differences in perceptions of access to finance between potential male and female entrepreneurs

Differences in perceptions ofaccess to finance between potentialmale and female entrepreneurs

Evidence from the UK

Caleb KwongEntrepreneurship and Innovation Group, University of Essex,

Southend-on-Sea, UK

Dylan Jones-EvansEnterprise and Innovation, University of Wales, Cardiff, UK, and

Piers ThompsonDepartment of Accounting, Economics and Finance,

Cardiff Metropolitan University, Cardiff, UK

Abstract

Purpose – The purpose of this study is to examine whether being female increases the probabilitythat an individual feels difficulty in obtaining finance is a barrier to starting a business. The studyaims to extend this to examine if a pure gender effect exists or whether it is the interaction of genderwith demographic, economic and perceptual characteristics that plays the most important role in theperception of financial constraint.

Design/methodology/approach – The data within this study are drawn from the GlobalEntrepreneurship Monitor (GEM) adult population survey between 2005 and 2007. The first stage ofthe study splits male and female respondents into separate sub-samples and runs individualregressions on each portion of the sample. The second stage of the study combines the male and femaleportions of the sample to directly examine the differences in perceived financial constraint betweengenders.

Findings – The findings suggest that a greater proportion of women are solely constrained byfinancial barriers than their male counterparts. The gender of the respondent was also found tointeract with a number of other personal characteristics in a significant manner.

Practical implications – This finding suggests that policymakers should be encouraged to marketthe availability of start-up finance from various sources to encourage women to attempt to obtain thenecessary finance rather than being discouraged at the first hurdle.

Originality/value – Although actual financial barriers faced by female entrepreneurs have beenextensively studied, this is one of the first studies to focus on the concept of perceived financialconstraints faced by potential female entrepreneurs.

Keywords Entrepreneurship, Gender, Finance, Small business, Perception, Barriers

Paper type Research paper

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1355-2554.htm

Although data used in this work are collected by the GEM consortium, their analysis andinterpretation are the sole responsibility of the authors.

Perceptions ofaccess to finance

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Received 4 December 2009Revised 11 May 2010

Accepted 1 January 2011

International Journal ofEntrepreneurial Behaviour

& ResearchVol. 18 No. 1, 2012

pp. 75-97q Emerald Group Publishing Limited

1355-2554DOI 10.1108/13552551211201385

IntroductionIn many nations across the world, such as the US (Carter and Allen, 1997), Australia(Bennett and Dann, 2000), Canada (Mirchandani, 1999), and New Zealand (McGregorand Tweed, 2002), there has been a significant growth in the level of femaleentrepreneurship. It is estimated that women own and manage up to one third of allbusinesses in developed countries (McClelland et al., 2005). In the UK, there was an 18.2per cent increase in the number of self-employed women between 2000 and 2008, ascompared to 15.6 per cent for self-employed men. Whilst this is an encouraging trend,women still account for only 28.8 per cent of the total number of the self-employed inthe UK (Causer and Park, 2009).

This relatively low uptake of self-employment suggests that women continue to faceconsiderable challenges in starting a new business. Previous literature suggests thatthis is due to fewer resources (Boden and Nucci, 2000), less extensive social networks(Kwong et al., 2009), restricted access to business clients (Bates, 2002), and slowerdelivery of orders from suppliers (Weiler and Bernasek, 2001). Studies have also shownthat a lack of access to funding continues to be a major impediment which can preventwomen from becoming entrepreneurially active (Brush et al., 2001; Marlow and Patton,2005; Shaw et al., 2005). The requirements for women to fulfil substantial family roles(Mirchandani, 1999) and subordination within waged work results in them being lesslikely to amass sufficient personal funds to start new ventures. It will also causedifficulties in attaining attractive enough credit histories to access external funding(Marlow and Patton, 2005). This results in lower levels of overall capitalisation, lowerratios of debt finance, and much lower usage of private equity or venture capital(Carter and Shaw, 2006; de Bruin and Flint-Hartle, 2005). This, in turn, will impactdirectly on the growth potential of women-owned businesses (Carter and Allen, 1997).

This study examines whether women perceive greater financial constraints thanmen prior to starting a business. However, while there is potential for a pure gendereffect, we develop a model which suggests that it is the interaction of other attributesreflecting human, financial and social capital with gender that account for aconsiderable amount of this greater perception of difficulty in raising finance. Unlikemany other studies in this area, this research will not examine women who havealready started a business. Instead, it will focus its attention on potential femaleentrepreneurs who are considering establishing a new venture but who may perceivedifficulties in obtaining finance as a constraint to entrepreneurial activity. Utilising theglobal entrepreneurship monitor (GEM) survey in the UK between 2005 and 2007, thepaper attempts to determine, after controlling for personal characteristics, whetherwomen consider that they are hindered by lack of access to finance when consideringstarting a business.

Structural factors, supply side considerations, risk aversion and perceivedavailability of financeAccording to Carter and Shaw (2006), gender differences in the use of finance withinsmall firms can be explained by three key factors namely, structural variations in thetype of businesses established, supply-side discrimination by financial institutionsagainst female-owned businesses and debt aversion. Various studies have indicatedthe structural dissimilarities between male and female-owned businesses (Kwong et al.,2006; Harding, 2007). For example, women are more likely to become self-employed in

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sectors such as education, health care and community work (Harding, 2007). Inaddition, it is found that women often require less finance than many male-ownedenterprises (Mirchandani, 1999). The research by Kwong et al. (2006) also found thatwomen’s expectations of turnover from their business are less than for men and thatthere are lower levels of start-up funding. A study by Shaw et al. (2005) found similarresults.

In terms of supply side discrimination, studies have suggested that banks imposetheir credit procedures and criteria subjectively against female entrepreneurs (Fayand Williams, 1991, 1993; Orser and Foster, 1994; Carter et al., 2007; Amatucci andSohl, 2004; Martin and Wright, 2005). As Blake (2006) notes, this is mainly becausethe conventional measures used by banks to determine creditworthiness have beenbased upon masculine norms including socialisation (Aldrich, 1989; Moore andButtner, 1997; Becker-Blease and Sohl, 2007), work and business related experiences(Carter and Rosa, 1998), personal savings (Marlow and Patton, 2005), length ofprevious career (Carter and Shaw, 2006), and domestic circumstances (Carter andRosa, 1998; Carter and Shaw, 2006). Nevertheless, evidence in this area remainslargely inconclusive (McKechnie et al., 1998; Carter and Shaw, 2006; Shaw et al., 2005)as the criteria used by banks to judge male and female applicants were broadlysimilar (Carter et al., 2007). Studies in the US that controlled for the creditworthinessof applicants have generally backed up these findings with no significant differencesin the loan denial rates of men and women (Blanchflower et al., 2003). In fact, similarloan denial rates are found even where higher levels of market concentration mightallow lenders to discriminate on a continuing basis. Where no firm dominates themarket, competition might be expected to force them to drop discriminatory practicesor to leave the market if they fail to adapt (Becker, 1957; Cavalluzzo et al., 2002). Thismight be an increasing feature if small business credit scoring (SBCS) continues toincrease in popularity (Berger and Frame, 2007). This more automated approach tomaking loans, which focuses on factors such as choice of sector as opposed to themore traditional relationship driven approach, could make it harder for women to getbeyond the application stage.

Finally, it has been argued that business ownership is a planned behaviour wherethe intention to complete the activity is governed by not only attitudes and socialnorms but also the perceived behavioural control of the individual (Ajzen, 1991; Konand Storey, 2003; Watson and Newby, 2005). As entrepreneurship is often a high-riskundertaking that requires individuals to have high levels of self-confidence and beliefin their ability to achieve (Bennett and Dann, 2000), its images and representationshave often been associated with male traits such as aggressiveness and risk-taking(Bruni et al., 2004; Bennett and Dann, 2000). Conversely, the risk-averse natureassociated with femininity means that women in general are less likely to believe intheir ability to obtain finance. This “discouraged effect” is recorded in the study byRoper and Scott (2009) which found that being a woman significantly increases theprobability that an individual will perceive lack of finance from people outside theircircle of family and friends as a barrier in starting a business. However, their studyfound no evidence that such a perception actually prohibited women from starting abusiness.

One explanation for this aversion is the presupposition by women that they wouldbe rejected anyway (Carter and Shaw, 2006). For example, Marlow (1997) found that


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while entrepreneurs from both genders felt that women faced discrimination in startingtheir businesses, a larger proportion of women believed this discrimination existed. Hillet al. (2006) reported that the perceptions of many women that bankers held a negativeview of female entrepreneurs regarding their creditability. Research by Carter andAllen (1997) found that factors such as accessing commercial loans and having a goodrelationship with their bank manager leads to an increase in the probability of womenowning a larger business. Nevertheless, the cross sectional nature of their analysisprevents the determination of whether this reflects either a financial barrier which isfaced by all but a few female entrepreneurs or a perceived barrier preventing access tofinance. Any presumptions about the likelihood for failure may also be reinforced bybank lending officers dissuading those who they feel have little probability ofsuccessfully applying for finance from making applications (Blake, 2006). On the otherhand, this aversion may due to previous negative experiences suffered whenpreviously dealing with formal financial institutions such as banks (Kon and Storey,2003).

These perceived hurdles in acquiring venture finance may lead some femaleentrepreneurs to respond to any potential refusal by requesting a smaller amount offinance or seeking external finance less frequently (Marlow, 1997; Hill et al., 2006). Thisis supported by previous research, which suggests that women are more reluctant toassume the burden of debt and engage in business growth, resulting in a lower demandfor debt, private equity and venture capital finance (Marlow and Carter, 2006; Carterand Shaw, 2006). In addition, female entrepreneurs may choose to engage in sectorsthat are smaller and require less start-up funding (Carter and Shaw, 2006 Coleman,2000). Where external finance is sought, female entrepreneurs are more likely torequest too little investment in the first round of funding (Amatucci and Sohl, 2004).According to Carter (1997) and Babcock and Laschever (2003), this demonstrates afemale trait of settling for less or, alternatively, a male trait of anticipating greaterfinancial needs. Nevertheless, this leaves women in a disadvantaged position duringthe later stages of business development as investors may be wary of continuedrequests for finance (Amatucci and Sohl, 2004).

This study will increase knowledge of the perceptions of potential femaleentrepreneurs regarding the availability of new venture finance. The research does notconcentrate on whether such perceptions are actually accurate. Instead, it focuses onwhether potential female entrepreneurs are more likely to perceive such problemswhen compared with their male counterparts. Perception is important because it oftencomes before real action and such perceptions, even when false, can be as damaging asthe presence of an actual barrier. As a result, entrepreneurial aspirations, and thus theongoing process in starting a business, may be badly damaged. In addition, theseperceptions can affect risk-taking behaviour such as the choice of business, the choiceof source of finance and the amount of finance required (Marlow, 1997). This, in turn,has implications on the structural dissimilarities between male-owned andfemale-owned businesses and supply-side discrimination. Therefore, by establishingwhether women with certain characteristics are more likely to perceive financialconstraint, we hope to lay down the foundation for future studies into the reasons as towhy such perceptions exist and whether they can be overcome, thus ensuring thatwomen can be more confident in entering entrepreneurship as well as choosing moreambitious venture projects.

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Personal characteristics and perceptions of financial constraintsThe evidence described in the previous section suggests that the greater difficulties inraising new venture finance faced by women, in comparison with men, are due to avariety of factors. This includes structural variations (Shaw et al., 2005), supply sidediscrimination (Carter et al., 2007), disadvantage in the workforce which reducesmatching personal finance (Carter and Shaw, 2006; Carter et al., 2007), debt and riskaversion (Roper and Scott, 2009), and lower confidence in their finance competencies(Orhan, 2001). As a result, women felt they were less able to raise finance (Carter andShaw, 2006) and were more likely to attribute any difficulties in raising finance to theirgender rather than the economic environment or weaknesses in the business plan(Marlow, 1997). On this basis, we propose:

H1. Women are more likely than men to attribute their inability to start a businessdue to lack of finance, holding all other characteristics equal.

However, other characteristics may also significantly impact upon the likelihood thatan individual perceives themselves to be financially constrained. In determining thedemographic characteristics that are likely to affect one’s perceived financialconstraints, two different groups of influences are likely to be at work namely thoselinked to actual difficulty in obtaining finance, and those which put individuals in abetter position to judge their likelihood of obtaining finance. Gender will inter-relatewith these demographic characteristics through two different processes namely anacquisitional effect and a performance effect. In the first of these, gender impedes theextent that other demographic characteristics that influence the acquisition of differentforms of capital are developed. This is because the differing family and social roles ofwomen will influence the extent to which they are able to acquire the human, social andfinancial capital associated with these demographic characteristics. For instance, thisacquisitional effect means that women may invest less in acquiring human capitalthrough education and training when in work due to the limiting influence of theirfamily roles on the returns associated with these investments (Bobbit-Zeher, 2007). Thesecond impact of gender operates through the performance effect. This relates to theimpact that demographic characteristics have upon women’s perceived ability toacquire finance. For example, although a man and a woman may acquire the same levelof human capital through education and training, this human capital may haveasymmetric influences on the perceived extent to which they improve the possibilitiesof obtaining finance for their businesses. Ultimately, this means that gender could havea double impact on the perceived ability to acquire finance, as it will be influence notonly the extent that demographic characteristics associated with acquiring finance aregenerated, but also their influence once produced. Pure differences in male and femaleperceptions of financial constraints are likely to diminish as the performance effects ofother characteristics are accounted for, but it is unclear if they will completelydisappear. Figure 1 presents a possible model of these relationships. The first part ofthe model links the different impacts that gender may have on the perceivedprobability of acquiring finance if sought, both directly where influences such asdiscrimination may play a role (shown by the dotted black arrows), and indirectlywhere the acquisition (shown by the solid black lines) or performance (shown by thedashed black arrows) of other demographic characteristics is influenced.


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Demographic characteristics that may influence the perceived difficulties in accessingfinance, and how gender may moderate their influence, are discussed in more detailbelow. Some demographic characteristics, such as household income acting as a proxyto wealth accumulation, may be assumed to have relatively equal effects in reducingfinancial constraints for men and women. Potential entrepreneurs of both genderswould expect finance sources to view household income as reflecting a greateravailability of collateral (Evans and Jovanovic, 1989; Kihlstrom and Laffont, 1979).However, there is no reason to believe that all demographic characteristics will have asymmetrical impact on men and women’s perceptions of financial constraint, as isdiscussed below. Therefore:

H2. There are no gender differences in the impact of household income onperception of access to finance as a constraint to starting a business.

Those in employment are most likely to have personal savings available to invest infuture business projects and are therefore less likely to perceive finance as a barrierfrom doing so (Stiglitz and Weiss, 1981). However, disadvantages faced by women inthe workplace such as occupational segregation could all result in lower personalsavings and assets to use as collateral (Carter and Shaw, 2006; Carter et al., 2007). Suchdisadvantages may also deprive women the types of technical and managerialexperiences that are highly valued by conventional investors when assessing theviability of new businesses (Manning and Swaffield, 2008). The higher level ofpart-time employment for women also means that even when employment experienceshave been acquired, they are likely to be valued less by investors (Brophy, 1992). Theseactual disadvantages in employment may negatively affect their perceived feasibilityin obtaining finance (Manning and Petrongolo, 2008; Baines and Wheelock, 2000). Wetherefore propose:

H3. Employment is less likely to alleviate the perceived existence of financialconstraints for women in contrast to men.

Figure 1.Acquisitional andperformance effects ofgender

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Educational attainment provides lenders with a signal of quality when determining thevalidity of potential entrepreneurs as investment propositions (Bates, 1991; Astebroand Bernhardt, 2003; Carter et al., 2003; Xu, 1998). Highly educated individuals are alsomore likely to identify sources of financial access, as well as better able to estimate thelikelihood of receiving finance (Vos et al., 2007). The mainstream labour marketliterature suggests that educational qualifications play a more important role forwomen than men (Loury, 1997). This is potentially because of the weaker role playedby employment experience, as discussed above. Therefore, we propose:

H4. Educational qualifications are more likely to reduce women’s perception ofbeing financially constrained than men.

Age is normally perceived as a proxy to experience and wealth accumulation, both ofwhich are essential to overcome perceived financial constraints and provide therequired financial safety net to make the subsequent investment decision comfortable(Baum and Silverman, 2004). Given the gendered nature of the mainstream labour forceand impact of career breaks in many women’s career path, we propose that age willhave a lower impact in reducing the perception of financial constraint for potentialfemale entrepreneurs than their male counterparts. Other evidence to support thisproposition includes women’s overrepresentation in part-time employment (Manningand Swaffield, 2008). It is also found that women are perceived to be older than men ofthe same age so that their optimal performance is reached at an earlier age (Duncanand Loretto, 2004). All of these factors are likely to increase women’s perception thatage will count against them in acquiring loans, especially as compared to their malecounterparts:

H5. Age is likely to have a stronger influence for men than women in reducing theperception of being financially constrained.

Individuals who know a recent business starter will be better able to recognise whetherfinance is actually available and from which sources (Hoanga and Antoncic, 2003;Jones-Evans and Thompson, 2009). However, women often struggle to entermale-dominated business networks that are perceived to be of higher quality(Aldrich, 1989; Moore and Buttner, 1997; Mirchandani, 1999; Becker-Blease and Sohl,2007; Burt, 1992). Their relative exclusion from such networks may reduce theirconfidence in their own ability to obtain finance. We therefore propose thatentrepreneurial social capital may be seen as of a lower quality for women than theirmale counterparts. This means it will be perceived to be of less benefit when seekingfinance:

H6. Knowing individuals who have started their own business is less likely toreduce the perception of financial constraint for women than men.

Risk aversion is perceived to be one of the primary hurdles that prevents potentialentrepreneurs from accessing finance (Marlow and Carter, 2006; Carter and Shaw,2006; Baines and Wheelock, 2000). However, there is evidence that women are morelikely to display traits that are associated with lower risk-taking, such as greater riskaversion and lower self esteem (Babcock and Laschever, 2003; Manning and Swaffield,2008; Cronson and Gneezy, 2009). There may also be less desire to be involved incompetitive situations (Cronson and Gneezy, 2009). These traits and other


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psychological factors decrease their financial negotiation abilities when compared withmen (Craver and Barnes, 1999; Manning and Swaffield, 2008). However, even if womenare less risk averse, it is found that others tend to stereotype women in this way(Johnson and Powell, 1994; Atkinson et al., 2003). As a result, women who are lessconfident of success know that there is a good chance that they will merely confirm theview that they are not prime entrepreneurial material, thus producing a “doublewhammy” of difficulties faced by women in raising finance. Holding other factorsconstant, we propose that fear of business failure will have a stronger influence onwomen in reducing their perceived ability to access finance:

H7. Lower fear of failure is more likely to reduce the perception of financialconstraint for female potential entrepreneurs compared to male potentialentrepreneurs.

Therefore, previous research studies suggest that whilst demographic characteristicsassociated with greater financial, human, and social capital are likely to reduce theperception that financial constraints will form a barrier to starting a business, it islikely that these will differ for men and women. For many women, their variedexperiences in the workplace and business community are likely to result in social andexperience-based forms of capital performing less effectively and having a smallerimpact in reducing perceptions of financial constraint. This may result in educationalqualifications playing a larger role for women in overcoming such barriers toentrepreneurship. The following section will outline the data and variables used toinvestigate these potential patterns.

Research methodologyAs discussed in the preceding section, gender may influence the probability of being afinancially constrained entrepreneur in two ways. As a preliminary analysis, the firststage of the study focuses on the acquisitional effect of gender. Using data drawn fromthe 2007 Office of National Statistics Annual Population Survey (APS) and AnnualSurvey of Hours and Earnings (ASHE) alongside the GEM data (discussed below), weconsider whether there is evidence that women acquire less of the resources that willinfluence their perceptions of financial constraints. The APS is a nationalrepresentative dataset of approximately 500,000 individuals, annually collectedthrough the combination of labour force surveys in England, Scotland, Wales andNorthern Ireland. Boosts are used to ensure a minimum sample of 510 in each localauthority in England, with a minimum of 450 in each London borough. The datasetcontains information on a broad set of socio-economic details, including labour forceparticipation and employment. The ASHE is produced using a 1 percent extract of HerMajesty’s Revenue and Customs data from Pay as You Earn (PAYE) tax data, whichprovides detailed information on the earnings of disaggregated groups of employees inthe UK.

Although it is difficult to produce a true measure of the human and social capitalacquired, demographic measures, such as qualifications and economic activity providean indication of the extent that women and men differ in their participation in activitiesthat relate to the acquisition of these resources. In addition, ASHE provides estimatesof earnings and employment with full and part-time work. In terms of the networks

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and experience gathered through the work environment, these measures provide anindication of the quality of these activities.

The data used within the main component of this study is drawn from the GlobalEntrepreneurship Monitor (GEM), which consists of a large stratified random sample ofthe UK population. GEM has conducted surveys of enterprise activities in a number ofcountries since 1999 (Bosma et al., 2008). One of the main aims of GEM is to produce anumber of internationally comparable measures of entrepreneurial activity, as well asconsidering factors motivating and dissuading individuals from starting new ventures(Kwong et al., 2009; Thompson et al., 2009). The GEM UK survey was conducted acrossall regions via telephone interviews utilising a randomised direct dial technique, andundertaken by a professional research organisation. Papers by Reynolds et al. (2005) andBygrave et al. (2003) provide a comprehensive explanation of the GEM data collectionand formatting processes. The data used in this study is drawn from the GEM UKsurveys for the years 2005 to 2007 during which a total of 117,395 respondents wereinterviewed. Of these, inclusion within the regression is limited to the working agepopulation between 18 and 64 without missing data on any regression variables.Consequently, only 49,107 individuals are included in a majority of the main analysis.

This study focuses on potential female entrepreneurs who are consideringestablishing a new venture but who may perceive difficulties in obtaining finance as aconstraint to entrepreneurial activity. Therefore only data from potential rather thanactual entrepreneurs were analysed. In the GEM survey, all respondents who did notstart a business are asked the following question: “What would you say are the biggestbarriers to you starting a business or becoming self-employed?” The GEM surveyprovides an open-ended format to this question in which the respondents provide a listof barriers that they perceived as preventing them from starting a business. Theseanswers are then coded into the survey by the interviewers, with all those whoperceived financial constraints to be a barrier to starting a business coded into onesingle variable. Our study focuses largely on those who reported access to finance astheir sole obstacle in starting a new venture[1]. Interviewers were directed to encouragerespondents to cite all barriers that had prevented them from starting a business. As aresult, we can be confident that this variable only represents those who considered anabsence of finance as the sole barrier that prevents their involvement in enterprise. Thefinancial constraint variable takes a binary format, with 1 indicating the perceivedpresence of financial constraints and 0 indicating an absence of it. Those who arealready engaging in entrepreneurial activities are removed from the sample as theycannot be considered potential entrepreneurs. Since the dependent variables arebinary, this study uses binominal logistic regression analysis to test the linkage. Thebinominal logistic regression estimates the probability of an event happening which, inthis study, is the perception of the existence of financial constraints by respondentswho decided against starting a business.

In order to control for individuals’ demographic characteristics that make themmore or less financially constrained, a variety of variables representing human andfinancial capital are also included in the regressions. These include age; education(Doctorate, Master’s degree, Bachelor degree, A-Level, GCSE[2], vocationalqualifications, no formal qualifications); work status (employed full-time, employedpart-time, homemaker, retired, in education, economically inactive); household income;and migration status (life-long resident of their present UK region, in-migrant from


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another UK region, immigrant from outside the UK). Availability of internal finance,and the availability of collateral to aid access to external finance, are the two factorsmost closely associated with wealth. Unfortunately, the GEM data does not containdata on wealth. As accumulated assets are a function of the individual or family’sincome stream, we therefore use household income as a proxy. The primary reason isthat we deem this to be a better proxy than individual income for the availability ofinternal capital is because friends and family have been found to be a primary source offinance in the early stages of business development (Bygrave et al., 2003). Use ofhousehold income also has the secondary benefit of being less strongly correlated withthe academic qualifications and age of the individual respondent. Variance inflationfactors were calculated for each of the demographic characteristic variables included inthe calculations. None of these were found to exceed 1.86, which suggests littleevidence of multicollinearity. As a further check, the estimates were produced in theabsence of household income. Similar results were also produced with the exclusion ofhousehold income as in its presence. However, the importance of household incomewas apparent in the significance of the likelihood test of the model with householdincome against the alternative of without it (model 2, see below: x 2 ¼ 155.429, d.f. [2],p-value ¼ 0.000).

The study also introduces two perceptual characteristics variables, namely socialnetworking with other entrepreneurs (represented by whether the respondentpersonally knows someone who started a business in the last two years), and fear offailure which would prevent involvement in a business start. Additional controls arealso made for ethnic background, location (UK government office region of residence)and temporal effects (year of survey). Most of these controls are represented usingdummy variables and, where more than two categories exist, multiple dummies arecompared to a base category. The exception is age, which is recorded as a continuousvariable.

The study is conducted in two parts. The first stage of the study focuses on each ofthe genders separately (female, n ¼ 27,757; male, n ¼ 21,350) to measure whether anyof the standard demographic, economic, and attitudinal characteristics affect women’sperceptions of financial constraint (model 1). The results of these gender specificestimations partly replicate the full and extended models discussed below. However,we include these in order to isolate the overall significance of demographiccharacteristics on the perception of financial constraint. In the extended and fullmodels for women, this is the combination of the coefficient on the demographiccharacteristic and relevant interaction term. If these possess opposite signs, then theoverall significance for women will be difficult to identify. The second stage of thestudy combines the male and female portions of the sample to directly examine thedifferences in perceived financial constraint between genders. Model 2 forms ourbaseline model and examines the connection between standard demographic, economicand attitudinal characteristics, and those respondents who perceived financialconstraints as the sole barrier to starting a business. Nevertheless, as the literature hasplaced a considerable emphasis on treating gender as an analytic category in its ownright, rather than simply being another variable (Lewis, 2006; Mirchandani, 1999;Bruni et al., 2004), Models 3 and 4 introduce gender interaction terms to capture thegender-specific effects. These extended and full models allow the identification of anysignificant differences in the influence of demographic characteristics on the

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perception of financial constraint between the genders. Model 3 is an extended versionof Model 2 with the introduction of interaction terms between gender and some of thecontrol variables. It provides information regarding any gender effect upon each of thecontrol variables examined although the perceptual variables are excluded from thisspecification. As a cost saving measure, the perceptual variables are only included inthe GEM questionnaire for half the sample, so the sample size is reduced considerably.The extended model (model 3) allows the full available sample to be used to check therobustness of the results obtained when the restricted sample is used. The full model isestimated as model 4 where gender interaction terms are included as in the extendedmodel (model 3). However, the perceptual variables are also included as in baselinemodel (model 2).

Results and discussionStarting with the acquisitional effect of gender, Table I shows that women are morelikely to be economically inactive and, where employed, are much more likely to be inpart-time employment. It appears therefore that the traditional gendered roles withinsociety inhibit the ability of women to make the same network contacts and acquire thesame human capital as their male counterparts, which would reduce the perceptions of

Female Male All

Economic activityPercentage of working age population (%) 69.8 83.3 76.5

Employment – full time employmentPercentage of employed (%) 58.2 88.6 73.7

Earnings – gross annual (£)Full-time: mean 24,131 33,656 30,015Full-time: median 20,513 26,281 24,043Part-time: mean 9,582 12,356 10,139Part-time: median 7,901 7,968 7,908

Earnings – gross hourly rate (£)Full-time: mean 12.40 14.88 13.97Full-time: median 10.48 12.09 11.47Part-time: mean 9.53 10.95 9.83Part-time: median 7.28 7.15 7.26

EducationNVQ Level 4 þ : percentage of economically active (%) 34.6 30.5 32.4NVQ Level 4 þ : percentage of working age population (%) 29.1 27.8 28.4No qualifications: percentage of economically active (%) 8.3 9.9 9.2No qualifications: percentage of working age population (%) 14.0 13.1 13.5

Social networkPercentage of working age population (%) 21.6 29.6 25.7

Fear of failurePercentage of working age population (%) 37.6 34.0 35.8

Table I.Demographic differences

by gender


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financial constraint. Women’s earnings, with the exception of median part-time hourlypay, are significantly lower than their male counterparts. Although the results shouldbe treated with caution, part of this difference is likely to reflect the lower quality ofemployment and less well regarded occupations in which women are over-represented.Further evidence is found from the GEM data on social networks, with women lesslikely to personally know someone that started a business in the last two years. Thosewomen in employment are on average better qualified, with a significantly smallerpercentage holding no qualifications and more educated to the equivalent of NationalVocational Qualification (NVQ) level 4 or above[3]. This could reflect the greaterimportance of formal education for women as a source of human capital relative toexperience (Loury, 1997).

Tables II and III display the results from the regression analysis[4]. The percentageof variance explained by the Models is relatively low, with between 4.5 and 5.2 per cent

Model 1Female Male

Dependent variable – finance the only barrier n p n p

Age 20.023 0.000 20.027 0.000

Education (base case – A-levels)Doctorate 20.603 0.011 20.392 0.042Master 20.443 0.000 20.268 0.011Bachelor 20.339 0.000 20.206 0.004GCSE 0.094 0.060 0.288 0.000Vocational 0.111 0.087 0.137 0.075Other qualifications 20.116 0.343 0.348 0.003No formal qualifications 0.287 0.000 0.285 0.000

Work status (base case – full-time employed)Part-time employed 20.127 0.003 20.114 0.231Homemaker 20.145 0.015 0.409 0.070Retired 20.342 0.000 0.166 0.090In education 20.264 0.019 20.158 0.266Economically inactive 0.094 0.222 0.202 0.019

Income (base case – middle 33 per cent)Lower 33 per cent 0.194 0.000 0.200 0.000Upper 33 per cent 20.302 0.000 20.291 0.000

Migrant status (base case – life-long residence)In-migrant 20.078 0.035 20.098 0.032Immigrant 20.205 0.016 20.051 0.591Social network 20.090 0.015 20.167 0.000Fear of failure 20.104 0.004 20.102 0.020

Constant 20.243 0.022 20.462 0.000n 27,757 21,350R 2 0.045 0.052Per cent correctly predicted 85.1 86.8LR test of model significance 774.88 0.000 613.24 0.000

Table II.Logit regressioncoefficients of perceivingfinancial constraintsacting as the sole barrierto starting a business formen and women

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Model 2 Model 3 Model 4Dependent variable – Baseline model Extended model Full modelfinance the only barrier B Sig. B Sig. B Sig.

Female 0.110 0.000 0.118 0.180 0.085 0.493Age 20.025 0.000 20.025 0.000 20.027 0.000

Education (BC: A-levels)Doctorate 20.501 0.001 20.577 0.000 20.376 0.051Master 20.363 0.000 20.371 0.000 20.256 0.014Bachelor 20.282 0.000 20.305 0.000 20.197 0.005GCSE 0.168 0.000 0.282 0.000 0.291 0.000Vocational 0.116 0.019 0.149 0.008 0.140 0.070Others 0.109 0.192 0.195 0.033 0.353 0.002No formal 0.276 0.000 0.333 0.000 0.296 0.000

Work status (BC: full-time employed)Part-time 20.092 0.017 20.141 0.050 20.112 0.236Homemaker 20.091 0.106 0.250 0.148 0.409 0.070Retired 20.120 0.066 0.013 0.849 0.171 0.080In education 20.209 0.017 20.100 0.341 20.155 0.274Economically inactive 0.142 0.013 0.217 0.007 0.209 0.016

Income (BC: middle 33 per cent)Low 33 per cent 0.199 0.000 0.226 0.000 0.198 0.000High 33 per cent 20.301 0.000 20.283 0.000 20.311 0.000

Migrant status (BC: Life-long residences)In-migrant 20.085 0.003 20.066 0.049 20.111 0.014Immigrant 20.131 0.038 20.020 0.780 20.060 0.530Social network 20.123 0.000 20.167 0.000Fear of failure 20.103 0.000 20.103 0.020Gender interactionGender *age 0.003 0.179 0.005 0.079

Education (BC: A-Levels)Gender *Doctorate 20.095 0.678 20.245 0.425Gender *Master 20.174 0.097 20.189 0.175Gender *Bachelor 20.061 0.363 20.146 0.107Gender *GCSE 20.124 0.036 20.196 0.016Gender *Vocational 20.022 0.759 20.025 0.802Gender *Other qualifications 20.196 0.117 20.472 0.005Gender *No formal qualifications 20.025 0.725 0.004 0.969

Work status (BC: full-time employed)Gender *Part-time employed 0.081 0.300 0.010 0.921Gender *Homemaker 20.374 0.035 20.550 0.019Gender *Retired 20.271 0.003 20.513 0.000Gender *Student 20.102 0.440 20.105 0.562Gender *Economically Inactive 20.098 0.246 20.120 0.302

(continued )

Table III.Logit regression

coefficients of perceivingfinancial constraints

acting as the sole barrierto starting a business for

men and women


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of the variation explained. The models correctly predict around 80 per cent ofresponses for the perception of financial constraint being the sole barrier, and thelikelihood ratio tests of the models indicate they all outperform the null of a constantprobability at the 0.1 percent level. The three models in Table III (models 2, 3 and 4) arehighly comparable, with most control variables exhibiting the same relationships withsimilar levels of significance.

The pure effect of gender on perceived financial constraints as a barrier to starting abusinessAfter controlling for other variables, the baseline model (model 2) shows that womenare significantly more likely to perceive difficulties in accessing finance as the solebarrier to entering entrepreneurship (both at the 1 percent level), thus supporting H1.This suggests that women are not only at a disadvantage when it comes to obtainingnew venture finance as found in previous studies (Carter and Shaw, 2006), but that thisbarrier can also be perceptual (Marlow, 1997). This means the confidence of women inobtaining external finance is reduced which, in turn, could dissuade attempts to accessfinance. The odds-ratios of 1.116 suggest that the odds of female respondentsperceiving finance as a barrier is 12 per cent greater than their male counterparts.

The additional gender effect on perceived financial constraints as barriers in starting abusiness – examining the effect of gender on the performance of demographic andeconomic variablesAlthough the gender specific and baseline models (models 1 and 2) found that mostdemographic characteristics influence the probability of perceiving financialconstraints by both genders in a similar direction, the strength of these influencesmay differ. In addition, a small number of variables did show some differences betweenthe results generated for each gender. Therefore, the extended and full models (models3 and 4) incorporate interaction terms between gender and the personal characteristicsto identify any significantly different effects for the genders. One notable change, as aresult of the inclusion of interaction terms, is that the pure gender effect is no longersignificant when the performance effect of gender on other characteristics was taken

Model 2 Model 3 Model 4Dependent variable – Baseline model Extended model Full modelfinance the only barrier B Sig. B Sig. B Sig.

Income (BC: middle 33 per cent)Gender *Lower 33 per cent 20.042 0.399 20.004 0.949Gender *Upper 33 per cent 0.019 0.716 0.021 0.765Gender *Social network 0.078 0.174Gender *Fear of failure 20.003 0.958

Constant 20.406 0.000 20.401 0.000 20.385 0.000n 82,584 82,584 49,107R 2 0.047 0.048 0.050Per cent correctly predicted (%) 85.8 83.3 85.8LR test of model significance 1300.7 0.000 2404.1 0.000 1357.2 0.000Table III.

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into account. In other words, women may perceive themselves to be more likely to facefinancial barriers to entrepreneurship. The reason for this is because demographiccharacteristics, which reduce the perception of financial constraint, are less effective.

Household income and genderThe baseline model (model 2) found that household income is negatively correlatedwith women’s perceived financial constraint and significant at the 1 percent level, aresult that is consistent with Stiglitz and Weiss (1981). The odds-ratio of 1.220 suggeststhat people living in households falling in the lowest third of the income range (lessthan £11,500) are around 22 percent more likely to perceive finance as the barrier tostarting a business as compared to those living in households in the middle third of theincome distribution (£11,500 to £49,999). This implies that the probability that those inthe upper third of households by income (£50,000 or more) perceive a financialconstraint to exist is only 74 percent of that of those in the middle third. In the extendedand full models (models 3 and 4), the interaction terms are found to be insignificant,thus supporting H2 namely that household income symmetrically influencesperceptions of financial constraints for men and women.

Employment status and genderModel 1 (female) suggests that the coefficient for the female homemaker, retired, andpart-time employment are negative and significant. This suggests that women in thesegroups are less likely to perceive financial constraints to be a barrier to starting abusiness as compared to women in employment. Contrary to this, no such relationshipwas found for men. In fact, model 1 (male) suggests that retired men are significantlymore likely than those in full-time employment to perceive financial constraints to bethe only barrier to starting a business. The negative finding for women suggests thatthey may have a partner who generates a stable income and therefore perceive less of aproblem in accessing finance.

In the full model (model 4), the interaction terms between gender and those who area homemaker and retired are significantly negative. Therefore, H3 is supported asemployment has a reduced influence on alleviating financial constraints for women incontrast to men. Nevertheless, a complication that is not possible to address with thecurrent dataset is that the work choices of couples are interdependently determined.

Education and genderConsistent with previous literature (Bates, 1991; Astebro and Bernhardt, 2003; Xu,1998; Vos et al., 2007), the baseline model (model 2) suggests that university graduatesare significantly less likely to perceive financial constraints to be a barrier to starting abusiness than those holding just A-levels who, in turn, are significantly less likely toperceive financial constraints to exist than those with no qualifications. For example,the odds-ratio for those who possess a Bachelor’s degree is 0.754, which suggests thatthose who hold an undergraduate degree are roughly 75 percent as likely to perceivefinancial constraints as the sole barrier to starting a business as those who onlypossesses an A-level qualification.

The extended model (model 3) finds that there is weak evidence to support H4. Theinteraction term between gender and possession of Master’s level qualifications isnegatively significant with the dependent variable at the 10 percent level. This


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suggests that whilst overall a Master’s level qualification reduces the likelihood ofperceiving financial constraints to be present, the influence of postgraduate educationon female perceptions is stronger. Using the extended and full models (models 3 and 4),it is also found that the interaction term between gender and GCSE qualifications isnegative and significant (at a 5 per cent level). This suggests that whilst those withonly GCSE qualifications are more likely to perceive financial constraints as being theonly barrier to start a business compared to those with A-Level qualifications, there isa lower impact for women. The weak support for H4 may reflect the lower value placedon those subjects predominantly studied by women by investors as is found to be thecase for employers (Bobbit-Zeher, 2007). This means that women face two conflictingeffects, i.e. education plays a more important role as a source of human capital indeveloping their perceptions of financial constraint, but they are aware that theirparticular qualifications may not be as highly valued as those held by others.

Age and genderThe baseline model (model 2) confirms the findings of Baum and Silverman (2004), thatage is negatively correlated with perceived financial constraint (at the 1 percent level).When examining the interaction terms in the full model (model 4), it is found that thecoefficient on the gender and age interaction terms are positive and significant at the 10percent level. This suggests that although age reduces the perceived financial barriersto starting a business as found in baseline model (model 2), this effect is smaller forwomen than men. The finding provides weak support for Hypothesis 5 i.e. that generallife experience will have less affect in reducing perceptions of financial constraint forwomen than men.

Social network and genderThe baseline model (model 2) found that social network significantly reduces, at a 1percent level, the perceived financial constraints of female respondents, supportingprevious studies in this area by Aldrich (1989). The odds-ratio for social network is0.884, which suggests that those who have personal knowledge of other individualswho started a business in the past two years are around nine-tenths as likely toperceive access to finance to be the sole barrier to entering entrepreneurship.

When the perceptual variables are introduced in the full model (Model 4), theinteraction term between gender and social network is insignificant. However, if wereplace the dependent variable by those who cited lack of finance as one of the manybarriers to start a business (model 5), we found that the interaction term is positivelycorrelated at a 10 percent level (Table IV). As social network is negatively andsignificantly correlated with perceived lack of finance in the baseline model (model 2),the positive interaction suggests that whilst knowing an entrepreneur reduces one’sperceived financial constraint, this has a smaller effect in alleviating the perception offinancial barriers for women. This provides weak support to H6 and could reflect thedifficulties faced by women in accessing male dominated business networks andtherefore in fully utilising their social capital to its maximum potential (Aldrich, 1989;Moore and Buttner, 1997; Becker-Blease and Sohl, 2007).

The inclusion of interaction terms with the perceptual variables results in theabsence of a pure gender effect, which implies that much of the gender effect found inthe baseline model (model 2) operates as a result of women perceiving themselves to be

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less able to exploit entrepreneurial social capital as effectively as men in order to accessfinance. It is unclear, however, if this is a direct effect of women considering themselvesless able to access finance through their social contacts or whether the informationdrawn from their networks is not as effective in reducing uncertainty about raisingfinance. However, given that these results are based on the broader measure offinancial constraints, this ineffectiveness could be due to a lack of interest inentrepreneurship by the respondent.

Fear of failure and genderThe study found weak evidence to support H7. Whilst the interaction term in the fullmodel (model 4) between gender and fear of failure is not significant, if we replace thedependent variable by those who cited lack of finance as one of the many barriers tostart a business (model 5), we find that the interaction term between the gender andfear of failure variables is positively significant at a 10 percent level. This suggests thatwhilst fear of failure increases financial constraint (as shown in the model 2), being awoman has an additional effect on perceived financial constraint.

ConclusionsThe results from the study show that women are more likely to perceive that they arefinancially constrained than their male counterparts, confirming the findings of Roperand Scott (2009). Additionally, this study found that gender plays an influential role inpreventing potential female entrepreneurs from starting a new business when no otherbarriers exist. The models developed found that women are around 10 percent more likelythan men to perceive finance to be the only barrier to entrepreneurship. This is despiteprior research suggesting that funding is broadly available to both genders by financialinstitutions in the UK (McKechnie et al., 1998; Shaw et al., 2005; Carter and Shaw, 2006;Carter et al., 2007). The results also indicate that perception of this funding issue bywomen manifests itself prior to any entrepreneurial activity. This suggests that suchperceptual problems can negatively affect business aspiration as well as actualparticipation, both in terms of size and sector of involvement, amongst women.Importantly, the study found that whilst very little pure gender effect existed, the gender

Model 5Dependent variable – finance one of one or more barriers B Sig.

Female 0.018 0.845Social network 20.251 0.000Fear of failure 0.443 0.000

Gender interactionGender *social network 0.073 0.085Gender *fear of failure 0.068 0.092

Constant 0.635 0.000n 49,107R 2 0.085Per cent correctly predicted 64.8LR test of model significance 3151.6 0.000

Table IV.Logit regression

coefficients (selected) ofperceiving financial

constraints acting as oneof the barriers to starting

a business for men andwomen


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effect operates through other characteristics as a performance effect. Worryingly, theexplanation for these performance effects may relate to a perception that less value isplaced on women’s work experience (Brophy, 1992) or perceived non-symmetric agediscrimination (Duncan and Loretto, 2004). Further sociological and psychologicalstudies, particularly using qualitative approaches, to explore the reasons for theoccurrence of such perceptions, could help to identify the policy actions required toencourage more women into entrepreneurship in a more confident manner, or highlightthose areas where new legislative interventions may be required to counterdiscrimination.

As suggested by Carter and Shaw (2006), aversion to risk is one of the possible reasonsthat could explain why women continue to see difficulties in obtaining finance. Indeed,this study found weak evidence that fear of failure has an additional effect on perceivedfinancial constraint for female respondents. Policymakers should therefore beencouraged to market the availability of start-up finance from various sources toencourage women to attempt to obtain the necessary finance rather than beingdiscouraged at the first hurdle. This includes the need to increase both financialawareness and financial literacy, so that potential female entrepreneurs are aware of allfinancial options open to them as well as increasing their ability to utilise those fundingsources they have knowledge of. A number of such initiatives have been set up in recentyears (LDA, 2005), including a series of outreach schemes called “Access to Finance” roadshows conducted by the UK’s Regional Development Agencies since 2006 to increase thefinancial awareness of potential female entrepreneurs. There is also female-friendlyfinancial literacy training available, such as the “Flying Start” programme conducted byNational Council of Graduate Entrepreneurship (NCGE) and the “Finance Readiness“course jointly conducted by London Development Agency and Business Link. However,there remains a need to encourage the development of further initiatives to supportwomen in accessing finance. These should not only emerge from public bodies andwomen’s stakeholders groups, but also from the private sector and community-basedorganisations, such as credit unions, which have greater outreach abilities.

As suggested by Hoanga and Antoncic (2003), the study found that having socialconnections to existing entrepreneurs reduces an individual’s perception of financialbarriers to starting a business. However, women’s entrepreneurial social networks havea smaller impact in reducing these perceptions of financial constraints compared tothose of their male counterparts. Of course, female business networks in the UK do exist,such as “Women Into the Network” funded by the EQUAL project of the European SocialFund, NGO-initiatives such as “The Amazon Women Entrepreneurs Network”, andregular local and regional meetings conducted by organisations within Prowess, themain organisation for female entrepreneurs. However, some have suggested that thereare essential differences between male and female networks in terms of structure, scope,breadth, and strength (Burt, 1992; Ibarra, 1992). This may affect the perceived feasibilityof obtaining finance and financial intentions of their members. There is also evidence tosuggest that women have struggled to enter male-dominated business networks(Aldrich, 1989; Moore and Buttner, 1997; Mirchandani, 1999; Becker-Blease and Sohl,2007). Therefore, there may be a role for public policy support in providing assistance tofemale entrepreneurs in acquiring the information traditionally obtained by menthrough business networks. This could take the form of business seminars and training

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or, if more direct resources are required, the development of matching services for femaleentrepreneurs with various sources of finance.

The study found a stronger effect from education in reducing these perceptions offinancial constraint for women. This echoes the study by Cook et al. (2007), whichsuggested that the educational level of women plays a strong role in the degree ofsuccess when developing business plans. This implies that female graduates couldprovide a source of potential entrepreneurs who are less likely to perceive obtainingfinance to be a problem and are more positively positioned to be capable of acquiringexternal funding. Universities and institutions such as the NCGE that have regularcontact with these groups could increase the level of female entrepreneurial activity byadvertising the benefits and potential of entrepreneurship as a career. For universities,this could be undertaken through cross faculty entrepreneurship educationprogrammes which address the needs of all the student population rather than justbusiness students. More importantly, they could provide enterprise initiatives that arespecifically targeted towards the specific needs of potential female entrepreneurswithin the student population.

This study focuses on findings from the UK and therefore it would be interesting todetermine the extent to which the findings on perceived financial constraints areconsistent internationally. The GEM study has repeatedly found that those who areborn outside the UK, as well as those who belong to ethnic minority groups in the UK,are considerably more likely to start a business ( Jones-Evans et al., 2008; Thompsonet al., 2010; Kwong et al., 2009; Jones-Evans et al., 2011). This implies that fewer peoplefrom these groups are deterred from starting a business as a result of perceivedfinancial barriers. It would therefore be interesting to find out whether it is the pressureof being in a new environment that pushed these people into entrepreneurship and ledthem to disregard their financial fears, or whether it is their entrepreneurial traits suchas lower fear of failure (Kwong et al., 2009) that may potentially reduce their perceivedfinancial barriers they face, contributing to the diverse entrepreneurship participationrates found in GEM (Jones-Evans and Thompson, 2009). The extent of genderdifferences was found to differ by ethnic group, suggesting that there is some elementof truth in the latter hypothesis (Kwong et al., 2009). Further qualitative andquantitative investigations exploring the international gender differences will certainlyenlighten the field.

Notes

1. The results from this variable is largely consistent with the variable that representsrespondents who reported access to finance as one of the obstacles that they faced in startinga business. For the purposes of preservation of space we omit the findings relating to thismore broadly defined perceived financial constraint variable from the main results reported,although where relevant they are referred to in the text. The full results are available fromthe authors on request.

2. Both A-level and GCSE are secondary qualifications in the UK.

3. National Vocational Qualification (NVQ) level 4 corresponds to a Bachelors or first degreelevel qualification.

4. Results reported are the logit regression coefficients. To preserve space only the coefficientsare reported in the tables, but where appropriate odds ratios are reported in the text to givean indication of the relative size of these effects.


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Corresponding authorCaleb Kwong can be contacted at: [email protected]


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