Corporate social responsibility performance, financial distress and firm life cycle: evidence from Australia

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Corporate Social Responsibility Performance, Financial Distre
Cycle: Evidence from Australia
Article in Accounting and Finance · April 2017
DOI: 10.1111/acfi.12277
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Ahmed Al‐Hadi
Curtin University
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Ali Yaftian
Deakin University
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Mostafa Monzur Hasan
Macquarie University
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Corporate social responsibility performance, financial
distress and firm life cycle: evidence from Australia
Ahmed Al-Hadia, Bikram Chatterjeeb , Ali Yaftianc,
Grantley Taylora, Mostafa Monzur Hasand
aSchool of Accounting, Curtin Business School, Curtin University, Perth, WA, Australia
bDepartment of Accounting, Waikato Management School, The University of Waikato,
Hamilton, New Zealand
cDepartment of Accounting, Deakin Business School, Deakin University, Burwood, VIC,
Australia
dSchool of Economics and Finance, Curtin Business School, Curtin University, Perth, WA,
Australia
Abstract
This study examines the association between corporate socialresponsibility
(CSR) performance and financialdistressand additionally the moderating
impact of firm life cycle stages on that association. Based on a sample of 651
publicly listed Australian firm-years’ data covering the 2007–2013 period, our
regression results show that positive CSR activity significantly reduces financia
distress of the firm. In addition, the negative association between positive CSR
performance and financial distress is more pronounced for firms in mature life
cycle stages.Our results are robust to alternative proxy measures of financial
distress, CSR performance and life cycle stages.
Key words:Corporate social responsibility; Financial distress; Corporate life
cycle
JEL classification: G01, G32, H26
doi: 10.1111/acfi.12277
1. Introduction
Corporate socialresponsibility (CSR) and financialdistress are prominent
research topics, but often these constructs are considered in isolation (Deegan
2002).The rationale behind corporate CSR engagement is multidimensional
and can range from culturaland socialreasons to economic and financial
reasons.We thus adopt a broad perspective of CSR activities and reporting
following Moser and Martin (2012),which encapsulates allcorporate actions
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Accounting and Finance

that impact firms’ stakeholders. Specifically, we are motivated in this study to
empiricallyexaminethe association between financialdistressand CSR
performanceof publicly listed Australian firmsbecausefinancialdistress
impacts the risk-shifting behaviour of firm management.
CSR can be regarded as how a business takes accountof its socialand
environmentalimpacts of its operations(Deegan,2002) and generally
incorporates benefits by way of economic development to both the firm and
the society in which the firm operates (Holme and Watts,2006;Moser and
Martin, 2012). CSR is regarded as key factor in the success and survivalof afirm (Hoi et al.,2013).However,there is generally no regulatory regime in
place mandatingdisclosureof CSR activities of a firm other than the
Australian Stock Exchange governance best practice recommendations, which
suggest that firms could consider reporting on these activities. Firms can then
voluntarilydiscloseCSR activities and a likely consequenceis that the
reporting of such activities will vary widely.
CSR activities could be directed primarily as a risk managementstrategy
used by a firm to enhance its reputation, which, in turn, protects the firm from
the risk of adverse political,regulatory and socialsanctions (Godfrey,2005;
Minor and Morgan, 2011). A lack of positive CSR orientation by the firm may
lead to negative sanctions such as loss of firm/executive reputation,increased
political/media pressure,and potentialfines and penalties and even possibly
consumer boycott. Further, positive engagement in CSR related activities may
generate a range of financial benefits to a firm. Indeed, the combined benefits
positive CSR engagement may out-weight the associated costs.Accordingly,firms could to some degree manage their financialdisposition by increasing
positive CSR activities (Godfrey, 2005) so as to lessen the expected probabilit
of falling into a state of financial distress.
We also argue thatthe association between CSR and financialdistress is
moderated by the firms’life cycle stage.Given that managements’access to
resources and their strategy are likely to evolve across different life cycle stag
we conjecture that the relation between financial distress and CSR performan
to similarly change across life cycle stages.The reason for this is thatany
association between financialdistressand CSR performance isdynamic in
nature contingent upon variation in economic fundamentals (e.g.cash flows,
retained earnings, asset turnover and solvency-related risks) and opportunitie
available to the firm across its different life cycle stages. Thus, we assess that
relation between financialdistress and CSR performance evolves conditional
upon firm life cycle stages.
Based on a sample of651 firm-yearsof publicly listed Australian firms
covering the 2007–2013 period, our regression results show that positive CSR
performance is significantly and negatively associated with financialdistress.
Moreover,the negative association between positive CSR performance andfinancialdistressis magnified forfirms in the maturestageof life cycle
development.Our results are robustto alternative proxy measures ofCSR
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performance,financialdistress and life cycle stages.Our findings extend the
literature on the drivers of financial distress and the economic consequences o
engaging in certain types of CSR activity.
This study contributes to the literature in severalimportant ways.First, it
provides unique empirical evidence that assesses the association between CSR
performance and financialdistress.A negative association isevident.Thisfinding suggests that a firm engaging in positive CSR activities also takes into
account its financialdisposition,which confirms the view that CSR is a core
activity used by firmsto support their financialactivities.Our findings
support the view that CSR activities preserve corporate financial performance
(Godfrey et al.,2009).This study then links CSR performance with firm life
cycle stages and provides evidence that the interaction between both positive
CSR performance and life cycle progression isempirically associated withfinancialdistress.In fact, our empiricalresultsshow that the negative
association between positive CSR activitiesand financialdistressis largely
magnified due to firm life cycle progression.To the bestof our knowledge,
this study is the firstto documentthis association empirically.Second,this
study extendsthe literatureby examiningthe association between CSR
performanceand financial distressgenerallyand by arguing that CSR
activities constitute a set of risk management mechanisms and strategies that
impact a whole range of stakeholders.This association is likely to be value
relevantto investorsin particular in assessing risk premiumsrelating to
future cash flows and the cost ofcapital,and in determining the likelihood
that a firm will be exposedto financial distress.This study provides
important evidence regarding the implications of CSR performance for firms’financial risk management.This is particularly important given that
sustainability and CSR performanceconstitutecore businessactivitiesof
Australian listed firms.
The remainder proceeds as follows. Section 2 outlines the background to the
study and develops our hypotheses.Section 3 discusses the research design
including thesampleand statisticaltechniques.Section 4 summarisesthe
empirical results. Finally, Section 5 concludes the paper.
2. Background and hypotheses development
2.1. Financial distress
Corporate financial distress, according to Altman and Hotchkiss (2006), is a
rathervague term,which can be furtherattributed to fourgeneric terms
commonly used in business research: failure, insolvency, bankruptcy and defa
Failure arises when the realised rate of return on invested capital, with allowan
for risk consideration, is significantly and continually lower than prevailing rate
on similar investments or insufficient revenues to cover costs,and where the
average return on investment is constantly below the firm’s cost of capital.
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Critically, financial distress increases incentives for risk-shifting to occur by
shareholders and their agents (i.e. firm management) (Maksimovic and Titma
1991;Eberhart and Senbet,1993).Indeed,in times of financialdistress,risk-
shifting behaviourincreases(Maksimovic and Titman,1991;Eberhartand
Senbet,1993;Campello et al.,2010,2011,2012).Financially distressed firms
exhibitan increase in the costof capital,a reduction in access to external
funding sources,weakercreditratingsand, in general,an increase in the
disposition of managers to take on more risk (Edwards et al., 2013). However,
credit-constrained firms focus on the need to conserve capital,to maintain
credit ratings, to meet the requirements of debt covenants and to continue as
going concern.A firm in financialdistress may also be subject to the risk of
severe negative sanctions such as loss of firm/executive reputation,increased
political/media pressure,potentialfinesand penalties,and even consumer/
creditorreprimands.In equilibrium, a firm will carry out CSR activities
provided that the marginal benefits of doing so exceeds marginal costs. A firm
strategies designed to reduce financial distress will become more appealing a
viable as the potentialcosts of financialdistressincrease.Overall, firm
managementmay be compelled to undertakerisk mitigating CSR-related
strategiesto mitigate the risksand costsassociated with financialdistress.
While there are severalmethodsto mitigate risk-shifting behaviour,more
traditionalmethods (e.g.the use of CSR) have not been evaluated tillnow,
motivating this study.
2.2. CSR performance and financial distress
Margolis and Walsh (2001)reviewed109 studiesthat examinedthe
association between CSR orientation and corporate financialperformance
and found that 54 of these studies reported a positive association between th
two. Godfrey et al. (2009) and Attig et al. (2013) find that enhanced financial
performance forstrongly CSR orientated firmsarisesthrough creation of
strongerexchangerelationshipswith key stakeholderssuch as customers,
creditors and employees, in negating the occurrence or potential impediment
of governmentintervention,and with the view to enhance future revenue
growth. Waddock and Graves (1997),purport that firms meet internal
stakeholders’expectationsthrough strategic use offinancialresourcesthat
enhances firms’reputation and competiveness.El Ghoul et al.(2011) provide
evidence thatstronger CSR engagementis associated with a lower costof
equity capitalwhile Cheng et al.(2013)find that firms with superior CSR
orientation have both better stakeholder engagement and transparency aroun
CSR performance which in turn assist in reducing capital constraints. Lee and
Faff (2009) and ElGhoul et al.(2011) assert that firms exhibiting poor CSR
practices face significantly higher idiosyncratic risk.
Minor and Morgan (2011) and Hoi et al. (2013) highlight the emerging trend
that CSR activities and reporting can be viewed as an important part of firm’s
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risk management.According to the risk management argument,a firm that
engages in and reports on its CSR activities would serve the interests of its
shareholders,which could potentially mitigate the risk associated with falling
into financial distress. Specifically, extensive positive CSR activities that impac
a range of stakeholdersact as a hedgeagainstfinancialimpedimentsor
constraints as the firm may be able to galvanise,and rely on its linkages and
reputation with various stakeholders to mitigate risks of financialdistress.Afirm’s action designed to ensure financial stability is legitimately influenced by
its attitude to and actions about CSR,which encapsulate broader consider-
ations regarding legality and ethics (Avi-Yonah,2008).As a result, a firm
develops CSR-related policies,strategies and activities that provide the most
favourable financial outcomes in a complex and competitive business environ-
ment.Accordingly,the risk managementperspective suggests thatincreased
positive CSR activitiesand financialdistressshould be systematically and
negativelyrelated.Godfrey et al. (2009) extendsthe risk management
perspective by asserting that when firms participate in institutionaltype CSR
activities aimed at society as a whole, this creates goodwill or moral capital fo
the firm that provides insurance-like protection when negative events occur.
They posit that such activity leads to positive attributions from stakeholders,
who then tempertheir negativejudgementsand sanctionstowardsfirms
because of this goodwill and this serves to preserve economic value for the fir
Another perspectiverelieson stakeholdertheory whereby positiveCSR
engagementrepresents a proxy for high quality management(Gross,2009).
Altman and Hotchkiss (2006) report that a pervasive reason as to why firms fa
into financial distress is due to management incompetence. If CSR activities ar
reflective of management quality in general(Attig and Cleary,2015),then it
follows that firms engaged in those activities are less likely to fall into a state ofinancial distress. Gross (2009) uses both multivariate regressions and a discre
time hazard modelto report that CSR disclosures are significantly negatively
associated with the degree of financial distress in the U.S. context. Gross (200
also shows that high disclosing firms (i.e.those in the top quartile of KLD
scores) are 11 percent less likely to experience takeover or default. In the U.S.
context,Attig et al.(2013)find a positive association between strong social
performanceand firms’ credit ratings,which they attributeto improved
stakeholder relations and an increase in firms’ long-term sustainability, a signa
of efficient resource use and sound financialperformance,and a reduction in
costs associated with socially irresponsible behaviour. In particular, Attig et al.
(2013)find that stakeholdermanagementattributessuch as community
relations,diversity,employeerelations,environmentalperformanceand
product characteristics are the most important in explaining firms’creditwor-
thiness. Overall, Attig et al. (2013) posit that credit analysts view positive CSR
activities favourably in their rating decisions because the resulting improve-
ments in long-term sustainability reduce the probability of default.Addition-
ally, disclosure of CSR information may enhance stakeholders’perception of
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compliance,governance and risk management,which could in turn provide
information regarding firms’ probability distributions of its future cash flows.
We conjecture that a similar line of argument could account for a possible
negativeassociation between firms’positiveCSR disclosureand financial
distress.
Taken as a whole, we thus expect firms that exhibit a higher level of positive
CSR activities as a risk management strategy to be subject to lower levels offinancial distress. We thus hypothesise that:
H1: All else being equal, positive CSR performance is negatively associated w
financial distress.
2.3. Firm life cycle, CSR disclosure and financial distress
Life cycle theory positsthat firms are subjectto systematic changesin
operating,investing and financing activities,resource endowment,organisa-
tional capabilities,risk appetiteand strategiesas they progressthrough
different stages (Helfat and Peteraf, 2003). Extant studies show that introduc-
tion and decline firms are less profitable and more risky,while growth and
mature firms are more profitable and less risky (Dickinson,2011;Habib and
Hasan,2015).It is thus not unreasonable to expect that these differences will
impact levels of financial distress across each stage of the firm life cycle.
Investors evaluate a firm’s ability to deal with financial distress and recover
profitability primarily through itsgeneration ofcash flows and earnings
potential (Black, 1998). When firms are faced with financial constraints, as the
are more likely to do so in their early stages of growth, their management tea
may search for ways to improve capabilities and resource retention (Helfat an
Peteraf, 2003). However, in the early stages, firms may lack liquid resources a
the ability to effectively compete with their peers (Spence, 1977, 1979, 1981)
particular, according to dynamic resourced-based theory, human capital, socia
capital and cognition, and resources (e.g. financing, technological and materia
are likely to be lacking in the early stages of firms’ life cycle (Helfat and Petera
2003). In the early stages of life, firms may face a high cost of capital owing to
uncertainties about future cash flows and earnings and the potential difficulty
of raising additionalcapital(Jenkins et al.,2004;Kim and Suh,2009;Hasan
et al., 2015).
During the mature phase, the firms may have greater competitive advantag
through resource use,capability managementand maintenance (Gray and
Ariss, 1985;Helfat and Peteraf,2003).In the mature stage,firms may be
sufficiently wellresourced making them less susceptible to financialdistress.
Access to greater resources including expertise in the maturity phase may me
that firm management can focus on maintaining reputation and investments
(Javanovic, 1982; Hasan and Habib, 2017). Firms in this stage of their life cycle
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have higher earningsper share, retainedearnings/totalassets,retained
earnings/totalequity and return on netoperating assets,leading to higher
and sustained dividend payouts compared to younger stage firms (DeAngelo
et al.,2006;Dickinson,2011).Firm size and age also increase in the mature
phase.Maintenance ofoperating cash flows,ongoing certainty relating to
future cash flows, earnings, innovations and investments and profit margins in
mature stage firmsmay mean thatthese firmsare lessprone to financial
distress.
Given thatpositive CSR performance reduces financialdistress,and thatfinancialdistress is contingent on firm life cycle,it is also possible that both
CSR performance and life cycle stages can jointly impact financial distress of afirm. Moreover,the association between financialdistress and CSR perfor-
mance is likely to be magnified as a consequence offirm life cycle stages.
Mature firms are concerned with thereputationalconsequencesof their
activities and how they interactwith key stakeholders,including regulatory
authorities and hence these firms are likely to engage in positive CSR activitie
more extensively as compared to younger or decline stage firms (Hasan and
Habib, 2017). In fact, in the early and decline phases of firms’ life cycle, CSR
activities and disclosure,and indirect costs including reputationaleffects andfinancial reporting effects, are likely to be less important than access to badly
needed capitalfor survival,growth,innovation and sustained financing.The
reason for this is that younger firms face uncertainty concerning revenue flow
and costs (Javanovic, 1982) and these firms face risk-taking around investmen
and innovations (Gort and Klepper, 1982; Miller and Friesen, 1984; Dickinson,
2011).Younger firms are concerned largely with achieving growth objectives
and ensuring that they can adequately compete and have sufficient resources
expand into new markets and to develop new product lines, and hence are les
likely to be concerned with engaging in positive CSR activities (Ramaswamy
et al.,2008).Legitimacy with key stakeholders by way of increased positive
CSR activities is likely to be less important as compared to achieving financial
objectives. The need to conserve capital or to meet the minimum capital need
of the firm is less criticalfor mature firms,so these firms can expend greater
resources in ensuring they engage in, and adequately communicate their CSR
activities (Hasan and Habib, 2017).
Certainty and reduced risk relating to current (and possibly future) earnings
and cash flows may mean that mature stage firms have reduced risk of financ
distress and a higher propensity to pursue positive CSR arrangements includin
communication of those activities.The reason is managers of these firms are
likely to have a better understanding ofthe environmentin which the firm
operates and have more resources at their disposalwhich may allow them to
identify opportunities to engage in, and communicate positive CSR activities.
Indeed, Waddock and Graves (1997) and Elsayed and Paton (2007) argue that
the existence offunds is a key determinantof whether managers decide to
engage in positive CSR activities. Moreover, if firms have excess cash, reduced
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A. Al-Hadi et al./Accounting and Finance 7

innovations,less competition and relatively higherlevelsof agency costs,
management of mature stage firms will be incentivised to re-invigorate the fir
by engagementin positive CSR programs (Jawahar and McLaughlin,2001;
Elsayed and Paton,2007).To do so may enhance a firm’s competitive and
reputation position in the market. In addition, managers of mature stage firms
are likely to be mindful of the potential reputational costs associated with poo
CSR engagement and communication.In essence,based on the difference in
economic fundamentals between young and older firms, the dynamic between
CSR activities and financialdistress is magnified (Miller and Friesen,1984;
Black, 1998;Helfat and Peteraf, 2003).Mature firms with steady-state
investments,combined with effective legitimacy with society through more
extensive positive CSR activities,are likely to face reduced financialdistress.
The reason is mature firms capitalise on their relations with key stakeholders,
and society as a whole, to maintain reputation and ensure that this also assist
in sustaining competitive advantage and financing opportunities.Thus, the
association between positive CSR performance and financial distress is likely t
be moderated by firm life cycle stages. Therefore, we hypothesise that:
H2: All else being equal, the association between positive CSR performance a
financial distress is magnified for firms in the mature life cycle stage.
3. Research design
3.1. Sample and data
Our initial sample consists of 135 randomly selected publicly-listed Australiafirms over the period 2007–2013. The final sample consists of 93 firms (651 fi
year observations) after excluding firms with missing data (42). A summary of
sample reconciliation is presented in Table 1, panel A. The number of firm-yea
observations distributed across industry sectors is provided as Table 1, panel
and the number of firms distributed across industry sectors and years is provi
as Table 1, Panel C. Both Panel B and C show that industrials, materials and
consumer discretionary sectors dominate in our sample.
3.2. Dependent variable
Financialdistress is the dependentvariable in this study.To improve the
robustness of our results, we rely on three measures of financial distress used
the accounting and finance literature:Berger et al.(1999) model(BOS_Dis),
Altman (1968)model(AltmanZ)and Almeida and Campello (2007)model
(AC_Dis). The models are each defined in Appendix I. For all these measures,
higher values of our financial distress proxies represent lower levels of financi
distress.
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3.3. Independent variables
3.3.1.Corporate social responsibility performance
Our independentvariable is represented by corporate socialresponsibility
(CSR) performance, which is used as a proxy measure of the level of positive
(or negative) CSR activity undertaken by a firm (Cho et al., 2013). We model
Table 1
Sample selection and distribution of the sample
Panel A: Sample Selection
Initial Sample – firms (firm-year observations) 135 (945)
Less
Financial and insurance firms 15 (105)
Firms with missing data 27 (189)
Final sample 93 (651)
Panel B: Number of observation based on industry
Industry Classifications Number Percent
Consumer Discretionary 136 0.201
Consumer Staples 34 0.050
Energy 58 0.100
Financials 4 0.006
Healthcare 36 0.055
Industrials 154 0.236
Information Technology 42 0.064
Materials 150 0.230
Telecommunication Services 14 0.021
Utilities 23 0.035
Total 651 100
Panel C: Distribution of firms across industry and year
Industry Classifications 2007 2008 2009 2010 2011 2012 2013 2014
Consumer Discretionary 1 20 19 20 20 19 19 19
Consumer Staples 1 6 5 6 6 4 4 3
Energy 1 10 10 10 10 6 6 6
Financials 1 1 1 1 1 0 0 0
Healthcare 1 6 6 6 6 4 4 4
Industrials 1 22 23 22 23 21 21 22
Information Technology 1 6 6 6 6 6 6 6
Materials 1 23 21 23 21 21 21 20
Telecommunication Services1 2 2 2 2 2 2 2
Utilities 1 3 3 4 4 3 3 3
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CSR performanceas a set of heterogeneousactivitiesin line with most
literature (see, e.g. Godfrey et al., 2009). Our proxy measures of CSR activity
are based on GlobalReporting Initiative (GRI)G4 sustainability reporting
guidelines.Specifically,using the GRI index of 75 items of CSR activity,we
divide those items into positive areas of CSR activity (43) and negative CSR
activities(32) in a similar mannerto that of Cho et al. (2013).Both the
positiveand negativegrouping of itemsincludesthe differenttypesand
categoriesof CSR activities.Positive CSR activitiescomprise forinstance
activitiesaround improving environmentalefforts,strengthening customer
relationships,improving employmentand health and safety asevidence of
adherenceto regulations,best practice,monitoringand effectivenessof
resource usage.Negative CSR activitiesmay comprise such activities,for
instance,as the payment of fines,the existence of liabilities relating to poor
environmentalor socialpractices,and engagement in controversialactivities
or risky activities.Thus,any potentialmeasurement error arising from using
CSR disclosure as a proxy for a broad range of CSR activities is minimised in
our study.
Our first measure of CSR reporting is based on the number of positive CSR
items disclosed by a firm in a given year: POS_CSR = natural log of the numbe
of positive CSR items (43) reported in the annual report. Our second measure
of CSR reporting is the natural log of the number of negative CSR items (32)
reported by each firm (NEG_CSR).Activitiesthat comprisepositiveand
negative CSR performance are provided in Appendix II.Use of these items
ensuresthat our CSR index includesa broad range ofcategoriesof CSR
disclosure that could possibly be engaged in by a corporation.We examined
sample firms’annualreports to analyse the reporting of75 individualCSR
activity items that can be grouped into ‘environmental’ (30 items) and ‘social’
(45 items). The association between each of these CSR performance grouping
and financial distress is examined.
For each of the 75 individualCSR activity item,a firm represented was
scored either1 for disclosure ofa particularperformance attribute,or 0
otherwise.The scoring was performed by a research assistant and an author,
with both cross-checking a sample for consistency.
3.3.2.Life cycle variable
Following prior studies (e.g. DeAngelo et al., 2006; Owen and Yawson, 2010
Al-Hadi et al., 2016), we employ the DeAngelo et al. (2006) model of firm life
cycle which utilises retained earnings scaled by totalassets or totalequity to
measure the stages of development in that life cycle.DeAngelo et al.(2006)
claim that the mix of earned/contributed capital(i.e.retained earnings (RE)
scaled by total assets (TA) or total equity (TE)) captures essential information
regarding corporate life cycle. Firms with high retained earnings to total asset
ratio (RE/TA) or retained earnings to total equity ratio (RE/TE) are typically
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more mature, or old with declining investment, while firms with a low RE/TA
or RE/TE tend to be young and growing.
3.4. Control variables
We include several control variables in our regression models, including firm
size, leverage,research and development(R&D) intensity,cash holding,
liquidity, profitability, industry sector and year effects.
Firm size (SIZE),measured as the naturallog of totalassets,controls for
differencesin resourcing,ability to cope with competition and funding
opportunities.Based on prior research,we expect larger firms to be able to
cope betterin periods of financialdistressbecausethey possesssuperior
economic and political power relative to smaller firms.
Leverage (LEV), measured as short-term and long-term debt divided by total
assets, controls for the level of a firm’s indebtedness. R&D intensity (RDINT),
measured as R&D expenditure divided by total assets, controls for firms’ level
of R&D expenditure.R&D-intensive firms are more likely to be subjectto
distressthan capitalintensive firms.We include firm’scash holdingsand
liquidity position to control for firms’ ability to deal with periods of financial
constraints.Additionally,we controlfor firm’s profitability using return on
assets (ROA) and loss (LOSS). Previous literatures suggest positive association
between CSR and liquidity (e.g.Subramaniam et al.,2016).Thus, we also
include liquidity ratio (QUICK).
Finally, industry sector (IND)dummy variables,defined by the two-digit
Global Industry Classification Standard (GICS) codes, are included as control
variables in our study as it is possible for financial distress to fluctuate across
different industry sectors.We also controlfor year fixed effect to controlfor
time trend.
3.4. Regression models
Our base OLS regression modelused to examine the association between
extent of CSR performance and financial distress is estimated as follows:
DISit ¼ a0it þ b1CSRit þ b2SIZE it þ b3LEV it
þ b4CASH it þ b5ROAit þ b6R&Dit þ b7QUICK it
þ b8LOSSit þ b918 IND it þ b1924 YEAR i þ eit
ð1Þ
where i= firms 1–93;t = financialyears 2007–2013;DIS = financialdistress
(proxied by AC_Dis,BOS_Dis and AltmanZ);CSR = eitherPOS_CSR or
NEG_CSR; SIZE = the naturallogarithm of totalassets;LEV = short-term
and long-term debt divided by total assets; CASH = cash holdings by the firm
defined as cash and marketable securities scaled by total assets; ROA = retur
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A. Al-Hadi et al./Accounting and Finance 11

on assets;R&D = R&D expenditure divided by totalassets;QUICK = cash
plus receivables/current liabilities; LOSS = Dummy variable scored as 1 if thefirm is a loss making firm in a given year;IND = industry sectordummy
variable,coded 1 if the firm is represented in the particular GICS category,
otherwise 0;YEAR = year dummy variable,coded 1 for a particular year,
otherwise 0 and e = the error term.
Our extended OLS regression modelused to investigate the association
between financialdistress,CSR performanceand firm life cyclestagesis
estimated as follows:
DISit ¼ a0it þ b1CSRit þ b2Life Cycleit þ b3CSRit Life Cycle
þ b4SIZE it þ b5LEV it þ b6CASH it þ b7ROAit
þ b8RDINT it þ b9QUICK it þ b10LOSSit þ b1120 IND it
þ b2126 YEAR i þ eit
ð2Þ
whereLife Cycle = DeAngelo et al.(2006)life cyclemodelmeasured as
retained earnings scaled over total assets (RE/TA) or retained earnings scaled
over total equity (RE/TE); CSR * Life Cycle = an interaction term comprising
the life cycle variable multiplied by CSR.
4. Empirical results
4.1. Summary statistics
Table 2 reports the descriptive statistics for the dependent variable (DIS),
independent variables (POS_CSR, NEG_CSR and LCS) and control variables
(SIZE, LEV, CASH, ROA, QUICK, LOSS). Our financialdistress measures
AC_Dis, BOS_Dis and AltmanZ have a mean (median) of 0.309 (0.331), 0.448
(0.457),and 11.775 (3.015),respectively.POS_CSR has a mean (median) of
0.229 (0.171), and NEG_CSR has a mean (median) of 0.184 (0.118). The mean
(median) of our measures of life cycle stages represented by RE/TA and RE/TE
are 0.086 (0.134) and 0.124 (0.261), respectively. Finally, an acceptable range
variation is observed forall variables,and there is a reasonable levelof
consistency between the means and medians,reflecting normality of distribu-
tions.
4.2. Regression results
Table 3 reportsthe regression resultsof the association between CSR
performance and financial distress over the 2007–2013 period. Higher values
our financial distress proxies represent lower levels of distress. In Panel A, wefind that the regression coefficient for positive CSR activities (POS_CSR) is
positive for all measures of financial distress (AC_Dis, BOS_Dis and AltmanZ)
© 2017 AFAANZ
12 A. Al-Hadi et al./Accounting and Finance

and statistically significant (p < 0.05 or better). Further, we find the regression
coefficientfor NEG_CSR is non-significantfor AC_Dis, BOS_Dis and
AltmanZ_Dis.These results provide supportfor H1. Our results show that
extent of positive CSR activity is positively associated with our measures offinancialdistress.Thus, firms that engage in more extensive positive CSR
activities are able to reduce their levelof financialdistress.Our regression
estimates are also economically significant.For example,in Model (1), one
standard deviation increase in positive CSR (POS_CSR) is associated with 1.46
percentdecrease in financialdistress.We also find that some of the control
variables are significantly associated with financialdistress.Specifically,the
regression coefficient for LEV is negative for AC_Dis, BOS_Dis and AltmanZ
and statistically significant(p < 0.05 orbetter).Moreover, the regression
coefficientfor SIZE is negative forAC_Dis, BOS_Dis, and AltmanZ and
statistically significant (p < 0.01).Larger firms are less likely to be subject tofinancial distress as they enjoy superior economic and political power relative
to smaller firms.The regression coefficient for CASH is negative for AC_Dis
and BOS_Dis and statistically significant (p < 0.01). The regression coefficient
for ROA is negative for AltmanZ and statistically significant (p < 0.10).The
regression coefficientfor QUICK is negative(positive)for AC_Dis and
BOS_Dis (AltmanZ)and statistically significant(p < 0.10 orbetter).The
regression coefficient for R&D is negative (positive) for AltmanZ (AC_Dis and
BOS_Dis) and statistically significant(p < 0.10 orbetter).We then find
consistenteffectsof CSR on financial distressusing a totalscore of CSR
performance items (see Table 3,PanelB). We find that naturallogarithm of
total CSR (i.e. sum of both positive and negativeCSR performance)
Table 2
Descriptive statistics
Variable N Mean SD 0.25 Median 0.75
AC_Dis 651 0.309 0.140 0.204 0.331 0.426
BOS_Dis 651 0.448 0.175 0.330 0.457 0.554
AltmanZ 651 11.775 35.960 2.022 3.015 5.723
POS_CSR 651 0.229 0.236 0.045 0.171 0.333
NEG_CSR 651 0.184 0.196 0.090 0.118 0.248
RE/TA 651 0.086 0.438 0.031 0.134 0.236
RE/TE 651 0.124 1.912 0.064 0.261 0.463
SIZE 651 7.013 1.785 5.808 6.858 8.397
LEV 651 0.178 0.155 0.035 0.162 0.271
CASH 651 0.138 0.170 0.033 0.067 0.169
ROA 651 6.885 9.168 3.280 6.400 10.10
R&D 651 0.004 0.018 0.000 0.000 0.000
QUICK 651 2.538 5.794 0.682 1.070 1.610
LOSS 651 0.143 0.350 0.000 0.000 0.000
© 2017 AFAANZ
A. Al-Hadi et al./Accounting and Finance 13

Table 3
Regression results
Panel A: Financial distress and corporate social responsibility performance
BOS_Dis AltmanZ AC_Dis BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
POS_CSR 0.0619** 14.8984*** 0.0667** – – –
(2.12) (3.79) (2.39) – – –
NEG_CSR – – – 0.0463 22.6094 0.0473
– – – (1.54) (1.58) (1.55)
SIZE 0.0121*** 7.3054*** 0.0121*** 0.0100*** 0.3604 0.0100***
(3.62) (5.21) (3.62) (3.12) (0.16) (3.10)
LEV 0.1834*** 16.0658*** 0.1817*** 0.1871*** 44.9548** 0.1871***
(4.81) (2.81) (4.79) (4.93) (2.28) (4.92)
CASH 0.3960*** 2.0948 0.6061*** 0.4014*** 95.4599 0.6050***
(13.12) (0.12) (20.14) (13.30) (0.99) (20.13)
ROA 0.0005 0.8013** 0.0005 0.0005 3.4459* 0.0004
(1.06) (2.53) (1.01) (1.07) (1.81) (0.89)
R&D 0.8577***65.8381* 0.8615*** 0.8830*** 144.3646 0.8835***
(3.88) (1.84) (3.91) (3.82) (0.91) (3.82)
QUICK 0.0017** 2.7309*** 0.0016* 0.0016** 2.9534* 0.0016*
(2.06) (3.51) (1.92) (1.98) (1.80) (1.90)
LOSS 0.0030 1.7065 0.0038 0.0007 0.9671 0.0001
(0.20) (0.37) (0.26) (0.05) (0.10) (0.01)
Constant 0.3851*** 52.4863*** 0.3836*** 0.3769*** 18.4215 0.3769***
(14.62) (4.85) (14.60) (14.09) (0.95) (14.05)
YEAR FE YES YES YES YES YES YES
IND FE YES YES YES YES YES YES
N 651 651 651 651 645 651
Adj. R 2 0.3730 0.4982 0.6051 0.3695 0.2548 0.6019
Panel B: Financial distress and total corporate social responsibility performance
BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3
Total_CSR 0.0635 0.0004*** 0.0720*
(1.45) (4.52) (1.74)
SIZE 0.0349*** 0.0370*** 0.0350***
(12.25) (12.33) (12.22)
LEV 0.0132 0.0183 0.0117
(0.43) (0.65) (0.38)
CASH 0.0099 0.0142 0.0588*
(0.31) (0.57) (1.75)
ROA 0.0001 0.0004 0.0001
(0.21) (1.30) (0.20)
R&D 0.5441*** 0.6224*** 0.5353***
(4.24) (5.24) (4.23)
QUICK 0.0001 0.0011 0.0001
(continued)
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14 A. Al-Hadi et al./Accounting and Finance

(Total_CSR) is significantlypositivelyassociatedwith financial distress
(AltmanZ and AC_Dis) with p < 0.10 or better. Overall, our results show that
only positive indicatorsof CSR performance contribute to a reduction infinancial distress, supporting H1.
We also report our results regardingthe associationbetweenCSR
performance,firm life cycle stages and financialdistress over the 2007–2013
period in Table 4. This Table shows that the regression coefficient for RE/TA
is positive for AC_Dis and BOS_Dis and statistically significant(p < 0.01).
Our findings are largely consistentwith the argumentthat firms with high
RE/TA are generally mature or older firms with sufficientlevels ofcapital,
investmentsand assetsand are thus less likely to be subjectto financial
distress. The regression coefficient of the interaction term between POS_CSR
and RE/TA (i.e.POS_CSR * RE/TA) is positive and significant (p < 0.05 or
better)for AC_Dis, BOS_Dis and AltmanZ. Firms with positive CSR
performance combined with maturity in life cycle stages are subject to lower
levelsof financialdistress.Similarly, we find that POS_CSR*RE/TE is
positivefor AC_Dis, BOS_Dis and AltmanZ and statisticallysignificant
(p < 0.01),providing further supportfor H2. This finding suggests thatthe
effectof positiveCSR performancein reducing financialdistressis more
pronounced for firms with high RE/TA or RE/TE.We also find that several
of our control variablesare significantly associated with ourmeasuresoffinancialdistress(p < 0.10 orbetter)such as SIZE, LEV, CASH, ROA,
QUICK, R&D and LOSS. These results again show thatlife cycle stage in
combination with the extent of positive CSR activity impacts firms’financial
distress.
Table 3 (continued)
Panel B: Financial distress and total corporate social responsibility performance
BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3
(0.14) (1.61) (0.15)
LOSS 0.0049 0.0053 0.0050
(0.36) (0.40) (0.36)
Constant 0.2203*** 0.2166*** 0.2233***
(8.58) (9.26) (8.70)
YEAR FE YES YES YES
IND FE YES YES YES
N 651 651 651
Adj. R 2 0.3274 0.3316 0.3284
Higher values of our financial distress proxies represent lower levels of distress. *, **, and ***
denote significance at 1, 5 and 10 percent, respectively (Two-tail). The variable definitions ar
in Appendix I. Robust t-statistic are in brackets.
© 2017 AFAANZ
A. Al-Hadi et al./Accounting and Finance 15

4.3. Robustness checks
We re-run our results using an alternative measure of positive CSR activity.
Using the positive CSR performance as a proportion of total CSR performance
(75), we find (see Table 5) consistent evidence that positive CSR performance
significantly associated (p < 0.10 orbetter)with reduced financialdistress
(AC_Dis and AltmanZ). This provides continued support for H1.
Additionally, we divide CSR performance into five subgroups: environment
(EN), social (SO), labour (LA), consumer practices (PR), and human resources
(HR) and testthe association between each ofthe subgroups and financial
Table 4
CSR performance, firm life cycle and financial distress
BOS_Dis AltmanZ AC_Dis BOS_Dis AltmanZ AC_Dis
POS_CSR 0.0099 3.3644 0.0192 0.0204 3.3547 0.0296
(0.37) (0.68) (0.75) (0.65) (0.62) (1.00)
RE/TA 0.0397***30.1658*** 0.0402***
(3.60) (3.28) (3.71)
POS_CSR
* RE/TA
0.3760*** 45.9861** 0.3473***
(6.45) (2.50) (6.64)
RE/TE 0.0196** 7.7601*** 0.0170**
(2.36) (3.12) (2.20)
POS_CSR
*RE/TE
0.1197*** 34.4772*** 0.1067***
(3.32) (3.14) (3.23)
SIZE 0.0178*** 4.7258*** 0.0177*** 0.0107*** 6.6834*** 0.0108***
(5.00) (3.26) (4.98) (3.05) (5.04) (3.12)
LEV 0.1302*** 26.6729*** 0.1308*** 0.1712*** 18.3707*** 0.1694***
(3.44) (4.43) (3.45) (4.40) (3.21) (4.37)
CASH 0.3799*** 19.2752 0.6229*** 0.4071*** 8.5024 0.5969***
(12.02) (1.37) (19.91) (12.60) (0.53) (18.70)
ROA 0.0010* 0.0993 0.0010* 0.0008 0.6380** 0.0007
(1.73) (0.38) (1.76) (1.50) (2.32) (1.38)
R&D 0.6748*** 10.6164 0.6825*** 0.9106***43.1053 0.9070***
(3.04) (0.29) (3.08) (4.06) (1.31) (4.06)
QUICK 0.0016* 3.0146*** 0.0016* 0.0014* 2.8492*** 0.0014
(1.92) (4.11) (1.84) (1.68) (3.70) (1.62)
LOSS 0.0262** 1.2752 0.0258** 0.0057 2.2978 0.0062
(1.97) (0.27) (1.96) (0.42) (0.51) (0.46)
Constant 0.4229*** 38.8507*** 0.4204*** 0.3810*** 51.1977*** 0.3800***
(15.52) (3.69) (15.49) (14.28) (4.93) (14.30)
YEAR FE YES YES YES YES YES YES
IND FE YES YES YES YES YES YES
N 651 651 651 651 651 651
Adj. R 2 0.4218 0.5576 0.6328 0.3914 0.5166 0.6148
The variable definitions are in Appendix I. Robust t-statistic are in brackets. *, **, and ***
denote significance at 1, 5 and 10 percent, respectively (Two-tail).
© 2017 AFAANZ
16 A. Al-Hadi et al./Accounting and Finance

distress. Results are provided in Table 6. We observe that EN, LA and SO are
significantly positively associated with BOS_Dis (p < 0.10 or better); LA, HR,
SO, and PR are significantly positively associated with AltmanZ (p < 0.001)
and EN, LA and SO are significantly positively associated with AC_Dis
(p < 0.10 or better).These results provide continued support for H1 with the
resultsbeing driven particularly by the environmental,social,and labour
subgroups.
To test H2, we employed life cycle modelof DeAngelo et al.(2006)to
examine whether association between CSR performance and financial distress
is augmented when we interact our life cycle proxy measure with the positive
CSR performance(Panel A). As a robustnesscheck of our model that
examines life cycle stages results,we follow Owen and Yawson (2010)and
Table 5
Robustness check: Use of alternative CSR performance
BOS_Dis AltmanZ AC_Dis BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
POS_CSR 0.0892 28.1267*** 0.1002*
(1.48) (3.92) (1.76)
NEG_CSR 0.0712 31.3339 0.0718
(1.21) (1.39) (1.23)
SIZE 0.0108*** 7.2327*** 0.0108*** 0.0093*** 0.0229 0.0093***
(3.20) (5.17) (3.22) (2.96) (0.01) (2.95)
LEV 0.1834*** 15.7704*** 0.1815*** 0.1868*** 45.4585** 0.1870***
(4.81) (2.77) (4.78) (4.93) (2.30) (4.92)
CASH 0.3978*** 2.2720 0.6043*** 0.4016*** 96.2020 0.6048***
(13.17) (0.13) (20.07) (13.29) (0.99) (20.10)
ROA 0.0005 0.8024** 0.0005 0.0005 3.4448* 0.0004
(1.05) (2.53) (0.99) (1.06) (1.81) (0.89)
R&D 0.8831***63.8818* 0.8864*** 0.8974*** 138.2368 0.8979***
(3.94) (1.79) (3.97) (3.90) (0.87) (3.90)
QUICK 0.0017** 2.7332*** 0.0016* 0.0016** 2.9528* 0.0016*
(2.03) (3.51) (1.90) (1.98) (1.79) (1.89)
LOSS 0.0022 1.6075 0.0030 0.0009 0.9314 0.0001
(0.15) (0.35) (0.21) (0.06) (0.10) (0.01)
Constant 0.3805*** 52.7391*** 0.3795*** 0.3743*** 19.6507 0.3743***
(14.26) (4.82) (14.26) (14.01) (1.00) (14.01)
YEAR FE YES YES YES YES YES YES
IND FE YES YES YES YES YES YES
N 651 651 651 651 645 651
Adj. R 2 0.3704 0.4983 0.6034 0.3686 0.2542 0.6014
POS_CSR is the positive CSR as a proportion of total CSR performance and NEG_CSR is
the negative CSR as a proportion of total CSR performance. The variable definitions are in
Appendix I. Robust t-statistics are in brackets. *, **, and *** denote significance at 1, 5 and
10 percent, respectively (Two-tail).
© 2017 AFAANZ
A. Al-Hadi et al./Accounting and Finance 17

Table 6
CSR categories and financial distress
BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 1 Model 2 Model 3 Model 4 Model 5 Model 1 Model 2 Model 3 Model 4 Model 5
EN 0.0205*** 1.3453 0.0209***
(4.17) (1.17) (4.28)
LA 0.0113** 3.1393** 0.0121**
(2.02) (2.45) (2.18)
HR 0.0066 4.1048*** 0.0071
(1.12) (3.05) (1.21)
SO 0.0099* 3.8256*** 0.0104*
(1.81) (3.05) (1.90)
PR 0.0001 2.3494* 0.0008
(0.02) (1.69) (0.13)
SIZE 0.0128*** 0.0100*** 0.0087** 0.0101*** 0.0073** 6.5037*** 6.8793*** 6.9984*** 7.1982*** 6.6183*** 0.0125*** 0.0098*** 0.0084** 0.0098*** 0.0071**
(3.79) (2.93) (2.57) (2.88) (2.16) (8.25) (8.78) (9.04) (8.99) (8.51) ( 3.73) (2.88) (2.50) (2.82) (2.11)
LEV 0.1960*** 0.1851*** 0.1843*** 0.1843*** 0.1873*** 17.5106** 16.3487** 15.1485* 15.8077** 15.9227** 0.1948*** 0.1835*** 0.1827*** 0.1827*** 0.1854***
(5.69) (5.33) (5.28) (5.30) (5.36) (2.18) (2.05) (1.90) (1.98) (1.99) (5.69) (5.32) (5.27) (5.28) (5.34)
CASH 0.3959*** 0.3920*** 0.4024*** 0.4004*** 0.4028*** 2.3861 0.1410 2.6012 1.9272 2.4898 0.6059*** 0.6104*** 0.5993*** 0.6014*** 0.5990***
(10.67) (10.36) (10.72) (10.68) (10.71) (0.28) (0.02) (0.30) (0.22) (0.29) (16.44) (16.24) (16.06) (16.14) (16.03)
ROA 0.0005 0.0005 0.0005 0.0005 0.0005 0.8017*** 0.8010*** 0.8105*** 0.8120*** 0.7935*** 0.0005 0.0005 0.0005 0.0004 0.0005
(0.92) (0.92) (0.89) (0.87) (0.92) (6.39) (6.41) (6.50) (6.51) (6.33) (0.87) (0.87) (0.84) (0.82) (0.87)
R&D 0.7810** 0.9127*** 0.9331*** 0.9109*** 0.9440*** 58.4613 56.1513 53.7419 60.0650 74.6837 0.7879*** 0.9208*** 0.9426*** 0.9196*** 0.9437***
(2.57) (2.99) (3.05) (2.98) (3.01) (0.83) (0.80) (0.77) (0.86) (1.04) (2.61) (3.04) (3.10) (3.03) (3.03)
QUICK 0.0018* 0.0016 0.0016 0.0016 0.0016 2.7195*** 2.7294*** 2.7141*** 2.7493*** 2.7054*** 0.0017* 0.0016 0.0016 0.0015 0.0016
(1.72) (1.53) (1.55) (1.48) (1.52) (11.13) (11.22) (11.18) (11.32) (11.07) (1.67) (1.48) (1.50) (1.43) (1.47)
LOSS 0.0029 0.0035 0.0017 0.0021 0.0011 0.9424 1.8668 1.5833 1.5914 1.2673 0.0024 0.0043 0.0024 0.0028 0.0017
(0.21) (0.24) (0.12) (0.15) (0.08) (0.28) (0.56) (0.48) (0.48) (0.38) (0.17) (0.30) (0.16) (0.19) (0.12)
Constant 0.3757*** 0.3634*** 0.3706*** 0.3729*** 0.3626*** 47.7695*** 47.1090*** 51.8601*** 50.8456*** 49.7208*** 0.3727*** 0.3602*** 0.3680*** 0.3701*** 0.3604***
(13.82) (13.31) (13.11) (13.37) (12.80) (7.54) (7.51) (8.03) (7.97) (7.65) (13.80) (13.28) (13.10) (13.36) (12.80)
YEAR
FE
YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES
IND FE YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES
N 652 652 652 652 652 652 652 652 652 652 652 652 652 652 652
Adj. R 2 0.3864 0.3734 0.3706 0.3726 0.3694 0.4934 0.4971 0.4997 0.4997 0.4946 0.6124 0.6040 0.6020 0.6033 0.6010
*, **, and *** denote significance at 1, 5 and 10 percent, respectively (Two-tail). The variable definitions are in Appendix I.
© 2017 AFAANZ
18 A. Al-Hadi et al./Accounting and Finance

modify the life cycle measure ofDeAngelo et al.(2006)by partitioning the
sampleinto three life cycle stages.Specifically,young firms are those
belonging to the cohort with the lowest one-third of RE/TA values,maturefirms are those belonging to the cohort with the middle one-third of RE/TA
values,and old firms those belonging to the cohortwith the top RE/TA
values.Resultsare provided in Table 7 (PanelA). This Panel showsthat
coefficient for POS_CSR is positive and significant for mature and old firms,
implying that positive CSR performance reduces financialdistress for mature
and old firms.
In Panel B, we repeat the analysis for RE/TE measure of firm life cycle and
obtain qualitativelysimilar results. Overall, positive CSR performance
reduces financialdistress,which is further more pronounced for mature and
old firms.
4.4. Instrumental variables (2SLS) regression analysis
It is possible thatour baseline regression results(see Table 3)could be
affected by endogeneity (e.g. simultaneity and/or reverse causality) arising frofirms’ engagementin various CSR activities leading to biased regression
coefficient estimates. We thus use an instrumental variable technique to furth
validate the interpretation of the result. The advantage of this technique is tha
it addresses reverse causality as well as omitted variable bias in the OLS at the
same time (Wooldridge,2010).To do so, we run a 2SLS modelthat uses
instruments for the endogenous variable, CSR performance. In the spirit of Cui
et al.(2016),we use industry mean POS_CSR performance as an instrument
(Industry Mean CSR) for POS_CSR. We use this instrument because firm-level
CSR is likely to vary considerably across industries owing to the nature of the
products produced,regulatory environment,shifts in socialnorms (Waddock
and Graves,1997;McWilliams and Siegel,2001).Therefore,we expect firm-
level CSR to be closely related to its industry norm, as captured by the industr
mean CSR. Thus, we expect industry mean CSR to be correlated with firm-leve
CSR but uncorrelated with financial distress.
For the instrument to be valid, it should also be uncorrelated with the error
terms. This essentially means that the instruments should (i) not be affected b
the dependent variable, (ii) not affect the dependent variable except through t
endogenous variables and (iii) not be correlated with omitted variables in the
model.
The results of the instrumentalvariable technique are reported in Table 8.
The positive and significant association between positive CSR performance anfinancialdistress remains robust even after accounting for endogeneity.This
suggests that endogeneity cannot account for the positive association betwee
POS_CSR and financial distress.
Our instrumentsalso passthe statisticaltestsfor strength,validity and
appropriateness.Results reported in Table 8 show that our instrument
© 2017 AFAANZ
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Table 7
Corporate social responsibility, corporate life cycle and financial distress: Alternative life cycle classification
Panel A
BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
Young Mature Old Young Mature Old Young Mature Old
POS_CSR 0.1158* 0.1177*** 0.1495*** 52.9249 3.2941* 7.1936* 0.0956* 0.1177*** 0.1523***
(1.92) (3.81) (4.18) (1.30) (1.79) (1.67) (1.67) (3.81) (4.21)
SIZE 0.0156** 0.0261*** 0.0108 23.7009** 2.9460* 2.3051* 0.0156** 0.0260*** 0.0108
(2.40) (4.24) (1.50) (2.47) (1.85) (1.82) (2.45) (4.24) (1.49)
LEV 0.0444 0.1129* 0.2113** 21.2399 5.7350* 26.3139*** 0.0388 0.1128* 0.2152**
(0.68) (1.69) (2.42) (0.38) (1.79) (3.04) (0.61) (1.69) (2.44)
CASH 0.4441*** 0.1474** 0.4938*** 122.6703 13.2255 19.0998 0.5613*** 0.8528*** 0.5010***
(7.89) (2.05) (9.21) (0.52) (1.24) (1.40) (10.04) (11.84) (9.25)
ROA 0.0011 0.0031** 0.0005 6.2106* 0.0866 0.3200 0.0009 0.0031** 0.0006
(1.44) (2.21) (0.47) (1.89) (0.32) (1.27) (1.30) (2.22) (0.52)
R&D 7.1719*** 2.6039** 0.2763 4234.9080** 324.1456 14.4915 7.1928*** 2.6054** 0.2970
(5.07) (2.30) (0.84) (2.02) (1.53) (0.38) (5.16) (2.30) (0.90)
QUICK 0.0009 0.0278*** 0.0005 1.7262 0.8828 0.9179 0.0009 0.0278*** 0.0010
(0.85) (3.75) (0.32) (0.61) (0.65) (1.46) (0.85) (3.75) (0.59)
LOSS 0.0225 0.0047 0.0487* 3.0832 0.6915 0.6353 0.0226 0.0047 0.0495**
(1.14) (0.21) (1.98) (0.15) (0.39) (0.16) (1.18) (0.21) (2.01)
Constant 0.3344*** 0.5215*** 0.4377*** 192.1061** 20.7805* 31.7601** 0.3288*** 0.5216*** 0.4384***
(6.98) (11.32) (8.20) (2.35) (1.69) (2.52) (6.97) (11.32) (8.21)
YEAR FE YES YES YES YES YES YES YES YES YES
IND FE YES YES YES YES YES YES YES YES YES
N 160 328 163 160 328 163 160 328 163
Adj. R 2 0.6267 0.3020 0.5081 0.3067 0.2415 0.2872 0.8386 0.4558 0.6158
(continued)
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20 A. Al-Hadi et al./Accounting and Finance

Table 7 (continued)
Panel B
BOS_Dis AltmanZ AC_Dis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
Young Mature Old Young Mature Old Young Mature Old
POS_CSR 0.4194*** 0.1793*** 0.1745 65.8668 7.8234* 8.1063 0.3634*** 0.1792*** 0.1800*
(4.46) (2.79) (1.53) (0.68) (1.92) (1.07) (4.09) (3.87) (1.98)
SIZE 0.0149** 0.0226*** 0.0031 22.1393** 2.9392* 2.0977* 0.0148** 0.0226*** 0.0030
(2.59) (3.71) (0.43) (2.34) (1.85) (1.84) (2.61) (3.74) (0.43)
LEV 0.0427 0.1286** 0.2138*** 19.0820 6.0900* 11.5691** 0.0370 0.1285* 0.2180**
(0.66) (2.15) (2.70) (0.34) (1.89) (2.30) (0.59) (1.91) (2.52)
CASH 0.4528*** 0.1763** 0.5170*** 120.1297 12.7730 20.6449 0.5532*** 0.8239*** 0.4774***
(8.02) (2.14) (8.07) (0.51) (1.22) (1.43) (9.83) (11.55) (8.55)
ROA 0.0009 0.0030** 0.0006 6.2206* 0.0927 0.2570 0.0008 0.0030** 0.0006
(1.15) (2.21) (0.49) (1.88) (0.34) (0.96) (1.03) (2.23) (0.59)
R&D 7.0935*** 2.3525 0.0799 4469.5660** 311.0947 63.4351 7.1555*** 2.3543* 0.0960
(5.27) (1.42) (0.14) (2.13) (1.45) (1.65) (5.41) (1.92) (0.30)
QUICK 0.0007 0.0279*** 0.0005 1.7672 0.9024 1.3133* 0.0007 0.0279*** 0.0010
(0.70) (3.09) (0.21) (0.63) (0.68) (1.82) (0.70) (3.76) (0.55)
LOSS 0.0344* 0.0059 0.0294 1.7830 0.7329 0.8034 0.0330* 0.0060 0.0300
(1.84) (0.24) (0.63) (0.08) (0.41) (0.27) (1.79) (0.26) (1.12)
Constant 0.3200*** 0.5174*** 0.4026*** 188.9151** 21.1298* 21.1062** 0.3156*** 0.5174*** 0.4030***
(6.84) (10.49) (7.10) (2.32) (1.71) (2.17) (6.84) (10.83) (7.13)
YEAR FE YES YES YES YES YES YES YES YES YES
IND FE YES YES YES YES YES YES YES YES YES
N 160 329 163 160 329 163 160 329 163
Adj. R 2 0.6492 0.2994 0.4847 0.3051 0.2518 0.2441 0.8468 0.4515 0.5972
*, **, and *** denote significance at 1, 5 and 10 percent, respectively (Two-tail). The variable definitions are in Appendix I. Robust t-statistics
in brackets.
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A. Al-Hadi et al./Accounting and Finance 21

Table 8
Endogeneity test using two-stage least square regression
Model 1: BOS_Dis Model 2: AltmanZ Model 3: AC_Dis
1st Stage 2nd Stage 1st Stage 2nd Stage 1st Stage 2nd Stage
Intercept 0.3539*** 0.6952*** 0.3539*** 64.488*** 0.3539*** 0.6952***
(8.99) (9.87) (8.99) (4.79) (8.99) (9.87)
POS_CSR 1.059*** 52.302** 1.060***
(5.54) (2.42) (5.54)
All variables in Main Specification Yes Yes Yes Yes Yes Yes
Year & Industry Dummies Yes Yes Yes Yes Yes Yes
Robust Yes Yes Yes Yes Yes Yes
N
Instrumental Variables Coff. (t-statistic) Coff. (t-statistic) Coff. (t-statistic)
Industry Mean CSR 0.5807 0.5807 0.5807
(6.03) (6.03) (6.03)
Post-estimations Test for Instrumental Variables
Predictive power partial R2
Robust F-test 37.27 37.27 37.27
p-value 0.000 0.000 0.000
Underidentification test
Kleibergen -paap rk LM statistic 29.712 29.712 29.712
p-value 0.000 0.000 0.000
Endogeneity test
Durbin-Wu-Hausman tests 73.328 3.538 73.328
Chi-sq(1) p-value 0.000 0.06 0.000
*, **, and *** denote significance at 1, 5 and 10 percent, respectively (Two-tail). The variable definitions are in Appendix I.
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22 A. Al-Hadi et al./Accounting and Finance

(Industry Mean CSR)is significantly positively correlated with endogenous
variable (POS_CSR). A commonly used test for the strength of the instruments
is the F-test that jointly tests the significance of the instruments. The F-statisti
acrossthe three modelsis 37.27 which is well above the recommended
minimum of 10. This number suggests that our instrument is strong. The null
hypothesis that CSR performance is exogenous is rejected at a p < 0.000.
5. Conclusion
This paper examines the association between CSR performance and financia
distress,and the moderating role oflife cycle progression in explaining this
association. Based on a sample of publicly-listed Australian firms covering the
2007–2013 period, our regression results show that positive CSR performance
significantly reduces financialdistress ofthe firm.In addition, the negative
association between positive CSR activities and financialdistress is magnified
for firms in mature stage of life cycle.Mature stage firms with positive CSR
performance are associated with reduced levels of financial distress. Our resul
are robust to an alternative proxy measure of positive CSR activity,and life
cycle stages.Our findingsextend the literature on the driversof financial
distress specifically and the economic consequences ofengaging in positive
CSR activity.
Our resultssupportthe conjecture thatfirms engaging in positive CSR
activities do so to support their financialactivities.In particular,we provide
evidence for the firsttime thatthe interaction between both positive CSR
performance and life cycle progression is empirically associated with financial
distress.These results have important implications for firm management and
otherstakeholders given thatfirms’accessto resources,and the ability to
compete with theirpeerswill vary acrosslife cycle stages.Similarly firms’
susceptibility to financialdistress can also vary systematically across different
life cycle stages.Firms that engage in positive CSR activities are likely to be
able to reduce the risk of financial distress at the more susceptible stages of li
cycle progression.Firm managementcould develop strategic approaches to
their engagement with CSR activities based on both the resourcing capacity of
the firm, contingent upon its life cycle progression, and its exposure to financi
distress. Our findings are likely to be value relevant to investors in particular in
assessing risk premiums relating to future cash flows and the cost of capital,
and in determining the likelihood thata firm will be exposed to financial
distress.
This study is subjectto severallimitations.First, the sample is based on
publicly-listed Australian firms.Owing to data unavailability,it was not
possible to include unlisted firmsin our sample.Second,financialdistress
occurs in differentstages and we are unable to relate CSR activity to the
different stages of financial distress.
© 2017 AFAANZ
A. Al-Hadi et al./Accounting and Finance 23

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Appendix I. Variable definitions and measurement
Variables Definition and measurement
Dependent variable
BOS_Dis Financial distress model of Berger, Ofek and Swary (1996) calculated as
(0.715* Receivable + 0.547 * Inventory + 0.535 * Net PPE)/Total Assets)
AltmanZ Altman (1968) predicting bankruptcy as a financial distress measures calculated
as: (1.2 * Working Capital/Total Assets.+ 1.4 * Retained Earnings/Total
Assets + 3.3 * Earnings Before Interest and Taxes/Total
Assets + 0.6 * Market Value of Equity/Book Value of Total
Liabilities + 0.99 * Sales/Total Assets)
AC_Dis Financial distress model of Almeida and Campello (2007) calculated as ((Cash +
0.715 * Receivable + 0.547 * Inventory + 0.535 * Net PPE)/Total Assets)
Independent variables
POS_CSR Natural log of the number of positive CSR items reported in the annual
report in a given year
NEG_CSR Natural log of the number negative CSR items disclosed in the annual report
in a given year
TOTAL_CSR Natural log of the sum of positive and negative CSR items disclosed in the
annual report in a given year
RE/TA Retain Earning/Total Assets, a proxy for corporate life cycle
RE/TE Retain Earning/Total Equity, a proxy for corporate life cycle
SIZE Natural log of the firms’ total assets at the beginning of year
LEV Leverage, measured as long-term debt (and short-term debt) scaled by total
assets
CASH Cash holding for firm, defined as cash and marketable securities scaled by
total assets
ROA Profitability of the firm, measured as operating income scaled by total assets
QUICK The quick ratio, calculated as (cash + receivable/current liability).
R&D
(continued)
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26 A. Al-Hadi et al./Accounting and Finance

Table (continued)
Variables Definition and measurement
Research and development expense ratio, measured as research and development
expense scaled by lagged assets. Missing values for research and development
expense are set to zero
LOSS Dummy variable that takes a value of 1 if net income is negative in a given
year, 0 otherwise
YEAR Dummy variables to control for year effects
IND Dummy variables to control for industry effects
Appendix II. GRI items
Panel A: Positive GRI Index CSR items
Materials used by weight or volume EN1
Percentage (or amount) of materials used that are recycled input materials EN2
Energy saved due to conservation and efficiency improvements EN5
Initiatives to provide energy-efficient or renewable energy based EN6
Reductions in energy requirements of products and services EN7
Percentage and total volume of water recycled and reused EN10
Operational sites owned, leased, managed in, or adjacent to, protected areas and areas of high
biodiversity value outside protected areas EN11
Description of significant impacts of activities, products, and services on biodiversity in protected
areas of high biodiversity value outside protected areas EN12
Habitats protected or restored EN13
Strategies, current action and future plans for managing impacts on biodiversity. EN14
Initiative to reduce of greenhouse gas (GHG) emissions achieved EN18
Total water discharge by quality and destination EN21
Initiatives to mitigate environmental impacts of products and services EN26
Percentage of products sold and their packaging materials that area reclaimed by category EN27
Total environmental protection expenditures and investments by type EN30
Total workforce by employment type, employment contract and region LA1
Total number and rate of new employee hires and employee turnover by age group, gender and
region LA2
Benefits provided to full-time employees that are not provided to temporary or part-time
employees, by significant locations of operation LA3
Return to work and retention rates after parental leave, by gender LA15
Percentage of employees covered by collective bargaining LA4
Minimum notice period(s) regarding operational changes, including whether it is specified in
collective agreements LA5
Percentage (or description) of total workforce represented in formal joint management-worker
health and safety committees that help monitor and advise on occupational health and safety
programs LA6
Health and safety topics covered in formal agreements with trade unions. LA9
Average hours of training per year per employee by gender, and by employee category LA10
(continued)
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A. Al-Hadi et al./Accounting and Finance 27

Table (continued)
Panel A: Positive GRI Index CSR items
Programs for skills management and lifelong learning that support the continued employability of
employees and assist them in managing career endings LA11
Percentage of employees receiving regular performance and career development reviews, by gen
by employee category LA12
Composition of governance bodies and breakdown of employees per employee category according
to gender, age group, minority group membership, and other indicators of diversity LA13
Ratio of basic salary and remuneration of women to men by employee category, by significant
locations of operation LA14
Percentage (or description) and total number of significant investment agreements that include
clauses incorporating human rights concern or that have undergone human rights screening HR1
Percentage and significant suppliers, contractors and other business partners that have undergon
human rights screening and actions taken HR2
Total hours of employee training on policies and procedures concerning aspects of human rights
that are relevant to operations including the percentage of employees trained HR3
Operations and significant suppliers identified in which the right to exercise freedom of associatio
and collective bargaining may be violated or at significant risk, and actions taken to support thes
rights HR5
Percentage of security personnel trained in the organisation’s policies or procedures concerning
aspects of human rights that are relevant to operations HR8
Percentage (or description) of operations with implemented local community engagement, impact
assessments, and development programs S01
Operations with significant potential or actual negative (or positive) impacts on local communities
(Charity donations) S09
Significant actual and potential negative (or positive) impacts on society in the supply chain and
action taken SO10
Percentage of employees trained in organisation’s anti-corruption policies and procedures S03
Actions taken in response to incidents of corruption SO4
Public policy positions and participation in public policy development and lobbying SO5
Total value of political contributions by countries and recipient/beneficiary SO6
Type of product and service information required by procedures, and percentage of significant
products and services subject to such information requirements PR3
Practices relating to customer satisfaction including results of surveys measuring customer
satisfaction PR5
Programs for adherence to laws, standards and voluntary codes related to marketing
communications, including advertising, promotion and sponsorship PR6
Panel B Negative GRI Index CSR items
Energy consumption within the organisation EN3
Energy consumption outside of the organisation EN4
Total water withdrawal by source EN8
Water sources significantly affected by withdrawal of water EN9
Number of IUCN Red list species and national conservation list species with habitats in areas
affected by operations, by level of extinction risk EN15
Total direct and indirect greenhouse gas emission by weight EN16
Other indirect greenhouse gas (GHG) emissions (Scope 3) EN17
28 A. Al-Hadi et al./Accounting and Finance
© 2017 AFAANZ

Panel B Negative GRI Index CSR items
Emissions of ozone-depleting substances by weight EN19
NO, SO, and other significant air emissions EN20
Total weight of waste by type and disposal method EN22
Total number and volume of significant spills EN23
Weight of transported, imported, exported, or treated waste deemed hazardous under the terms o
the Basel Convention Annex 1, II, III and VIII, and percentage of transported waste shipped
internationally EN24
Identity, size, protected status, and biodiversity value of water bodies and related habitats
significantly affected by the reporting organisation’s discharges of water and runoff EN25
Monetary value of significant fines and total number of non-monetary sanctions for non-
compliance (or statement of compliance) with environmental laws and regulations EN28
Significant environmental impacts of transportation of products and other goods and materials
used for the organisation’s operations, and transporting members of the workforce EN29
Type of injury and rates of injury, occupational diseases, lost days, and absenteeism, and total
number of work-related fatalities, by region and by gender LA7
Workers with high incidence or high risk of diseases related to their occupation LA8
Total number of incidents of discrimination and corrective actions taken HR4
Operations and significant suppliers identified as having significant risk for incidents of child
labour, and measures taken to contribute to the effective abolition of child labour HR6
Operations and significant suppliers identified as having significant risk for incidents of forced or
compulsory labour, and measures to contribute to the elimination of all forms of forced or
compulsory labour HR7
Total number of incidents of violations (or improvements) involving rights of indigenous people
and actions taken HR9
Percentage and total number of operations that have been subject to human rights reviews and/or
impact assessments HR10
Number of grievances related to human rights filed, addressed and resolved through formal
grievance mechanisms HR11
Percentage and total number of business units analysed for risks related to corruption SO2
Total number of legal actions for anti-competitive behaviour, anti-trust, and monopoly practices
and their outcomes SO7
Monetary value of significant fines and total number of non-monetary sanctions for non-complianc
with laws and regulations SO8
Life cycle changes in which health and safety impacts of products and services categories subject
such procedures PR1
Total number of incidents of non-compliance with regulations and voluntary codes concerning
health and safety impacts of products and services during their life cycle, by type of outcomes PR
Total number of incidents of non-compliance with regulations and voluntary codes concerning
product and service information and labelling, by type of outcomes PR4
Total number of incidents of non-compliance with regulations and voluntary codes concerning mar
communications, including advertising, promotion and sponsorship by type of outcomes PR7
Total number of substantiated complaints regarding breaches of customer privacy and losses of
customer data PR8
Monetary value of significant fines for non-compliance (or description of compliance) with laws and
regulations concerning the provision and use of products and services PR9
Table (continued)
© 2017 AFAANZ
A. Al-Hadi et al./Accounting and Finance 29
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