Do CEO demographics explain cash holdings in SMEs?

European Management Journal (2013) xxx, xxx–xxx

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Do CEO demographics explain cash holdings in SMEs?

Raf Orens a, Anne-Mie Reheul b,*

a KU Leuven Faculty of Economics and Business at Antwerp, Korte Nieuwstraat 33, 2000 Antwerpen, Belgiumb Hogeschool-Universiteit Brussel (KU Leuven), Warmoesberg 26, 1000 Brussels, Belgium

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KEYWORDSAgency theory;Cash policy;Financial hierarchytheory;SME;Trade-off theory;Upper Echelons Theory

Summary This study examines the idiosyncratic manager-specific influence on corporatecash holdings. Although traditional economic theories such as trade-off theory, financialhierarchy theory and agency free cash flow theory have already contributed to a deeperunderstanding of corporate cash policy, we examine whether the integration of the UpperEchelons Theory (UET) into these traditional theories provides additional power inexplaining corporate cash holdings. We contend that social, psychological and cognitivecharacteristics of CEOs, proxied by a number of CEO demographics, affect the level ofimportance that CEOs (and shareholders) attach to the economic arguments providedby the traditional theories, in turn affecting cash policy. We test our hypotheses usinga sample of Belgian privately held SMEs. Controlling for the impact of traditional economictheories our findings suggest that older CEOs and CEOs without experience in other indus-tries are more concerned with the precautionary motive of cash and less concerned withthe opportunity cost of cash, giving rise to higher cash levels compared to younger CEOsand CEOs with other-industry experience. This indicates that cash policy in Belgian pri-vately held SMEs reflects the natural tendencies of CEOs. Since cash policy affects share-holder value, it is important for stakeholders to consider the demographics of present ornew CEOs and to understand their associated inclinations concerning cash policy.ª 2013 Elsevier Ltd. All rights reserved.

Introduction

Prior literature documents that firms hold a reasonable pro-portion of their assets as cash and cash equivalents, butshareholders have to be concerned that CEOs retaining ex-cess levels of cash might distort overall shareholder value(Harford, 1999). To explain cross-sectional differences incorporate cash holdings, prior literature focuses on tradi-tional economic theories, such as the trade-off theory(Opler, Pinkowitz, Stulz, & Williamson, 1999), the financial

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ubrussel.be (A.-M. Reheul).

s, R., & Reheul, A.-M., Do CEO6/j.emj.2013.01.003

hierarchy theory (Myers & Majluf, 1984) and the agency(free cash flow) theory, which all assume rational behavior(Jensen, 1986). The former two theories assume that CEOsalways act in the interest of shareholders, suggesting thatagency conflicts between shareholders and managers areabsent (Belghitar & Khan, 2013). The free cash flow theoryhighlights that severe agency conflicts arise in case of largefree cash flows suggesting that CEOs may not act to increaseshareholders� wealth.

The impact of these theories on cash holdings is exten-sively discussed and tested for samples of large listed firms,but knowledge about the determinants of cash holdings inprivate (unlisted) small and medium-sized enterprises

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demographics explain cash holdings in SMEs? European Management

http://dx.doi.org/10.1016/j.emj.2013.01.003

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2 R. Orens, A.-M. Reheul

(SMEs) is scarce, although SMEs represent a large proportionof a country�s GDP. Given this limited knowledge, a firstcontribution of our study is to study cash policy among SMEs.The few empirical studies focusing on cross-sectional differ-ences in cash holdings in private SMEs (e.g. Bigelli & San-chez-Vidal, 2012; Faulkender, 2002; Garcıa-Teruel &Martınez-Solano, 2008; Steijvers & Niskanen, 2012) attri-bute the differences in cash holdings to the same theoriesused for large listed firms, but contend that the importanceof these theories in explaining cash holdings differs betweenlarge listed firms and SMEs due to differences in ownershipstructure or informational uncertainty for instance (Mant-econ, 2008). The present article will also elaborate on this.

A second contribution of our study is to combine insightsfrom Upper Echelons Theory (UET) with the traditional eco-nomic theories to explain cash holdings. An emerging bodyof finance literature considers bounded rationality and asso-ciated behaviors/perceptions of decision makers as attri-butes of financial phenomena like stock returns, tradingactivity and corporate finance (Subrahmanyam, 2007). Thisstream of literature investigates managerial attributes (cog-nitive ability), behaviors (overconfidence) and perceptions(with regard to valuation) and link them to corporate finan-cial decisions related to capital structures and corporateinvestments (Baker & Wurgler, 2002; Malmendier & Tate,2005).

UET argues that decision makers are characterizedby bounded rationality and therefore also make decisionson the basis of their cognitive, social and psychologicalcharacteristics. Organizational processes and decisions thusinclude a behavioral component that reflects the idiosyncra-sies of decision makers (Hambrick & Mason, 1984). Accordingto UET the cognitive, social and psychological characteris-tics of CEOs can be proxied by demographics like tenure,education, background, age and gender (Hambrick, 2007).The extant UET literature relates CEO demographics to var-ious organizational processes and outcomes, such as innova-tion (Kitchell, 1997), R&D spending (Barker & Mueller, 2002),internationalization (Herrmann, 2002), corporate financialdisclosure (Bamber, Jiang, & Wang, 2010), strategy forma-tion (Gibbons & O�Connor, 2005) and firm performance(Weinzimmer, 1997). However, Carpenter, Geletkanycz,and Sanders (2004) made a call in the UET literature to focuson understudied corporate processes. We respond to this callby examining whether CEOs can place their distinctive markson their firms� cash policy. Our study relates to Bertrand andSchoar (2003) who for a sample of large listed firms observean idiosyncratic manager-specific influence on corporatedecisions such as cash holdings.

Based on the combined insights from UET and the tradi-tional economic theories, we investigate whether CEOdemographics (i.e. tenure, age, experience in other indus-tries, experience in the same industry and education) arereflected in corporate cash holdings in a sample of privateSMEs. We conduct this study using a sample of 203 Belgianmanufacturing SMEs. The CEO specific data are collectedby means of a survey. We opt for a setting of SMEs sinceCEOs in these firms are often the sole decision maker andhave to reckon less with the views of other top managementteam (TMT) members, allowing them to decide on cashlevels (Miller, Kets de Vries, & Toulouse, 1982; Van Gils,2005). Consistent with UET, we observe that cash holdings

Please cite this article in press as: Orens, R., & Reheul, A.-M., Do CEO dJournal (2013), http://dx.doi.org/10.1016/j.emj.2013.01.003

are positively associated with CEO age and negatively asso-ciated with CEO other-industry experience. These resultsdemonstrate the idiosyncratic nature of cash holding deci-sions. Dividing our sample in two subsamples, i.e. small pri-vate firms and medium-sized private firms, the regressionresults reveal that UET only explains cash holdings in thesmall firm subgroup, not in the medium-sized firm subgroup.This finding suggests that especially CEOs in small firms pos-sess sufficient discretion to determine cash levels. We attri-bute the lower level of CEO discretion in the medium-sizedfirms to their more efficient governance mechanisms(boards characterized by higher outsider proportion and lessCEO duality) and to the presence of other TMT members andadditional management layers.

The paper proceeds as follows. Theoretical frameworkand hypothesis development presents a literature reviewon the traditional theories of cash holdings and on UET,and combines these theories to derive hypotheses explain-ing cash holdings. Research method elaborates on our re-search design. Empirical results details the findings of thestatistical analyses, and finally, conclusion comprises a dis-cussion of these findings and their relevance.

Theoretical framework and hypothesisdevelopment

Traditional economic theories provide rational economicarguments in (dis)favor of both low and high cash levels.We propose that cash policy also depends on decision mak-ers� perceived or subjective importance attached to thesealternative economic arguments. This argumentation isbased on the principle of bounded rationality, in whichUET is grounded. As the traditional economic theories ex-plain the basic principles of cash holdings, we elaborateon these theories in Traditional theories of cash holdings.In Hypothesis development we integrate insights from UETwith the traditional economic theories to derive hypothe-ses. We also elaborate on the presence of CEO discretionin our dataset, a prerequisite to conduct this study.

Traditional theories of cash holdings

The extant literature relies on a number of traditional eco-nomic theories to explain variations in cash holdings, pri-marily the trade-off theory, the financial hierarchy theoryand the agency theory. First we describe these theories,and second we discuss their relative importance in privateSMEs versus large listed firms, both from a theoretical andan empirical point of view.

The trade-off theory states that the amount of cash re-tained in a firm is based on the trade-off between the ben-efits and the costs of holding cash, indicating that firms setan optimal level of cash. According to Opler et al. (1999),firms are able to receive two major benefits of holding cash.First, cash holdings enable firms to reduce transaction costsof raising funds (All-Najjar & Belghitar, 2011). The liquid as-sets can be used to finance operating activities and invest-ments avoiding the costs of external financing. Second,cash holdings are considered as a buffer against unexpectedevents (Opler et al., 1999). In addition, having certain cashlevels reduces the likelihood of financial distress, especiallyfor those firms with more volatile cash flows (Ferreira &

emographics explain cash holdings in SMEs? European Management


Do CEO demographics explain cash holdings in SMEs? 3

Vilela, 2004). On the other hand, investing in cash also en-tails opportunity costs since cash provides lower returnscompared to productive investments and since potentialtax advantages by holding debt (as a substitute for cash)are lost (Bigelli & Sanchez-Vidal, 2012).

The financial hierarchy theory (or pecking order theory)posits that firms prefer to finance investments with re-sources internally generated before resorting to debt orequity providers, since in the presence of information asym-metry, firms have more difficulties to obtain funds and/orhave higher borrowing costs (Chen, 2008; Myers & Majluf,1984). According to this theory, firms follow a strict patternby first funding their projects relying on retained earnings,followed by debt and equity. If cash flows are sufficient en-ough to cover the investment needs, firms decide to repaytheir debts (All-Najjar & Belghitar, 2011). Hence, the levelof cash reserves changes with the firm�s success and fortuneand by consequence, the financial hierarchy theory con-tends the non-existence of an optimal level of cash (Opleret al., 1999).

The trade-off theory as well as the financial hierarchytheory assume that management always acts in the interestof shareholders indicating that agency conflicts between themanagers and the shareholders are absent. However, in theagency literature the free cash flow theory contends thatlarge free cash flows increase the power of CEOs indicatingpotential agency conflicts between shareholders and man-agers. When the firm has sufficient funds to finance its pro-jects internally, CEOs avoid the monitoring when applyingfor new funds from the financial markets. This may resultin projects that suit managerial interest, but not share-holder interest. Excessive amounts of cash, especially inprofitable firms with low investment opportunities, can bedetrimental to the shareholders if these resources are in-vested in value decreasing projects (Chang & Noorbakhsh,2009; Jensen, 1986; Opler et al., 1999). Shareholders canprevent the risk of managers making value decreasing acqui-sitions by requiring dividend pay, subsequently decreasingcash positions. Managers may avoid the accumulation of ex-cess cash in this circumstance since it attracts the attentionof shareholders resulting in proxy contents and leading tothe increased probability of executive turnover and cashdistributions to shareholders (Faleye, 2004). Besides equityagency conflicts also debt agency conflicts affect cash hold-ings. As shown in Steijvers and Voordeckers (2009) andNiskanen, Niskanen, and Laukkanen (2010), debt agencyconflicts result in more unfavorable lending conditions oreven restricted availability of bank debt increasing the needto maintain higher cash holdings.

These three important theories examining the determi-nants of cash holdings are extensively tested in empiricalstudies focusing on large listed firms. These studies docu-ment the predominant role of the trade-off theory (in termsof transaction costs and precautionary motives) in explain-ing cash holdings (All-Najjar & Belghitar, 2011). This conclu-sion based on archival data is confirmed by a surveyconducted among the CFOs of large listed firms. The surveyresults provide strong support for the trade-off theory,moderate support for the financial hierarchy theory, andlimited support for agency cost explanations (Powell & Ba-ker, 2010). The following paragraphs address whether thedifferences between SMEs and large listed firms influence

Please cite this article in press as: Orens, R., & Reheul, A.-M., Do CEOJournal (2013), http://dx.doi.org/10.1016/j.emj.2013.01.003

the relative importance of these three theories on cashholdings.

Given the specific nature of SMEs, we contend that thetrade-off theory in explaining cash levels might be moreimportant in SMEs compared to large listed firms for numer-ous reasons. Transaction costs are relatively larger in SMEscompared to large listed firms since the latter firms benefitfrom economies of scale (Faulkender, 2002; Mulligan, 1997).In addition, market imperfections such as financial distressare more severe for SMEs (Belghitar & Khan, 2013). The pre-cautionary motive for holding cash is more pronounced inSMEs since they possess fewer non-core assets that couldbe sold when cash is needed, leading to higher cash holdingsin private firms (Bigelli & Sanchez-Vidal, 2012). The oppor-tunity costs of holding excess levels of cash in terms oftax shields from debt or in terms of lower rates of returnare also present in private firms (Bigelli & Sanchez-Vidal,2012). In line with these theoretical considerations, the ex-tant empirical SME research highlights the important role ofthe trade-off theory in explaining cash holdings (which is infact similar to the empirical findings for large listed firms).Garcıa-Teruel and Martınez-Solano (2008) and Bigelli andSanchez-Vidal (2012) provide empirical evidence on the pre-cautionary motive to hold certain cash levels. Their resultsshow that SMEs with a greater degree of cash flow volatilityhold greater amounts of cash to reduce the costs of liquidityconstraints. In a similar vein Faulkender (2002) observesthat SMEs with higher costs of financial distress stockpilemore cash. Concerning the transaction cost motive for hold-ing cash, Faulkender (2002), Steijvers and Niskanen (2012)and Bigelli and Sanchez-Vidal (2012) find that cash holdingsdecline with firm size indicating increased economies ofscale or lower transaction costs for larger SMEs. The studyof Bigelli and Sanchez-Vidal (2012), relating to the opportu-nity cost of holding cash, reveals that, compared to SMEshaving lower effective tax rates, SMEs with higher effectivetax rates hold lower amounts of cash since they benefitmore from tax benefits by holding debt.

Belghitar and Khan (2013) contend that the importanceof the financial hierarchy theory in explaining cash holdingsis also more important in SMEs than in large listed firmssince levels of uncertainty and information asymmetry inSMEs are higher than in large firms. Monitoring is moreexpensive as SMEs tend to disclose less information publiclyand as analyst following is absent (Mantecon, 2008). HenceSMEs might be constrained in getting access to external cap-ital (Bigelli & Sanchez-Vidal, 2012; Faulkender, 2002; Fazz-ari & Petersen, 1993; Whited, 1992). Consequently, in SMEshigh (low) cash levels are more likely to be observed in thecase of high (low) internal cash generation than in largelisted firms. Empirical evidence strongly supports the influ-ence of the financing hierarchy theory in explaining cashholdings in SMEs. Garcıa-Teruel and Martınez-Solano (2008)document a positive association between cash holdingsand cash flow generation which indicates that firms relyon internal financing rather than raising external funds. Big-elli and Sanchez-Vidal (2012) reveal that SMEs hold less cashwhen the cash conversion cycle is shorter and when thefinancial deficit is higher. Finally, Steijvers and Niskanen(2012) find that family firms with a higher likelihood offinancial distress have lower levels of cash because of diffi-culties to meet their payments.




From a theoretical point of view the agency free cashflow theory can play a role in the cash holdings of both largelisted firms and private SMEs. Large listed firms havedispersed ownership structures with a strong distinctionbetween the shareholders and the CEO, giving rise to equityagency conflicts. SMEs have more diverse ownership struc-tures, ranging from concentrated to more dispersed owner-ship, and from overlapping ownership and management (oneowner-manager) to separated ownership and management.Hence the impact of agency costs varies across the variousgroups of SMEs. In the context of SMEs with a single own-er-manager, many studies support the absence of equityagency costs (Ang, Cole, & Lin, 2000; Bigelli & Sanchez-Vidal, 2012), since acts of self-interest are attenuated byloyalty and commitment to the firm as well as by increasedcooperation and communication (Schulze, Lubatkin, & Dino,2003). However, this classical view has been questioned inrecent studies since the sole owner-manager can also takedecisions which are harmful for firm value maximization.Parental altruism can lead to agency costs due to adverseselection problems, for instance by hiring labor force with-out the expected qualifications (Chrisman, Chua, andSharma, 2005) or due to a reduction in the monitoring effec-tiveness (Lubatkin, Schulze, Ling, & Dino, 2005). In the caseof dispersed ownership, majority shareholders (often own-er-managers) can use their concentrated shareholding toexpropriate wealth from minority and/or non-executiveshareholders through excessive compensation, related partytransactions, risk avoidance, etc. (Loderer & Waelchli,2010). In the case of separated ownership and management(i.e. management by an outside CEO), the misalignment ofincentives can give rise to manager-shareholder agency con-flicts (Steijvers & Niskanen, 2012). Debt agency conflicts,i.e. agency conflicts between shareholders/managers andcreditors, are more prevalent in SMEs than in large firmsdue to higher information asymmetry (Berger & Udell,2003). This can result in tighter financial constraints (Bigelli& Sanchez-Vidal, 2012) or increased borrowing costs(Fazzari & Petersen, 1993; Kim, Mauer, & Sherman, 1998;Whited, 1992) in SMEs. Even though close bank-borrowerrelationships can mitigate information asymmetries in SMEs,leading to improved availability of credit or a decline in loanrates (Berger, Klapper, & Udell, 2001; Berger & Udell, 1995;Boot & Thakor, 1994; Petersen & Rajan, 1994), contractterms can also deteriorate (Degryse & Van Cayseele, 2000)because of creation of internal information for the bankand information asymmetry between the banks in themarket (Rajan, 1992; Sharpe, 1990). To our knowledge,few studies in large (listed) firms provide empirical supportfor agency cost explanations of cash holdings (e.g., Kuan,Li, & Chu 2011). The limited role of agency conflicts indetermining cash holdings is also confirmed in a surveyamong CFOs (Powell & Baker, 2010). This could be due tothe lower variation in ownership structures and the lowerimportance of debt agency problems in large listed firms.In SMEs, however, Faulkender (2002), Niskanen andSteijvers (2011) and Steijvers and Niskanen (2012) do finda relation between agency costs and cash holdings. Steijversand Niskanen (2012) reveal that both equity and debtagency conflicts affect the amount of cash the family firmholds. They find that the type of family firm management(descendent vs. founder CEO, and family vs. outside CEO)


has an impact on cash holdings, and that this impact is mod-erated by the ownership structure (high vs. low ownershipdispersion). Further, they reveal that close bank-borrowerrelationships make it easier to obtain bank debt reducingthe need to hold cash. The next empirical studies also re-veal debt agency costs in SMEs. Steijvers and Niskanen(2012), Garcıa-Teruel and Martınez-Solano (2008) and Bigelliand Sanchez-Vidal (2012) observe that firms with more non-cash liquid assets possess less cash. The two latter studiesalso note a negative association between bank debt andlevels of cash. This is evidence of debt agency costs as suchcosts may lead to financial constraints resulting in a moredeterminant role of cash substitutes (e.g. non-cash liquidassets, bank debt) in the amount of cash holdings (Bigelli& Sanchez-Vidal, 2012).

Hypothesis development

Previous SME studies relating CEO characteristics to cashholdings adopted the agency theory perspective (Faulkender,2002; Niskanen and Steijvers, 2011; Steijvers & Niskanen,2012). These studies considered the effect of the level ofCEO ownership, the effect of descendent versus founderCEOs, and the effect of family versus outside CEOs on cashholdings. We adopt a novel approach and consider the effectof CEO demographics (tenure, age, education and experi-ence) on cash holdings, using the insights of both UET andthe trade-off theory. Both theories share some related keyconcepts, which enables their combination. The precaution-ary motive (trade-off theory) can be related to CEOs� riskaversion (UET), the opportunity cost of cash (trade-off the-ory) can be related to CEOs� propensity for change/invest-ment (UET). Where UET makes an explicit link with agencytheory, we combine UET with agency theory as well.

According to UET managerial decision making is to a largeextent the outcome of top managers� cognitive, psychologi-cal and social frames due to bounded rationality, to multipleand conflicting goals, to differing preferences and to varyingaspiration levels (Hambrick & Mason, 1984). Organizationsare a reflection of their top managers (Carpenter et al.,2004). An important concept within UET is CEO discretionor latitude of freedom. CEO discretion is the degree to whichCEOs can put their distinctive cognitive, social and psycho-logical marks on organizational processes and decisions(Hambrick & Finkelstein, 1987). If CEO discretion is lacking,contextual factors rather than executive characteristics willbe reflected in organizational processes/outcomes and noassociation will be found between CEO characteristics andorganizational processes/outcomes. If discretion is present,a CEO is able to affect organizational processes and to con-tribute to a firm�s outcome. CEO discretion is influenced byamongst other environmental conditions (e.g. hostility ver-sus munificence) and organizational factors (e.g. board,ownership) (Hambrick, 2007).

An important prerequisite for conducting this study isthat the CEOs in our dataset have a sufficient level of discre-tion and are able to put their distinctive marks into cash pol-icy. We argue that this is the case. According to Miller et al.(1982) and a large number of subsequent studies CEOs arethe main (and often the sole) decision makers concerningcorporate policies in SMEs, especially in smaller SMEs. In asimilar vein, Van Gils (2005) found for Dutch SMEs that other




members of the TMT and boards of directors only have asecondary role in decision-making, especially in matureSMEs where TMTs and active boards are often absent. Theabsence of active boards implies that potential agencyconflicts between CEOs and shareholders are insufficientlytackled and that disciplining of CEOs by shareholders/direc-tors is weak (also in terms of limiting the cash levels overwhich the CEO has discretion for example) (Belghitar &Khan, 2013; Johannisson & Huse, 2000; Van den Berghe &Carchon, 2002). In Description of the sample it is revealedthat our dataset includes a large number of small andmature SMEs with passive boards, suggesting that CEOdiscretion with regard to cash holdings in our dataset ishigh. In addition, a survey on SME financing conducted in2006 (i.e. the period under study) by the Belgian KnowledgeCenter for SME Financing (BeCeFi, 2006) revealed that Flem-ish SMEs get access to bank lending quite easily. Moreover,the SMEs in our dataset are mature (start-ups have beenexcluded) and operate in the old economy. This implies thatthey are less likely to experience large cash flow volatility,make less risky investments and face fewer challenges toobtain bank finance compared to start-ups and new econ-omy (high tech) firms (Chen, 2008). Given the passiveboards, the accessibility of bank finance, and the lowdegree of hostility for the mature old economy firms inour dataset (Hambrick, 2007) we claim that the CEOs inour dataset experience considerable freedom in cash hold-ing decisions.

We propose in line with UET that CEOs� cognitive, socialand psychological characteristics affect their cash holdingdecisions. The UET stipulates that CEO demographic charac-teristics are adequate proxies to measure the CEO�s under-lying cognitive, psychological and social characteristics(Hambrick, 2007). For the purpose of our study, we considerthe following CEO demographics: CEO tenure, CEO age, CEOexperience in the same industry, CEO experience in otherindustries and CEO education. Based on UET, we posit thatCEO cognitive, social and psychological characteristics,proxied by the CEO demographics, influence corporate cashpolicy by affecting the extent to which CEOs (and sharehold-ers) are concerned with the arguments included in thetraditional economic theories of cash explanations.

CEO ageUsing arguments grounded in UET we expect older CEOs toattach more value to the precautionary and flexibility roleof cash and to grant less value to the opportunity cost ofcash. First, UET reveals that older CEOs are more risk averseand conservative than younger CEOs (Barker & Mueller,2002; Hambrick & Mason, 1984). Consequently, older CEOstend to hold larger levels of cash in order to hedge againstfuture, undesirable events. In addition, risk averse CEOstend to have a higher preference for (safe) internal fundingover (more risky) external funding. Hence, we assume thatolder CEOs are more conservative and more concerned withthe precautionary motive of cash, resulting in higher cashlevels compared to younger CEOs. This expectation is in linewith Bertrand and Schoar (2003) who already evidenced apositive association between CEO age and cash holdingsfor a sample of large firms.

Second, older CEOs have shorter time perspectives. Theshorter career horizon of older CEOs denies them the time


to shape strategic patterns to fit their own personal prefer-ences. Moreover, long-term investments take away fundsfrom current profitability and only deliver pay off in the longterm, which is not at the benefit of older CEOs. Therefore,older CEOs lose interest in long-term investments andopportunities, and will merely focus on the short term (Bar-ker & Mueller, 2002; McClelland & O�Brien, 2011). There-fore, we posit that older CEOs will be less concerned withthe opportunity cost of cash, implying higher cash holdings.Based on these arguments we hypothesize that:

Hypothesis 1. Cash holdings are positively associated witha CEO�s age.

CEO tenureDespite theory development often considering CEO tenureand CEO age as synonymous (Damanpour & Schneider,2006), we discuss both constructs separately. There is someoverlap between the UET propositions for both constructs,but previous studies suggest that tenure effects and age ef-fects are different and should be studied separately (e.g.Barker & Mueller, 2002).

First, based on UET we presume that longer tenured CEOspay less attention to the opportunity cost of holding excesslevels of cash, which may lead them to hold more cash thanshorter tenured CEOs. This presumption is grounded in stud-ies documenting the presence of regular patterns in the lifecycle of CEOs (Hambrick & Fukutomi, 1991; Miller, 1991).New CEOs have to gain knowledge about the organizationand the environment in which the firm operates (Richard,Wu, & Chadwick, 2009), are more likely to consider severalalternatives, have a more external focus, and are moreopen to fresh ideas, change and experimentation than longtenured CEOs (Hambrick, Geletkancyz, & Fredrickson,1993). As short tenured CEOs identify more investmentopportunities we suggest that they will be more aware ofthe opportunity cost of not investing cash in profitable pro-jects. Consequently we expect lower cash levels with short-er tenured CEOs. As tenure increases, CEOs become moreconfident that they will not be replaced and commit to theirearlier strategies hereby refusing to collect and analyzeexternal information and refusing to pursue change (Finkel-stein & Hambrick, 1996; Kor, 2006; Miller & Shamsie, 2001).Due to their risk aversion, inertia and lack of external focuswe posit that long tenured CEOs will be less concerned withthe opportunity cost of cash and more concerned with theprecautionary role of cash.

Second, longer tenured CEOs have more power to influ-ence the selection of board members and to constitute per-sonal relationships with directors compared to shortertenured CEOs (Finkelstein & Hambrick, 1996). Longer ten-ured CEOs also demonstrate more legitimacy in the eyesof internal and external stakeholders, which mitigatesagency conflicts as perceived by directors and shareholders(Miller, 1991). It is thus more likely that such CEOs areallowed to use higher cash levels to their own discretion.Based on these arguments, we posit the followinghypothesis:

Hypothesis 2. Cash holdings are positively associated witha CEO�s tenure.




CEO experienceThe UET contends that managerial decision making isalso affected by the extent to which executives haveother experiences. Herrmann and Datta (2006) arguethat past experiences of executives define how execu-tives interpret issues, how they design their organiza-tions, and how they pursue strategic choices. In ourstudy, we distinguish between CEOs� same-industryexperience and other-industry experience. We expecta relationship between both types of experiences onthe one hand, and a CEOs� concern with the opportunitycost of cash on the other hand.

Concerning same-industry experience prior researchdemonstrated that it increases CEOs� knowledge of markets,competition, regulations, customers and suppliers, whichhelps CEOs identify and assess emerging opportunities anddesign proper strategies (Patzelt, zu Knyphausen-Aufse, &Nikol, 2008). The knowledge advantages of same-industryexperience are found to be particularly strong in industriesat early life cycle stages, as knowledge about these indus-tries is rare and not yet widely documented (Castanias &Helfat, 2001; Patzelt et al., 2008). Besides the increasedknowledge base as a consequence of same-industry experi-ence, prior empirical research also supported the positionthat same-industry experience can cause a routine trap. Anumber of empirical studies have found that same-industryexperience is related to commitment to the status quo(Geletkanycz & Black, 2001; Hambrick et al., 1993). Thisis a drawback when it comes to identifying new investmentopportunities. Given the current study�s old economy set-ting, same-industry experience is equal to experience inthe stable old-economy industry. Therefore, the routinetrap associated with same-industry experience is realisticin this study. Given the two opposing views concerningsame-industry experience – the higher knowledge basehypothesis and the routine-trap hypothesis – our hypothesisis non-directional:

Hypothesis 3. Cash holdings are associated with a CEO�sexperience in the same industry.

Other-industry experience allows CEOs to consider is-sues from different perspectives (Koellinger, 2008). CEOswith experience in outside industries possess broadermodes of thinking and operating compared to CEOs whohave spent their career in the same industry (Raskas &Hambrick, 1992). They are more likely to break out of anarrow mindset and to recognize that situations canchange and that these changing situations require newapproaches (Shepherd, Zacharakis, & Baron, 2003; Starr& Bygrave, 1991). Besides the consequences of other-industry experience, also the choice to face differenttypes of experiences is a signal of the innate propensitytowards change of such individuals (Dearborn & Simon,1958; Silva, 2007). The choice to work in different envi-ronments is more likely to be made by inventive individu-als (Koellinger, 2008).

Moreover, the possibility that CEOs with other-industryexperience only (i.e. without same-industry experience aswell) lack the knowledge base to identify opportunities in


their current firm (in the old-economy) is relieved by thepresence of institutions providing specialized industry-specific knowledge and skills to executives. Suchnstitutions, affiliated with Chambers of Commerce, tradeunions or trade associations, are common in theEuropean Union (Soriano & Castrogiovanni, 2010). As faras the old-economy industry is concerned, industry-specific knowledge is rather well documented and canto a certain extent be made available to CEOs throughspecialized education (Castanias & Helfat, 2001; Patzeltet al., 2008).

Finally, other-industry experience expands CEOs� profes-sional networks (Richard et al., 2009), which might increaseCEOs� awareness of opportunities to invest in productiveinvestments instead of keeping large amounts of cash. Fol-lowing these arguments, we contend that CEOs with experi-ence in other industries view more opportunities to investcash resources and reckon more with the opportunity costof cash than CEOs without other-industry experience. Wehypothesize that:

Hypothesis 4. Cash holdings are negatively associated witha CEO�s experience in other industries.

CEO educationBesides CEO age, tenure and experience, the level ofCEO education is also an important UET variable. Itmay seem unlikely that educational experiences wouldaffect managerial decisions since top executives typicallyare many years beyond their formal education. Yet a sig-nificant body of research suggests that CEO education isreflected in the characteristics of their organizations,through the association of education with a wide arrayof cognitive, psychological and social characteristics.CEO education is associated with a higher capacity forinformation processing (Schroder, Driver, & Struefert,1967), a higher level of open-mindedness, higher recep-tivity to innovation (Becker, 1970), higher boundary span-ning, higher tolerance for ambiguity and higherintegrative complexity (Dollinger, 1984). These observedassociations have been found robust and stable, alsoafter controlling for CEO age and industrial setting (Wier-sema & Bantel, 1992). We expect higher educated CEOsto be associated with lower cash levels for the followingreasons.

First, as higher educated CEOs are less risk averseand better informed about the external environment(Dollinger, 1984; Schroder et al., 1967), we posit thatthey will be less concerned with the precautionary motiveof cash. Second, as higher educated CEOs are more opento new ideas, changes and investment opportunities(Barker & Mueller, 2002; Wally & Baum, 1994; Wiersema& Bantel, 1992), we contend that these CEOs will be bet-ter aware of the opportunity cost of cash. Hence, highereducated CEOs are more likely to spend their cashresources in profitable investments compared to lowereducated CEOs as their external focus identifies moreinvestment opportunities and as they better realize thatproductive investments provide higher returns comparedto cash. We posit that:




Hypothesis 5. Cash holdings are negatively associated witha CEO�s educational level.

1 Graydon, a Belgian commercial company providing businessinformation, delivered the information to classify board membersas �insiders� or �outsiders�, taking into account family and profes-sional relationships. Insiders are defined as board members thatbelong to the firm�s management or have family relationships withthe firm�s management (based on surname and address). We alsoused information available on the company and other websites(organization charts, contact details mentioned on vacancy mes-sages and product information fiches, . . .), to classify some addi-tional board members as inside directors. The board members notclassified as inside directors according to the previous steps wereclassified as outside directors.2 If board demographics (duality, outsider proportion) are

included in our regression model none of these are significantlyrelated to cash holding. This proves the passive nature of the boardsrepresented in our dataset.3 We also scale cash and cash equivalents with total assets instead

of net assets, and obtain similar research findings.

Research method

In order to test our hypotheses, we collect data from asample of Belgian manufacturing SMEs. The followingsections detail the sample selection procedure, the surveyinstrument employed and the measurement of thevariables.

Description of the sample

The research population consists of Belgian (Flemish) SMEsthat have between 15 and 250 employees (expressed infull time equivalents) that belong to four industry-codeswithin manufacturing and in business for at least fiveyears. The four selected industries (manufacture of furni-ture, of synthetic products, of metal constructions, and ofmachinery for general use) are the largest ones within theFlemish SME sector. By selecting firms from specificindustry codes and regions, we are able to control forthe influence of industry, technology, and culture on cashpolicy. Applying these selection criteria yields a popula-tion of 948 firms.

These firms received a questionnaire in order to collectinformation about the CEO demographics and the controlvariable Environmental Uncertainty (EU). The question-naires were addressed to each firm�s CEO. Following Dillman(2000) we implemented the following three steps during oursurvey: (i) initial mailing, (ii) first follow-up, and (iii) secondfollow-up. We received 138 usable responses immediately.The two follow-ups resulted in an additional 82 usableresponses. In total, we obtained 220 usable responses,representing a response rate of 23.21%. This response rateis satisfactory and comparable to the response ratesreported in other mail-survey studies of small firms (Dennis,2003). After excluding missing answers we withhold 203observations.

In order to detect non-response bias, a two-step analy-sis is conducted. First, we compare respondents with non-respondents in terms of firm size, leverage, profitability,liquidity and cash holdings. Chi-square tests reveal no sig-nificant differences between respondents and non-respon-dents with respect to these variables. We control themain construct measures (i.e. the variables relating tothe CEO) for dissimilarity between the immediate respon-dents and the respondents to the follow-up surveys. Inde-pendent sample t-tests and chi square tests reveal nodifferences between both groups. These analyses allowus to conclude that non-response bias is not a major con-cern in this sample.

Analyzing our dataset, we observe that the sample SMEsare characterized by weak governance structures. First, 42SMEs in our dataset do not have a board of directors sincethey are not required to install a Board due to their legalorigin. From these firms, 34 firms (81%) have a CEO withan ownership stake and count less than 50 employees,making it likely that only one owner-manager is present inthe majority of these SMEs, implying a considerable amountof freedom to determine cash levels. From the SMEs having


a board of directors installed, we observe that up to 45% ofthem have boards merely consisting of insiders1. Theremaining 55% of the boards are characterized by outsiderrepresentation, but consist in large majority of insiders.Further, in 65% of the SMEs in our dataset the CEO is theboard chair reducing the degree of board monitoring inthese firms (Boyd, 1994). Moreover, in our dataset non-CEO-duality often goes together with the role of chairmanof the board being taken on by another insider and not byan outsider. The board compositions observed in our datasetare not in line with the Belgian corporate governance codefor SMEs (code Buysse) that strongly encourages to have asufficient number outsiders (independents) on the boardand to have the board chaired by somebody else than theCEO in order to strengthen governance and control(Gabrielsson & Winlund, 2000). Our dataset is thus charac-terized by passive boards2, suggesting that the CEOs in ourdataset have considerable discretion with regard to cashholding decisions.

Measurement instruments

We use an industry-adjusted measure of cash holdings asdependent variable. The level of cash holdings in a firm ismeasured as the ratio between cash and cash equivalentsto total assets less cash and cash equivalents (Harford, Man-si, & Maxwell, 2008; Opler et al., 1999)3. Since the survey isconducted in 2006, we compute the level of cash holdings atyear-end 2006. In addition, we compute the average level ofcash holdings at year-ends 2005 and 2006 which proxy forthe average level of cash holdings during the year 2006.Since industry might be a significant factor in the level ofcash holdings (Harford et al., 2008), we compute an industryadjusted measure of a firm�s cash holdings. We compute themedian cash holdings within each of the four industries in-cluded in our study and subtract the corresponding industrymedian cash holdings from each firm�s level of cash hold-ings. A higher industry-adjusted cash holding indicateshow much excess (if positive) or less (if negative) cash a firmholds compared to the industry�s median value.

The research variables include the CEO demographicscollected from the survey. In the questionnaire, CEO ageis measured as a categorical variable including three clas-ses: younger than 35 year, between 35 and 50 year, and



5 To a higher or lower extent, depending on a CEO�s tolerance forambiguity for example.6 To capture environmental uncertainty, we use an instrument

based on Gordon and Narayanan (1984) still widely used in therecent literature (Abdel-Kader & Luther, 2008). Respondents rateon a 5 point Likert scale ranging from 1 (=‘‘completely predict-able’’) to 5 (=‘‘completely unpredictable’’) the extent to whicheach of the following eight environmental elements are unpredict-


more than 50 year. These classes correspond with the clas-ses used in Damanpour and Schneider (2006). We createdummy variables for each class and include in the regressionequation the dummy variable indicating whether the CEO isbetween 35 and 50 years and whether the CEO is older than50 years. We expect a positive sign for both indicator vari-ables suggesting that younger CEOs (less than 35 years) areless likely to hold excess cash levels compared to the olderCEOs. CEO Tenure is measured using a categorical variable,which is in line with Maes, Sels, and Roodhooft (2005). Wedistinguish between tenures below 5 years (=1), tenures of5 up to 9 years (=2), and tenures of ten years and more(=3). The scale is defined on the basis of Finkelstein andHambrick (1996) who claim that these cut offs distinguishbetween respectively short, medium and long tenures, inturn being associated with certain CEO attributes. Barkerand Mueller (2002) used similar cut offs in their study (to de-fine subgroups based on tenure in function of a subgroupanalysis). In line with Yang, Zimmerman, and Jiang (2011)we measure CEO industry experience using a dummy vari-able. Because same- and other-industry experience arenot mutually exclusive we created a dummy variable forsame-industry experience (1 = yes, 0 = no) and a dummy var-iable for other-industry experience (1 = yes, 0 = no)4. CEOEducation is a dummy variable with the value of one whena CEO obtained at least a degree in higher education(bachelor or master degree) and zero otherwise.

Firm�s level of cash holdings is regressed on the researchvariables together with some control variables (i.e. firmsize, cash flow generation, liquidity, financial leverage,environmental uncertainty and industry membership). FirmSize is the natural logarithm of the total assets. We expect anegative association between cash holdings and firm sizesince larger firms benefit from economies of scale of holdingcash that is used for their normal activities (Mulligan, 1997).In addition, larger firms have lower financial constraints(Fazzari & Petersen, 1993; Whited, 1992), have lower levelsof information asymmetry (Berger et al., 2001; Jordan,Lowe, & Taylor, 1998) and are to a lower extent vulnerableto financial distress (Rajan & Zingales, 1995; Titman &Wessels, 1988) which gives rise to lower cash holdings. CashFlow Generation is computed as the ratio of cash flows tototal assets. In case of information asymmetry, firms preferto fund themselves with internally generated resourcesinstead of borrowing these funds (Myers & Majluf, 1984).Hence we assume a positive association between cash levelsand cash flows, consistent with Opler et al. (1999) and Gar-cıa-Teruel and Martınez-Solano (2008). Given the impor-tance of cash substitutes in SMEs (Bigelli & Sanchez-Vidal,2012), we introduce liquidity and financial leverage ascontrol variables in our dataset. Liquidity (or net workingcapital) is considered as a cash substitute and is definedas the difference between current assets (less cash and cash

4 According to Kitchell (1997) the effect of experience is charac-terized by �diminishing returns�. Several years of experience arecritical to broaden horizons, but once new psychological attitudesare formed, additional years of experience are not useful. Conse-quently, dummy variables capture the CEO attributes related toexperience well (certainly given long periods of experience in thecurrent dataset). By means of dummies we also capture the innatepropensity of executives towards other types of experiences (Silva2007).


equivalents) and current liabilities scaled by total assets.We expect a negative association between liquidity and cashholdings (Bigelli & Sanchez-Vidal, 2012). Financial leverageis measured as the ratio of long- and short-term bank debtsto total assets. Prior literature finds a negative associationbetween cash holdings and leverage since the costs of fundsused to invest in liquid assets rise as leverage increases(Baskin, 1987; Garcıa-Teruel & Martınez-Solano, 2008).Financial debt also serves as a monitoring mechanism to en-sure that managerial decisions are in line with shareholdermaximization. Firms with low levels of debt engage in theaccumulation of cash reserves (Ferreira & Vilela, 2004).

Environmental uncertainty tends to be an important attri-bute of a corporate cash policy (Ramirez & Tadesse 2009).Environmental uncertainty implies the inability to accuratelyassess the external environment of the organization or thefuture changes that might occur in that environment. Higherlevels of environmental uncertainty make it difficult formanagers to make accurate predictions about the market(Milliken, 1987). Consequently, a high level of environmentaluncertainty is more likely to result in fear5 for potentialfinancial distress caused by unexpected losses. Potentialcash shortage could force managers to raise funds on unfa-vorable terms or to liquidate other assets at large discount.To overcome this situation, CEOs operating under a high levelof environmental uncertainty may decide to hold larger lev-els of cash at their disposal. Environmental uncertainty ismeasured on the basis of the CEOs� responses on factors thatcapture this concept6. Finally, we control for industry influ-ence by inserting industry dummies in the regression equa-tion. The dependent and control variables are winsorizedat 1% and 99% level to mitigate the influence of outliers.

Empirical results

Descriptive analyses

Table 1 provides statistics about the profile of the respon-dents. Panel A documents that 43% of the CEOs are morethan 50 years old and that 80% of the respondents possessa bachelor or master degree. Almost 60% of the respondentshave a tenure of 10 years or more (a tenure of more than 20or 30 years is not an exception). The average CEO tenure is13 years. Moreover we observe that of those CEOs having

able: market activities of competitors, needs and tastes ofcustomers, actions of suppliers, production technologies, govern-ment regulation and policy, economic environment, industrialrelations, and deregulation/globalization. Based on a factor anal-ysis, the ratings on only six items (excluding the two factors relatingto the unpredictability of customers and suppliers) are averaged toarrive at an overall EU index. Internal consistency is assessed withthe Cronbach�s a coefficient and corresponds with a value of 0.66.This meets the cutoff value of 0.6 (Hair, Anderson, Tatham, &Black, 1998).



Table 1 Profile of the respondents (N = 203).

Variables %

Panel A: CEO demographicsCEO ageYounger than 35 years 10Between 35 and 50 years 47Older than 50 years 43

CEO tenureLess than 5 years 21Between 5 and 9 years 20More than 9 years 59

CEO industry experienceBoth same- and other-industry experience 13Same-industry experience only 22Other-industry experience only 27

CEO educationHaving a degree in higher education 80

Panel B: Industry distributionManufacture of metal constructions 33Manufacture of synthetic products 22Manufacture of machinery for general use 23Manufacture of furniture 22

Panel C: Firm size distributionLess than 50 FTE 67Between 50 and 100 FTE 23More than 100 FTE 10

Notes: This table provides frequency statistics for the CEOdemographic variables, the industry distribution and the firmsize distribution (based on the number of full time equivalentemployees).


gained same-industry and other-industry experience(respectively 35% and 40% of the CEOs), the large majority(80% on average) had an experience of more than 3 years.The survey findings reveal that 38% of the respondents donot have any experience in neither the same nor anotherindustry. The majority of the sample firms are operatingin the metal constructions industry (Table 3panel B). Wealso notice that the large majority of responding SMEs aresmall since 67% of the sample firms have less than 50 FTEemployees and only 10% of the sample firms employ morethan 100 FTE employees with a maximum of 244 FTEemployees (Panel C).

Table 2 reports the descriptive statistics of the continu-ous variables used in the regression analyses. This tableexhibits an average deviation of a firm�s cash holdings fromindustry median of 7%. Cash and cash equivalents representon average 12% of a firm�s total assets (not tabulated). Thispercentage is a bit larger than the percentage revealed forSpanish SMEs (Garcıa-Teruel & Martınez-Solano, 2008).

Table 3 presents univariate tests about the associationbetween the CEO demographics and cash holdings. The re-sults show a positive association between CEO tenure andcash holdings. Older CEOs tend to retain higher cash levelsas well. The statistics further demonstrate higher cash hold-ings by CEOs without other-industry experience. Inconsis-tent with predictions, the results do not yield statisticallydifferent levels of cash holdings associated with CEOsame-industry experience and CEO education.


The correlation matrix in Table 4 documents similarassociations between the CEO demographics and the levelof cash holdings as illustrated in Table 3. We also notesome significant correlations between the control vari-ables and the level of cash reserves. Table 4 exhibits thatfirms with higher cash flows and with lower bank debtshold higher levels of cash. A positive correlation existsbetween cash levels and environmental uncertainty. Thecorrelation between cash levels and firm size is negativeand marginally significant. The correlations between theindependent variables do not yield multicollinearityproblems.

Multivariate results and discussion

In order to examine the association between cash holdingsand the set of CEO and control variables, we run OLSregressions. Table 5 reports several models. The models1–3 present the regression results with the cash levels of2006 as dependent variable, and the models 4–6 reportthe results with the average cash holdings of 2005 and2006 as dependent variable. We run the models for (i) allfirms included in the sample, (ii) only the small firms(fewer than 50 employees) in the sample and (iii) only themedium-sized firms (more than 50 employees) in the sam-ple. In order to control for heteroscedasticity, significancelevels are adjusted to reflect White�s correction of thestandard errors.

Considering all firms in the analysis, the regression find-ings illustrate that both dummy variables related to CEOage have a positive association with the level of cash hold-ings. These results confirm H1 indicating that older CEOstend to hold higher levels of cash. On the condition thatwe control for CEO age, which is the case in our regressionmodels, CEO tenure is revealed not to be related to cashholdings. Hence, the regression results do not give supportfor H2. These findings indicate that CEO age is a strongerpredictor of cash holdings than CEO tenure. Our finding isconsistent with McClelland et al. (2010) who identifiedCEO tenure as a weaker predictor of CEO commitment tothe status quo than CEO age. Our finding is also consistentwith Barker and Mueller (2002) for example, who revealedthat CEO tenure is much less important than CEO age inexplaining R&D spending. The critical factor is that olderCEOs have shorter career horizons in which to recoverlosses, causing them to be highly conscious of the needfor career and financial security. We note that 10% of theCEOs in our dataset are older than 60 years and close tothe process of retirement (an aspect which is not capturedby our categorical measure for CEO tenure). According toBarker and Mueller (2002) and McClelland and O�Brien(2011) these CEOs lose interest in long-term opportunitiesand become increasingly conservative. Consequently, theywill be less concerned with the opportunity cost of cashand more concerned with the precautionary role of cash,implying higher cash holdings.

Concerning CEO experience, our findings reveal thatCEOs with other-industry experience are less likely to holdexcess levels of cash compared to CEOs without other-industry experience. Hence, these results allow us toconfirm H4. CEOs with other-industry experience have abroader mindset, demonstrate a higher openness for and



Table 2 Descriptive statistics for the continuous variables (N = 203).

Variables Min. Max. Mean Standard deviation

Dependent variablesCasht �0.11 0.87 0.07 0.20Cashavg �0.11 0.88 0.07 0.19Independent variablesSIZEt�1 (in th. EUR) 304 355,356 9,929 26,814CFLOWt�1 �0.37 0.31 0.10 0.10LIQt�1 �0.61 0.67 0.13 0.24FLEVt�1 0.00 0.40 0.07 0.10EU 1.17 4.50 3.09 0.50

Notes: This table provides descriptive statistics for the variables Casht: industry adjusted cash and cash equivalents at year 2006 scaled bytotal assets less cash and cash equivalents; Cashavg: industry adjusted average cash and cash equivalents at year-ends 2005 and 2006scaled by total assets less cash and cash equivalents; SIZEt�1: total assets in 2005; CFLOWt�1: cash flow to total assets in 2005; LIQt�1:current assets minus current liabilities scaled by total assets in 2005; FLEVt�1: long- and short-term debt to total assets in 2005; EU:environmental uncertainty.

Table 3 Univariate statistics (N = 203).

Variables Mean Casht Test statistic Mean Cashavg Test statistic

CEO Age F-test F-testYounger than 35 years 0.012 1.670 �0.010 2.371c

Between 35 and 50 years 0.068 0.061Older than 50 years 0.095 0.086

CEO Tenure F-test F-testLess than 5 years �0.001 4.714a 0.005 3.722b

Between 5 and 9 years 0.064 0.045More than 9 years 0.104 0.093

CEO Industry experience t-test t-testNo same-industry experience 0.082 0.918 0.066 0.227With same-industry experience 0.056 0.060No other-industry experience 0.101 2.538a 0.094 2.852a

With other-industry experience 0.031 0.019

CEO Education t-test t-testNo higher education 0.100 0.960 0.083 0.731With higher education 0.067 0.059

Notes: This table provides univariate statistic results of the association between CEO demographic variables (CEO age, CEO tenure, CEOindustry experience and CEO education) and Casht: industry adjusted cash and cash equivalents at year 2006 scaled by total assets lesscash and cash equivalents; Cashavg: industry adjusted average cash and cash equivalents at year-ends 2005 and 2006 scaled by total assetsless cash and cash equivalents.a Statistical significance at the 1% level (one tailed test).b Statistical significance at the 5% level (one tailed test).c Statistical significance at the 10% level (one tailed test).


awareness of new opportunities and have a higher innatepropensity towards change (Raskas & Hambrick, 1992; Silva,2007), causing them to reckon more with the opportunitycost of cash, resulting in lower cash levels. CEOs withsame-industry experience do not hold different amountsof cash compared to CEOs without same-industry experi-ence. Probably this insignificant result is driven by theopposing effects of the knowledge base benefit and the rou-tine trap risk related to same-industry experience. Based onour empirical results we are unable to confirm H3.

Finally, cash holdings are found to be unrelated to the le-vel of CEO education, which is in line with Bertrand and


Schoar (2003), but inconsistent with H5. A potential expla-nation for the insignificant finding is that more educatedmanagers tend to pursue long-term development and donot invest in current projects which can generate lower re-turns than long-term projects. This strategy accumulatesfree cash flows and increases cash holdings.

The coefficients of the control variables are in line withprior literature, except for firm size. Firms with more cashflows, lower debt levels and lower levels of working capitalhold higher levels of cash. Firm size is insignificantly relatedto the level of cash holdings. We also observe a positivecoefficient for the variable EU, indicating that firms are



Table 4 Correlation matrix (N = 203).

1 2 3 4 5 6 7

1. Casht 1.0002. Cashavg 0.955a 1.0003. CEO age < 35 �0.112c �0.141b 1.0004. CEO age35_50 �0.018 �0.004 �0.335a 1.0005. CEO age > 50 0.090 0.094c �0.303a �0.796a 1.0006. CEO tenure 0.211a 0.189a �0.358a �0.073 0.305a 1.0007. CEO s.i. exp. �0.067 �0.019 �0.132c 0.016 0.068 �0.114 1.0008. CEO o.i. exp. �0.175a �0.196a 0.026 �0.059 0.042 �0.232a �0.0289. CEO education �0.064 �0.048 0.025 0.054 �0.070 �0.218a 0.03410. SIZEt�1 �0.103c �0.099c 0.033 �0.106 0.087 �0.126c �0.07011. CFLOWt�1 0.202a 0.176a �0.015 0.004 0.006 0.135b 0.04712. LIQt�1 0.005 �0.048 �0.001 �0.115c 0.116c 0.095 �0.07113. FLEVt�1 �0.289a �0.332a 0.066 0.053 �0.096 �0.147b �0.01914. EU 0.182a 0.165a 0.043 0.018 �0.045 0.087 �0.017

8 9 10 11 12 13 14

8. CEO o.i. exp. 1.0009. CEO education 0.260a 1.00010. SIZEt�1 0.006 0.184a 1.00011. CFLOWt�1 �0.060 �0.096 0.025 1.00012. LIQt�1 �0.002 0.016 0.140b 0.268a 1.00013. FLEVt�1 0.098 0.039 0.032 �0.162b �0.208a 1.00014. EU �0.081 �0.154b �0.070 0.087 �0.059 �0.075 1.000

Notes: This table reports the Pearson correlation coefficients between Casht: industry adjusted cash and cash equivalents at year 2006scaled by total assets less cash and cash equivalents; Cashavg: industry adjusted average cash and cash equivalents at year-ends 2005 and2006 scaled by total assets less cash and cash equivalents; CEO age < 35: dummy variable representing 1 when the CEO is less than 35 year;CEO age35_50: dummy variable representing 1 when the CEO is between 35 and 50 year; CEO age > 50: dummy variable representing 1when the CEO is more than 50 year; CEO tenure: categorical variable based on the number of years that the CEO is appointed in the firm;CEO s.i. (same-industry) experience: dummy variable representing 1 when the CEO has experience in the same industry; CEO o.i. (other-industry) experience: dummy variable representing 1 when the CEO has experience in another industry; CEO education: dummy variablerepresenting 1 when the CEO obtained a degree in higher education; SIZEt�1: natural log of total assets in 2005; CFLOWt�1: cash flow tototal assets in 2005; LIQt�1: current assets minus current liabilities scaled by total assets in 2005; FLEVt�1: long- and short-term debt tototal assets in 2005; EU: Environmental uncertainty.a Statistical significance at the 1% levels (one tailed test).b Statistical significance at the 5% (one tailed test).c Statistical significance at the 10% levels (one tailed test).


more likely to retain cash when the economic environmentis difficult to predict.

Focussing on the regression results for both subgroups(i.e. small firms and medium-sized firms), Table 5 only re-ports significant regression coefficients for the CEO demo-graphics within the subgroup of small firms and not withinthe subgroup of medium-sized firms7. The regression resultsfor the small firms document that older CEOs and CEOs with-out other-industry experience tend to hold more cash com-pared to younger CEOs and CEOs with other-industryexperience. These results are consistent with the findingsfor the whole sample. The insignificance of UET in explain-ing cash holdings among medium-sized is probably caused by

7 We acknowledge that the number of observations within themedium-sized group is quite low reducing the degrees of freedom.However, also the correlation matrix illustrates insignificant corre-lations between the CEO demographics and cash holdings for thesample of medium-sized firms. Moreover, including the CEOdemographics in a regression equation without control variables(with the purpose to increase the degrees of freedom) does notyield significant coefficients either.


a lower level of CEO discretion. Using t- and chi-squaretests, we namely observe significantly stronger governancemechanisms in the medium-sized subgroup than in thesmall-sized subgroup. Medium-sized firms demonstratehigher outsider proportion on their boards and less CEOduality, suggesting more stringent CEO monitoring and low-er CEO discretion. Additionally, medium-sized firms arecharacterized by larger TMTs and more management layers.This implies that CEOs have to consult different views be-fore taking decisions, resulting in lower CEO discretion.

In order to test the validity of our results, we use othermeasurement scales for the CEO variables. First, we use aslightly different categorical classification for tenure (i.e.below 4 years, between 4 and 8 years, and 9 years or more).Second, we replace the categorical variable CEO tenurewith the following two dummy variables: a dummy variabletaking value 1 when CEO tenure is low (below 5 years) and adummy variable taking value 1 when CEO tenure is moder-ate (between 5 and 9 years). The reference variable is adummy variable taking value 1 when CEO tenure is high(9 years or more). Third, we employ continuous variables



Table 5 Regression results on the associaton between cash policy and ceo demographics.

Variables (1)CashtAll

(2)CashtSmall

(3)CashtMedium-sized

(4)CashavgAll

(5)CashavgSmall

(6)CashavgMedium-sized

Intercept 0.112 �0.109 0.191 0.110 �0.187 0.128(0.104) (0.172) (0.229) (0.097) (0.175) (0.209)

CEO age35_50 0.048 0.095 �0.074 0.062 0.095 �0.003(0.035)c (0.045)a (0.075) (0.030)b (0.043)a (0.053)

CEO age > 50 0.070 0.098 �0.061 0.086 0.109 0.005(0.039)b (0.050)a (0.069) (0.033)a (0.048)a (0.043)

CEO tenure 0.018 0.009 0.032 0.010 0.005 0.017(0.015) (0.020) (0.028) (0.014) (0.020) (0.022)

CEO s.i. experience �0.039 �0.062 �0.033 �0.024 �0.053 �0.012(0.031) (0.039) (0.043) (0.028) (0.036) (0.031)

CEO o.i. experience �0.050 �0.064 0.034 �0.061 �0.067 0.010(0.025)b (0.028)a (0.047) (0.024)a (0.030)a (0.039)

CEO education 0.028 0.022 0.038 0.035 0.033 0.056(0.043) (0.051) (0.050) (0.041) (0.048) (0.037)

SIZEt�1 �0.009 0.021 �0.014 �0.009 0.030 �0.014(0.011) (0.020) (0.021) (0.010) (0.020) (0.019)

CFLOWt�1 0.376 0.427 0.473 0.301 0.397 0.409(0.122)a (0.158)a (0.238)b (0.114)a (0.158)a (0.196)b

LIQt�1 �0.087 �0.119 �0.030 �0.121 �0.146 �0.084(0.058)c (0.076)c (0.108) (0.054)b (0.072)b (0.092)

FLEVt�1 �0.484 �0.492 �0.479 �0.575 �0.620 �0.481(0.118)a (0.160)a (0.168)a (0.107)a (0.149)a (0.128)a

EU 0.182 0.250 0.007 0.149 0.215 0.020(0.074)a (0.092)a (0.149) (0.074)b (0.095)b (0.128)

Industry dummies Yes Yes Yes Yes Yes YesAdjusted R2 14.14% 13.03% 16.27% 16.32% 15.52% 21.02%F-value 3.412a 2.455a 1.902b 3.815a 2.758a 2.235b

N 203 137 66 203 137 66

Notes: This table report OLS regression results including the following variables: Casht: industry adjusted cash and cash equivalents atyear 2006 scaled by total assets less cash and cash equivalents; Cashavg: industry adjusted average cash and cash equivalents at year-ends2005 and 2006 scaled by total assets less cash and cash equivalents; CEO age35_50: dummy variable representing 1 when the CEO isbetween 35 and 50 year; CEO age > 50: dummy variable representing 1 when the CEO is more than 50 year; CEO tenure: categoricalvariable based on the number of years that the CEO is appointed in the firm; CEO s.i. (same-industry) experience: dummy variablerepresenting 1 when the CEO has experience in the same industry; CEO o.i. (other-industry) experience: dummy variable representing 1when the CEO has experience in another industry; CEO education: dummy variable representing 1 when the CEO obtained a degree inhigher education; SIZEt�1: natural log of total assets in 2005; CFLOWt�1: cash flow to total assets in 2005; LIQt�1: current assets minuscurrent liabilities scaled by total assets in 2005; FLEVt�1: long- and short-term debt to total assets in 2005; EU: environmental uncertaintyand industry dummies.The regression analyses are conducted for three samples: the complete sample, a subsample of small SMEs only (<50 employees), and asubsample of medium-sized SMEs only (P50 employees).The table exhibits the beta coefficient and the White corrected standard error between brackets.a Statistical significance at the 1% levels (one tailed test).b Statistical significance at the 5% (one tailed test).c Statistical significance at the 10% levels (one tailed test).


for CEO tenure, CEO same-industry experience and CEOother-industry experience instead of a categorical or a dum-my measurement scale. All robustness checks (untabulated)support the main research findings, especially in small firms.

Conclusion

Traditional finance theories like the trade-off theory, thefinancial hierarchy theory and the agency theory provideeconomic arguments to explain cash holdings and adopt a


rational economic view. We add to existing knowledge bystudying whether also the CEO�s (subjective) importance at-tached to these alternative economic arguments explainscash level decisions. To this end, we rely on the Upper Ech-elons Theory (UET) (Hambrick & Mason, 1984). This theoryattributes well defined behaviors and inclinations to CEOswith certain cognitive, social and psychological characteris-tics, and posits that the latter characteristics can be validlyproxied by CEO demographics (e.g. age, tenure, experience,education). Our study builds further on the recent stream of




behavioral finance studies that depart from decision makers�bounded rationality in explaining financial decisions (Subrah-manyam, 2007). In particular, we integrate insights of UETinto the traditional finance theories to explain cash holdings.

This study is conducted using a sample of 203 CEOs ofBelgian (Flemish) private SMEs as it is generally acknowl-edged that CEOs in SMEs are often sole decision makersand thus have high discretion in determining cash policy(Van Gils, 2005). Our study reveals that in addition to themost prominent financial and operational variables captur-ing the traditional economic theories explaining cash policy,CEO demographics add power in models explaining cashholdings. First, we find that older CEOs retain higher cashlevels than younger CEOs. The risk aversion and the commit-ment to the status quo characterizing older CEOs (Barker &Mueller, 2002; McClelland & O�Brien, 2011) give rise to ahigher concern for the precautionary role of cash and a low-er concern for the opportunity cost of cash, resulting inhigher cash levels. Second, we find that CEOs with other-industry experience hold less cash than CEOs withoutother-industry experience. The more positive attitude to-wards change and innovation characterizing CEOs with ahigher diversity in experience goes together with a higherconcern for the opportunity cost of cash, resulting in lowercash levels. CEO tenure, CEO same-industry experience andthe level of CEO education do not have an association withthe level of cash.

Splitting the sample in two subgroups (i.e. small firmsand medium-sized firms), we observe that UET especiallyadds explanatory power in determining cash levels for thesample of small firms, but not for the sample of medium-sized firms. Within the latter group, none of the CEO demo-graphics show a significant association with cash holdings. Apotential explanation for the differences in research find-ings is that the governance mechanisms to monitor theCEO are more developed in medium-sized firms comparedto small firms, which lowers the discretion of CEOs in cashholding decisions. In addition, medium-sized firms employmore managers which reduce the power of CEOs to takedecisions on their own.

The findings of our study are of practical importance forstakeholders. As CEOs tend to hold excess cash levels, caus-ing opportunity costs and being detrimental to stakeholder(including shareholder) value, it is useful to stakeholders toknow the cash practices associated with current or potentialnew leaders� demographics. Stakeholders should for examplebe aware that older CEOs and CEOs without other-industryexperience tend to hold higher levels of cash, increasingthe risk to miss opportunities and lowering shareholder va-lue. Stakeholders should judge whether these tendenciesare acceptable, given the broader organizational context.

The present study is subject to a number of limitations,which provide avenues for future research. A first set of lim-itations relates to the measurement of the CEO demograph-ics. With regard to CEO education we consider the level ofeducation, not the type of education. With regard to CEOexperience we do not focus on functional experience (mar-keting, sales, general management, . . .). Future researchcould examine whether type of education, e.g. more busi-ness-oriented or more technical-oriented, and whether dif-ferent kinds of functional experiences affect CEO behaviorwith regard to cash policy in a different way. Second, our


research population is restricted to industrial SMEs in theold economy. We are unable to generalize our results toSMEs in other industries. Future research can examinewhether a CEO�s impact on cash policy is similar in commer-cial, service or high tech SMEs.

Acknowledgments

We thank Dr. Tensie Steijvers, two anonymous reviewersand the editor for their valuable suggestions and comments.

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RAF ORENS is assistant professor financialaccounting at the KU Leuven – Faculty ofEconomics and Business at Antwerp, Bel-gium. In 2007, he obtained his PhD inapplied economics at Hasselt Universitywith a dissertation on the relevance of non-financial disclosures. His main researchinterests are: international accountingstandard setting, earnings quality, non-financial reporting and analysts� behaviour.

ANNE-MIE REHEUL received her Ph.D. inApplied Economics in 2009 at the Universityof Antwerp. Subsequently she joined theHogeschool-Universiteit Brussel (HUB)where she is assistant professor at the Fac-ulty of Economics and Management. Herresearch focuses on small business, man-agement accounting and external auditing.


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Do CEO demographics explain cash holdings in SMEs?

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