plots was undertaken to identify univariate outliers for each of the continuous
independent variables. Three potential outlier cases were identified: two that had large
values for the variable TA=TL, and one that had a large value for the variable CA=CL.
Examination of Cook's Distance and Leverage Values was undertaken to determine the
effect of these cases on the multivariate model. This examination indicated that the two
cases with potential outlier values for TA=TL had little effect on the multivariate model.
Diagnostics for the case with a large value for CA=CL suggested it might have had an
effect on the logistic regression model. The logistic regression analyses were re-run,
excluding the potential outlier case and its paired case in each analysis. The resulting
models were only marginally different with and without these cases, therefore, the
models are reported based on the full final sample of 40 companies.
# AAANZ, 2000
Liquidation (n ˆ 20)
Range
Range
Variable
Mean
S. Dev.
High
Low
CA=CL
Shareholders' Equity #
ROA
TA=TL
Charge #
Total Assets
5.51
0.65
0.11
0.75
0.75
1,976,069
17.33
n=a
0.87
0.60
n=a
1,883,780
77.18
1
2.92
2.77
1
5,771,200
0.06
0
1.07
0.09
0
41,667
significant at p < 0.05
For the nominal scale variables the last column shows Chi Square statistic
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
#
1.11
0.70
0.12
3.16
0.70
7,288,806
1.54
n=a
0.26
6.12
n=a
18,448,351
High
Low
t-statistic
(1-tailed)
Chi
Square
6.89
1
0.15
24.84
1
79,691,000
0.01
0
0.86
0.05
0
67,212
1.13
n=a
0.059
1.76
n=a
1.28
n=a
0.114
n=a
n=a
0.125
n=a
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Reorganisation (n ˆ 20)
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# AAANZ, 2000
Table 3
Univariate statistics-Reorganisation= liquidation decision
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251
Table 4
Correlations between predictor variables
Reorganisation= liquidation decision (n ˆ 40)
CA=CL
CA=CL
Shareholders' Equity
ROA
TA=TL
Charge
1.00
0.14
0.09
0.14
0.11
Shareholders'
Equity
1.00
0.33
0.23
0.11
ROA
TA=TL
1.00
0.02
0.13
1.00
0.31
Charge
1.00
For the dichotomous variables, the Eta strength-of-association index is reported between these
variables and the other interval scale variables. In all other cases within the table, Pearson
correlation coefficients are reported.
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
Table 5
Results of logistic regressionÐReorganisation= liquidation decision
Reorganised (1)
Liquidated (0)
Variable
B
Sig
Current Ratio
Positive Owners' Equity (0 ˆ ve, 1 ˆ ‡ve)
Return on Total Assets
Total Assets=Total Liabilities
Chargeholder (0 ˆ no charge, 1 ˆ charge)
2 Log Likelihood
2 (5, n ˆ 38)
Goodness-of-fit (significance)
Nagelkerke Psuedo R 2
Classification Accuracy
Reorganised (n ˆ 20)
Liquidated (n ˆ 20)
Overall (n ˆ 40)
0.17
3.05
1.47
5.42
0.14
31.43
23.97
0.0002
0.60
0.000
0.013
0.194
0.000
0.892
75% (15)
85% (17)
80% (32)
denotes significant at p < 0.05
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
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predictor variable, the direction of its effect is opposite to that suggested in the
proposition, with companies more likely to reorganise as leverage increases.
Thus, only partial support for Proposition 1 is found. This result might be
explained by the interaction of the two measures of leverage included in the
model. While the direction of the TA=TL variable is counter-intuitive at face
value, when interpreted in conjunction with the result for shareholders' equity
it appears that an upper bound (of one) occurs for the leverage ratio variable
for companies most likely to reorganise. The result suggests reorganisation is
most likely to occur when leverage is high, and some shareholders' equity
remains. This is consistent with equity holders pursuing reorganisation to
preserve their claim over the company's assets, however small that claim
might be.
Proposition 2, that companies with higher levels of short-term liquidity are
more likely to reorganise, is supported by the results. This suggests that
unsecured creditors have an important role in the decision-making coalition in
VA. Higher levels of short-term liquidity would allow the reorganisation plan
to include an immediate pay-off to these creditors. Their acceptance of the
reorganisation plan may also provide important debt forgiveness. Interestingly,
past profitability is not a significant predictor, providing no support for
Proposition 3. This suggests the reorganisation decision may not be based on a
consideration of available indicators of the company's long term prospects.
Furthermore, the results indicate major secured creditors may be indifferent to
the outcome of VA (Proposition 4).
The results appear to indicate that the reorganisation decision is largely a
result of `coalition' behaviour involving equity (with management acting as
agent) and unsecured creditors. We find that companies with positive owners'
equity and higher liquidity are more likely to reorganise. Reorganisation will
tend to preserve equity (and current management), and some amount of
liquidity will allow a reorganisation plan that provides an immediate return
to creditors. Results indicating that high leverage is associated with
reorganisation also conform to the `coalition' model. For highly levered
companies, liquidation would provide little or no return for unsecured
creditors. For unsecured creditors, choosing reorganisation in coalition with
equity would provide a marginally greater return. In addition, payment to
secured creditors from liquid assets would provide some measure of debt
forgiveness.
Prediction success rates for the logistic model were good: overall, 80 per
cent of liquidations and reorganisations were correctly classified (75 per cent
for reorganisations and 85 per cent for liquidations). Cross validation of
results for the model was performed by holding out individual pairs,
developing a model based on the other 38 observations, and using the model
to predict outcomes for the two observations held out. Classification success
for the 20 holdout tests was less than for the original model at 70 per cent
overall (70 per cent for reorganisations and 70 per cent for liquidations). The
# AAANZ, 2000
Unsuccessful (n ˆ 20)
Range
Variable
Mean
S. Dev.
High
CA=CL
Shareholders'
Equity #
ROA
TA=TL
Charge #
Industry #
Total Assets
3.89
0.38
9.68
n=a
35.72
1
0.21
1.21
0.62
6.31
10,381,041
0.92
1.33
n=a
2.29
33,586,345
2.92
4.69
1
8.00
122,000,000
Range
Low
Mean
0.01
0
0.83
0.09
0
2.00
139,745
0.77
0.58
0.31
1.05
0.58
5.68
12,846,898
significant at p < 0.05
For the nominal scale variables the last column shows Chi Square statistic
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
#
S. Dev.
High
0.63
n=a
2.42
1
0.36
0.59
n=a
2.21
41,772,198
0.09
2.53
1
8.00
184,000,000
t-statistic
(1-tailed)
Chi
Square
0.01
0
1.16
n=a
n=a
1.166
0.93
0.36
0
2.00
41,667
2.22
0.47
n=a
n=a
0.19
n=a
n=a
0.042
0.604
n=a
Low
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Successful (n ˆ 20)
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# AAANZ, 2000
Table 6
Univariate statistics ÐSuccessful=unsuccessful reorganisation (n ˆ 32)
253
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result of holdout testing suggests the model is reasonably stable, and
problems with overfitting due to the small sample size may not be of major
concern.
6.2. Successful=unsuccessful reorganisation model
Descriptive statistics for predictor variables included in the successful=
unsuccessful reorganisation model are presented in Table 6. Mean values of
predictor variables for the two groups are similar with the exception of the
Current Ratio and Return on Total Assets (ROA). The mean difference for
Current Ratio is not significant, while ROA is significant (p < 0.05).
Correlations among independent variables for this model are reported in
Table 7. While some correlations are high, it is unlikely they would create
statistical problems at the levels found (Tabachnick and Fidell, 1996). To
confirm that multicollinearity is not at a problematical level for development of
the logistic regression model, an additional analysis was performed omitting
the variable Total Assets=Total Liabilities, which is reasonably highly
correlated with two other variables (Current Ratio and Shareholders' Equity).
The result of this analysis was substantively consistent with the full model,
thereby alleviating concerns about multicollinearity.
Results of the second logistic regression model (see Table 8) indicate
companies that reorganise successfully are more profitable, are more highly
Table 7
Correlations between predictor variablesÐSuccessful=unsuccessful reorganisation
CA=CL
CA=CL
Shareholders' Equity
ROA
TA=TL
Charge
Log Total Assets
Industry
1.00
0.21
0.18
0.72
0.14
0.05
0.11
Shareholders'
equity
1.00
0.01
0.65
0.06
0.08
0.03
ROA
TA=TL
Charge
1.00
0.01
0.19
0.20
0.00
1.00
0.08
0.04
0.07
1.00
0.35
0.23
Log
total
assets
Industry
1.00
0.00
1.00
For the dichotomous variables, the Eta strength-of-association index is reported between these
variables and the other interval scale variables. In all other cases within the table, Pearson
correlation coefficients are reported.
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
Size ˆ Natural log of total assets
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Table 8
Results of logistic regressionÐSuccessful= unsuccessful reorganisation
‡ve ROA (1)
ve ROA (0)
Variable
Current Ratio
Positive Owners' Equity (0 ˆ ve, 1 ˆ ‡ve)
Return on Total Assets
Total Assets=Total Liabilities
Chargeholder (0 ˆ no charge, 1 ˆ charge)
Natural Log of Total Assets
Industry
Mining
Manufacturing
Wholesale
Retail
Service
2 Log Likelihood
2 (10, n ˆ 32)
Goodness-of-fit (significance)
Nagelkerke Psuedo R 2
Classification Accuracy
‡ve ROAÐSuccessful (n ˆ 13)
ve ROAÐUnsuccessful (n ˆ 19)
Overall (n ˆ 32)
B
Sig
7.68
5.64
10.23
7.91
1.07
0.8
1.33
1.84
8.69
19.47
0.01
14.013
29.217
0.010
0.015
0.005
0.073
0.562
0.103
0.004
0.0011
0.81
85% (13)
89% (17)
87% (28)
denotes significant at p < 0.05
CA=CL ˆ current assets=current liabilities
Shareholders' Equity ˆ positive owners' equity (0 ˆ ve, 1 ˆ ‡ve)
ROA ˆ operating profit=total assets
TA=TL ˆ total assets=total liabilities
Charge ˆ existence of chargeholder (0 ˆ no charge, 1 ˆ charge)
Size ˆ Natural log of total assets
levered and have higher levels of short-term liquidity. In addition, industry
classification has an effect on the likely success of reorganisation. Examination
of raw data for industry classifications showed that a higher proportion of
retail companies was unsuccessful than for other classifications. This is
reflected in the large negative coefficient for this variable in the model. The
existence of a chargeholder, and company size were not significant predictors
of successful=unsuccessful reorganisation.
As discussed previously, the second model is presented for the purpose of
comparison with the actual decision model. Results relating to the effects of
individual variables for the second model differ from those in the reorganisation decision model. The most striking difference between the models is the
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strong significance of past profitability as a predictor of successful reorganisation. This result has implications regarding the efficiency of the liquidation=
reorganisation decision, as profitability was not a significant predictor in the
decision model. The results of the comparative model suggest past profitability
is an important variable in distinguishing, from a pool of distressed companies,
suitable candidates for reorganisation.
The negative sign for the TA=TL ratio, while consistent with the decision
model, suggests that higher leverage at the time of reorganisation is associated
with success (greater profitability) in reorganisation. In addition, the results
indicate negative owner's equity at the time of reorganisation is associated with
successful reorganisation. We suggest these results need to be considered in the
context of restructuring that will likely take place because of the administration
process. A company's capital structure and leverage position may be altered
significantly because of reorganisation. For example, payment to unsecured
creditors from current assets, which appears to be an important aspect to the
decision to reorganise, may give rise to significant levels of debt forgiveness
that will alter the company's leverage position. The nature of reorganisation
plans adopted under VA, and their relationship to post-administration
performance is an aspect of the operation of VA that could be considered in
future research.
Prediction success rates for the model were good: overall, 87 per cent of
successful and unsuccessful reorganisations were correctly classified (85 per
cent for successful reorganisations and 89 per cent for unsuccessful
reorganisations). Cross validation of results for the model was performed by
holding out individual cases, developing a model based on all other
observations, and using the model to predict outcomes for the observation
held out. Classification success for the 20 holdout tests was similar to the
original model at 81 per cent overall (73 per cent for successful reorganisations
and 88 per cent for unsuccessful reorganisations). Again, the result of holdout
testing suggests the model is reasonably stable, and problems with overfitting
due to the small sample size may not be of major concern in relation to the
results of analysis.
7. Summary and conclusions
Overall, the results of this study have the following implications. First, the
analyses and results lend support to the coalition behaviour theory of
reorganisation choice. Importantly, this provides a basis for further development of a parsimonious bankruptcy reorganisation prediction model based on
a theoretical background. The reorganisation decision model developed in this
study could be applied to data from other jurisdictions to further test the
validity of analysing coalition behaviour as a means of understanding how
insolvency law affects the decision making process.
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257
Limitations of the generalisability of results concerning testing of coalition
behaviour theory arise from the difficulty with obtaining data. The small
sample size and missing data present limitations, although these are common
problems with research in the area of financial distress. Generalisability of
results could be determined more accurately by further testing of the model
with an independent holdout sample. A further limitation associated with the
difficulty of obtaining data is the limited choice of variables available to
represent financial constructs in the models. If the chosen variables do not
adequately operationalise financial constructs outlined in the propositions
there may be some divide between the theory and the model tested.
For policy-makers the results presented here are hardly reassuring.
Arguably, the VA procedure appears to be problematic in terms of possible
bias toward reorganisation of inefficient companies. The intent of the
legislation was to allow viable companies the opportunity to reorganise.
However, failure of the VA procedure to adequately filter inefficient
companies may be adding to the overall economic cost associated with
corporate insolvency. The results indicate that decision-making of parties
involved in the reorganisation decision is inefficient by allowing companies
with few prospects for recovery to proceed with reorganisation. Greater
liquidity, which will likely mean reasonable immediate return for unsecured
creditors, and positive owners' equity as distinguishing characteristics for
firms that reorganise indicate the decision making `coalition' in VA is made
up of equity and unsecured creditors. As discussed above, equity holders will
pursue reorganisation to preserve their interest in the company, and
unsecured creditors will support reorganisation if the anticipated return is
greater than in liquidation. Decisions as to the company's future do not
appear to be based on an assessment of its prospects to operate efficiently in
the future. This is supported by underlying profitability being an important
variable in the model that distinguished successful from unsuccessful
reorganised companies.
These findings also have implications for Australian insolvency policy,
which has adopted a flexible approach to allowing companies to proceed with
reorganisation. Other jurisdictions have requirements that are more stringent
for distressed firms that seek to reorganise. For example, the United States
Chapter 11 procedure has greater scrutiny by the courts of the validity of a
reorganisation plan. German `Composition Proceedings' require composition
plans to be confirmed by the courts and the reorganisation process under
French law requires a `continuation plan' to be approved by the Commercial
Court (Iraj, 1997, Franks et al., 1996). The results presented in this paper
suggest that the trade-off between reducing costs associated with a flexible
regime and the economic cost of allowing unsuitable companies to reorganise
requires further consideration. Therefore, extension of the work presented here
to better understand the effects of insolvency legislation on decision outcomes
may be useful for constructing efficient insolvency rules.
# AAANZ, 2000
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J. Routledge, D. Gadenne / Accounting and Finance 40 (2000) 233± 260
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