samuel mwaura finance and household influences (cdfa workshop)

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Finance and household influences on the growth of micro- enterprises Supporting micro-enterprise growth: ambition, family and finance CDFA workshop 13 March 2014 Sara Carter and Samuel Mwaura [email protected] [email protected] 1

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Presentation. Samuel Mwaura, Sara Carter , Finance and household influences on the growth of micro -enterprises.

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Page 1: Samuel Mwaura finance and household influences (cdfa workshop)

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Finance and household influences on the growth of micro-enterprises

Supporting micro-enterprise growth: ambition, family and financeCDFA workshop13 March 2014

Sara Carter and Samuel [email protected]

[email protected]

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Micro-enterprise in the UK• 1971 - 820,000 small firms in the UK• 2008 - 4.26 million businesses• 2012 - 4.8 million businesses

Half a million new businesses since the recession

• Despite… significant reductions in public sector employment

• Growing employment since 2009• Mostly self-employment(Lord Young Report)

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The vital 95% (?)• 2012 95.5% (4.6 million) of all UK enterprises micro-

firms (0–9 employees). 32% of private sector employment (7.8

million) 20% of private sector turnover. (Lord Young Report)

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Micro-enterprise in the UK

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Micro-enterprise in the UK

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The vital 95% (?)

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Drivers of growth• Growth important, beyond mere entry• But… How to engender growth?• Young report (3Cs)

Confidence – in the economy but entrepreneurs must have confidence in themselves (ambition)

Capability – skills (management)Coherence – government support and policy

towards entrepreneurship should be comprehensible, trustworthy and easily found

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Drivers of growth• Entrepreneurship literature (3Ms)

Money, Markets, Management (Bates et al, 2007)• Women’s entrepreneurship (5Ms)

Motherhood, Meso/Macro environment Meso – intermediate/ regional supportMacro – economic policy, culture, legal

environment(Brush et al, 2009)

• 6Ms - How about entrepreneurial “mojo”?

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Ambition“It is self-evident that if entrepreneurs do not intend to grow their businesses, their businesses are less likely to grow. Achieving growth is difficult and demands effort, and if the effort is not there, growth is less likely to materialise. But are the chances of business growth any greater for entrepreneurs who intend to grow their business?”(Levie and Autio, 2013, p9 - ERC White paper)

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Ambition• “Quality” of entrepreneurship more important for economic growth

than “quantity” of start-ups or self-employment (Levie and Autio, 2013)

• Back to “the vital 6%”?

• Other research: “Innovation orientation” has a higher impact on firm performance than

innovation inputs (R&D) and innovation outputs (new products) (Rosenbusch et al, 2011).

“Written strategy” (Hadjimanolis, 2000)

• Key take-away: ambition not blind ambition or delusion. • It’s about harnessing a battery of other productive aptitudes

and resources to enhance firm performance• Also, when written down… becomes a better articulated and

considered plan, hence higher likelihood of success.

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Family• All entrepreneurs embedded in the family

(Aldrich and Cliff, 2003)• Family norms, attitudes and values

Family role models (e.g. Parker, 2009)

• Founding teams usually family members (Ruef et al, 2002)

• Family key for resources and (moral) support Free or low cost labour, knowledge, other capital Spare resources used to diversify family business portfolio (as

one entity) (Alsos et al, 2014) Low risk “bricolage” within home-based businesses

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Home-based

businesses

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Family• Family transitions and lifecycle influence start-up, growth

and business lifecycle (e.g. Alsos et al, 2014) Young children – flexible occupation Kinship extension (through marriage) – new resources and new

business activities Departure (children moving out, retirement, death, etc)

• Family/ household dynamics affect business performance and growth Women: motherhood, household tasks, mobility – narrowly

tethered businesses (Brush et al 2009; Nichter and Goldmark 2009)

• Business systems affect family systems – including norms, attitudes and values (e.g. first in the family to start a business role-modelling for later generations)

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Family

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Finance• Access to finance the most significant barrier entrepreneurs face

Especially ethnic minority businesses (Ram and Jones, 2008; Ram et al, 2002; Fraser, 2009)

Women (Marlow and Patton, 2005; Hughes et al., 2012; Roper et al., 2006; Roper and Scott, 2009)

• However: Is due to outright discrimination by banks? (Hertz, 2011; Carter

et al, 2007) Is it structure? i.e. enterprise age, size, sector, ownership status

(Watson, 2002; BDRC, 2012; Marlow, 2012) Or gendered structure? e.g. women more likely to be sole-

proprietors in social services, restaurants, etc (Wu and Chua 2012)

Is it debt avoidance? (Cliff, 1998; Bird and Brush, 2002) Or discouragement (Kon and Storey, 2003; Han et al, 2008))

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• Traditionally, only two groups of borrower types: applicants and non applicants

• Within this context, issues included: • Non-applicants

Demand side risk-aversionNo need

• Applicants - Rejection Outright discrimination? Credit rationing?Structure and creditworthiness?

Finance

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• Since Kon and Storey (2003) “discouraged borrowers” became a big finance issue

“A good firm, requiring finance, that chooses not to apply to the bank because it feels its application will be rejected”

• Emergent evidence:Discouraged smaller, riskier and younger (Chandler, 2010; Han et al,

2008; Chakravarty and Xiang, 2012)Other factors: sector, firm strategy, experience, perceived quality of

existing banking relationshipsAlso: gender and ethnicity (Freel et al, 2010; Fraser, 2009).Fear of rejection highly ethnicised – 4% of White firms compared to

44% of Black African, 39% of Black Caribbean, 31% of Bangladeshi, 21% of Pakistani and 9% of Indian (Fraser, 2009)

Finance

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A typology of borrowers

New/ Renewed borrowers

(New successful applicants)

Unpropitious borrowers (No present need for finance)

Potential borrowers (Debt-averse: require finance, but no formal

application to bank at all)

Defunct borrowers (Prior user but no

present need)

Listless nonborrowers (Never applied, no

present need)

Dissuaded (bank advised

against applying)

Disillusioned (Rejected in the past; bank poorly handled

rejection)

Dismissed Departed

Borrower declines bank’s offer

Directly Discouraged (by direct bank actions)

Distracted (Other

reasons – media,

hearsay, etc)

Daunted (intimidated

by a priori notions of what bank borrowing

entails)

Self-diagnosed (Believed from self-evaluation

that they would be declined)

Undesirable Deals

(Unsuitable products , prices or

procedures)

Partial Demand (Do not apply for all required

finances e.g. need loan and overdraft but apply for O/D only)

Latent demand (Non-applicants/ non-

borrowing firms)

Extant borrowers (Existing borrowers, no

new application)

Partial borrowers (Do not apply for all required finances e.g. need loan and

overdraft but apply for O/D only)

Disinterested borrowers (Require finance, but

prefer nonbank sources)

Discouraged Borrowers (Require finance but

certain factors discourage application)

Bank rejects credit application

1

Indirectly discouraged (By non-bank factors)

Declined borrowers (Unsuccessful new

application)

Patent Demand (Applicant/ existing

borrowers)

Notional demand (All firms)

2

3

4

5

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A typology of borrowers

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• No gender effect detected. Women’s businesses’ borrowing behaviour and outcomes

categorisation not different from men’s once structural factors (enterprise age, size, sector, etc) are accounted for.

However, differences in amount of credit secured not presently investigated

• A small ethnicity effect remains after accounting for structure• Compared to Whites, some Ethnic Minorities Businesses (EMBs)

still more likely to be: declined credit Demand less than what they need (partial demand) Disinclined from borrowing even when they have investments needs

(i.e. debt-aversion attributable to discouragement – fear of rejection, or disinterest – preference of non-bank finance)

• However, no evidence of EMBs being more likely to not have investments needs

SME Finance Monitor Data Analysis

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SME Finance Monitor Analysis

ETHNICITYPOPULATION (England 2009)

Enterprise participation

rates (SME FM sample)

White 87.9% 92.20%Mixed 1.8% 0.97%Indian 2.6% 2.21%Pakistani 1.8% 0.43%Bangladeshi 0.7% 0.16%Other Asian 0.7% 0.42%All Asian or Asian British 5.9% 3.22%Black Caribbean 1.1% 0.25%Black African 1.5% 0.30%Other Black 0.2% 0.10%All Black or Black British 2.8% 0.65%Chinese 0.8% 0.23%Any other ethnic groups 0.8% 0.07%Ethnicity unstated   2.66%

All minority ethnics 12.1% 7.80%   

All ethnic groups 100.0% 100.0%

Caveat: Low enterprise participation rates by ethnic minorities means small EMB samples hence statistical estimates not quite as robust.

Policies to encourage higher enterprise participation rates would help the robust analysis of post-entry performance.

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• Significant sectoral differences• Compared to Firms in the agricultural sector:

SMEs in manufacturing and construction: more likely to not have investment needs (unpropitious borrowers)

Wholesale/retail: more likely to be declined, partial borrowers, debt-averse, and unpropitious borrowers than agricultural SMEs

Hotel and restaurant, and transport and communications SMEs more likely to be declined

Professional services (estate agencies, accountants, etc) and social and health services more likely to not have investment needs compared to agricultural SMEs

• Caveat: agricultural SMEs highly diversified. Many undertake (food) processing, others have hotels (B&Bs) and touristic businesses, and more recently green energy production.

SME Finance Monitor Data Analysis

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• Significant borrower-type differences attributable to size

• Compared to SMEs with over 250 employees:No significant differences in the likelihood of rejection

attributable to sizeAlso, SMEs with 50-99 employees and 100-250 employees

have no significant differences with the larger SMEs across all categories.

However, SMEs with 10-49 workers more likely be partial borrowers and debt-averse than the larger SMEs

Micro-enterprises (self-employed only, 1-9 employees) more likely than the larger SMEs to be partial borrowers, debt-averse and to be unpropitious borrowers (i.e. have no planned investments that require financing).

SME Finance Monitor Data Analysis

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• Age effectsCompared to firms over 10 years old, those

between 1-10 years more likely to be declined, partial borrowers, debt-averse, and unpropitious borrowers.

New SMEs under 1 year old have especially higher rates of rejection and debt-aversion.

• No large differences attributable to location (UK GOR level)

SME Finance Monitor Data Analysis

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• Ambition and ManagementSMEs with a formal business plan more likely to have

secured bank credit than to have had no planned investments.

In particular, SMEs with high growth ambitions especially expanding product range or expanding market reach more likely to have secured credit

SMEs with a qualified professional managing finances less likely to be rejected, borrow partially or not borrow at all

• Networks – SMEs that are members in an industry body or business group more likely to have investment plans and to secure credit

SME Finance Monitor Data Analysis

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• Encourage females and ethnic minority enterprise participation and in turn the pursuit of credit

• Different sectors have different borrowing needs and may need different financial products or credit arrangements. SMEs in wholesale and retail, hotel and restaurants, and transport and

communications with relatively higher likelihood of bank rejection should also consider exploring alternative sources of finance.

• The likelihood of rejection for micro enterprises is not any different from that of larger SMEs (250+ employees)

• However, a disinclination to apply for bank finance is quite high, in part due to “the fear of rejection” amongst microenterprises

• Absence of investment needs , and therefore no need for credit, is also significantly higher amongst micros than larger SMEs Microenterprises need to be (helped to be) more active in the development of

business opportunities and in turn the pursuit of bank finance.

Summary and implications

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• The risk of rejection is very high for start-ups and the incidence of debt-aversion (due to the fear of rejection) higher still. Alternative sources of finance may suit new firms more until they have

built up a sufficient record that banks can consider.

• Growth ambitions and articulate growth strategies enhance the likelihood of securing finance

• Professional handling of business finances also vital Through training and business counselling, microenterprises should be

encouraged to be ambitious but to also exercise strategic and professional managerial practices in pursuing such ambitions

• SMEs should also be encouraged to join industry bodies and business groups to be able to draw from the abundant resourcefulness of such networks

Summary and implications

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ERC WP3 Next steps

• Wealth and Assets survey data• Understanding Society/ British Household

Panel Survey• 30 case-studies of entrepreneurship in the

household context

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Thank you.