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Structural Change and Economic Dynamics 55 (2020) 177–189

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Structural Change and Economic Dynamics

journal homepage: www.elsevier.com/locate/strueco

Access to finance among small and me dium-size d enterprises and job

creation in Africa

Zuzana Brixiováa , ∗, Thierry Kangoye

, Thierry Urbain Yogo

University of Economics, Prague, W. Churchill Sq. 1938/4, 130 67 Prague 3 – Žižkov, Czech Republic

African Development Bank

World Bank

a r t i c l e i n f o

Article history:

Received 15 January 2020

Revised 15 July 2020

Accepted 27 August 2020

Available online 5 September 2020

JEL codes:

D22

Keywords:

Entrepreneurship

Financial inclusion

Employment

Propensity score matching

a b s t r a c t

In the past decade inclusive growth, that is job-rich growth, has topped the policy agenda in developing

countries. This paper investigates how the access to finance affects employment in small and medium-

sized enterprises (SMEs) in Sub-Saharan Africa. It first presents a model where firm creation requires

entrepreneurial search and paying the start-up costs, while the firm’s size in terms of employment de-

pends on the access to credit. Under the financial market imperfections, access to credit can be a binding

constraint on firm entry and employment even when the banks have sufficient liquidity. Using an impact

evaluation-based approach on firm-level data from 42 African countries, we show that SMEs with access

to formal financing create more jobs than firms without access, with employment in firms having ac-

cess to more affordable and larger loans growing the fastest. The impact of access to finance is stronger

for firms in manufacturing than in services, pointing to sectoral targeting of finance as a possible policy

supporting industrialization.

1. Introduction

Employment is a key channel through which growth translates

into poverty reduction. However, many developing countries, in-

cluding in Africa, have grown rapidly over the past decades with-

out a substantial reduction in poverty. Recent analysis suggests

that the poverty rate in African countries is expected to decline

only to about 25% by 2030 while in the other regions of the

World it will drop to less than 3% ( Bicaba et al., 2017 ; Beegle and

Christiansen, 2019 ). Among the factors holding back poverty re-

duction is the lack of access to finance for small and medium-

sized enterprises (SMEs), which are among the largest contrib-

utors to job creation in developing countries ( Blancher, 2019 ;

R The authors thank Jan Babecky, Mina Baliamoune and Leonce Ndikumana for

earlier discussions and two anonymous reviewers for helpful comments that im-

proved the paper. This is substantially revised and rewritten version of the IZA Dis-

cussion Paper No. 6193.

∗Corresponding author: University of Economics, Prague. Mailing address: Uni-

versity of Economics, Prague, W. Churchill Sq. 1938/4, 130 67 Prague 3 –Žižkov,

Czech Republic

E-mail address: zuzana.brixiova@vse.cz (Z. Brixiová).

Ghassibe et al., 2019 ).

1 A report from the International Financial

Corporation (2017) estimated that in developing countries, more

than 40% of SMEs have at least partially constrained access to ex-

ternal finance, while about 20% face heavy constraints.

Policymakers and researchers have recognized that financial in-

clusion is a key dimension as well as a strong driver of inclusive

growth. Access to financial services could also boost employability

and women labor participation by providing them with the means

to invest in education and training ( Asongu and Odhiambo, 2018 ;

Asongu et al, 2020 ). Beck et al (2005) showed that relaxing finan-

cial constraints positively impacts SMEs’ employment growth. This

effect is lar ger the smaller the firm, the more labor-intensive its

production structure, and the larger its inherent need to finance

working capital ( Dao and Liu, 2017 ). However, the access to credit

for new firms in Africa is limited by weak property rights, gaps in

financial auditing as well as by the lack of financial skills among

entrepreneurs. Several studies also underscored that small firms,

1 Given the high prevalence of extreme poverty in Africa, we focus mostly on in-

clusive growth that is absolute pro-poor, that is, brings about reduction in absolute

poverty. In the policy recommendations in the concluding section, we also discuss

policies that would lead to relative pro-poor growth, that is, bring

about reduction

in inequality. These definitions of inclusive growth are provided in, for example,

Asongu and Nwachukwu (2017) .

https://doi.org/10.1016/j.strueco.2020.08.008

178 Z. Brixiová, T. Kangoye and T.U. Yogo / Structural Change and Economic Dynamics 55 (2020) 177–189

which consistently report higher growth obstacles than medium-

sized or large firms, are financially more constrained than larger

ones and less likely to access the formal finance.

Although highly relevant, the literature so far has focused

mostly on a large set of developing and emerging market

economies which may differ markedly in their specificities of the

labor market and access to finance by SMEs.

2 In contrast, this

study focuses on Africa, which is the poorest continent in the

world and the most excluded in terms of access to finance partly

due to the underdevelopment of its financial system. In addition,

the widespread informality in the labor market induces a low level

of permanent jobs. Not distinguishing between permanent and

non-permanent jobs could lead to the overestimation of the im-

pact of access to finance on employment.

Another feature of African countries is the lack of collateral due

to issues related to land ownership and leasing. The lack of collat-

eral worsens financial exclusion and pushes SMEs to resort to the

informal finance (credit from suppliers, advances from customers

or friends and relatives).

This paper contributes to closing the knowledge gap on link–

ages between the access to finance and job-rich growth in Africa.

Specific questions that the paper seeks to answer are: (i) Does ac-

cess to finance impede the creation of new firms and the num-

ber of jobs that these firms generate? (ii) Are there sectoral differ–

ences in the impact of the access to finance on firm creation and

employment? Towards this goal the paper examines these two di-

mensions of inclusive growth – financial inclusion and job creation

–both theoretically, in a search model and empirically, by inves-

tigating the impact of access to finance on job creation in SMEs.

The focus is on privately-owned SMEs, which are the most finan-

cially excluded even though they are a key generator of employ-

ment. The question is highly relevant as evidence suggests that up

to one third of private firms in Africa report limited access to fi-

nance as a major constraint, while the private sector generates es-

timated 90% of jobs on the continent ( McKinsey & Company, 2012 ).

In addition, the paper provides a granular analysis of the impact of

access to finance on job creation while distinguishing between the

formal and non-formal sources of finance as well as accounting for

the size and maturity of the loan, and the collateral. Another con-

tribution of the paper is that it examines sectoral differences, in

particular between manufacturing and services, in the impact of

access to finance and job creation in Africa.

With exception of Aghion et al. (2007) , the literature on the

SME access to finance is by and large empirical.

3 In contrast,

this paper first presents a model where firm creation depends

on matching potential entrepreneurs with productive opportuni-

ties and overcoming start-up costs, while the jobs generated by

the firm hinge on the availability of capital and hence the access

to credit. Limited access to credit due to the lack of collateral ham-

pers capital accumulation especially among nascent entrepreneurs

in African countries, where financial frictions stem, broadly, from

weak legal frameworks and limited transparency in financial ac-

counting. The analysis shows that the constrained access to credit

and hence to investment capital, which can emerge even when

the financial sector has liquidity, is a binding impediment to en-

trepreneurship.

The model is tested on a sample of firm-level data from 42

African countries during the 2006 –2009 period, utilizing a re-

search design based on propensity scores-matching. The match-

2 The exceptions include Baliamoune-Lutz et al. (2011) , Grimm et al. (2012) ,

Fowowe (2017) , and Quartey et al. (2017) .

3 In contrast to our paper, Aghion at al. (2007) do not cover firms

or aggregate

employment.

ing techniques are increasingly utilized in assessing the impact of

an exposure to a specific situation or to an experiment (called

the “treatment ”in the impact evaluation literature) on a selected

outcome variable. The results indicate that access to financial ser–

vices (loan financing) positively affects growth in the number of

firms’ permanent employees. Specifically, larger loans as well as

loans with smaller collateral size and longer maturities are associ-

ated with a stronger and more significant impact on employment.

Moreover, the empirical analysis shows that access to finance has

a greater impact on firms in the manufacturing sector than those

in services.

The paper is organized as follows. After this introduction, the

next section provides a review of the literature, with a focus on

the determinants of entrepreneurship and the impact of institu-

tional and policy reforms on entrepreneurship. Section 3 presents

the theoretical model that underpins the empirical analysis.

Section 4 contains the empirical analysis and the regression results,

while Section 5 summarizes the findings and discusses policy im-

plications.

2. A review of the literature

This paper builds on the literature on the role of policies in pro-

moting productive entrepreneurship. Baumol (1990) underscored

that the extent of entrepreneurship across societies is mostly given.

Policies should thus encourage potential entrepreneurs to enter

highly productive rather than less productive or even destruc-

tive activities. Policymakers thus strive to overcome both finan-

cial and non-financial constraints, which have impeded produc-

tive entrepreneurship across Africa and emerging market countries

( Baliamoune-Lutz et al., 2011 ). However, productive SMEs in the

formal sector in African countries have been hampered by numer–

ous non-financial constraints, including low revenue collection and

the lack of social protection, as highlighted in Auriol (2014) or by

the lack of skills ( Brixiová, 2010 ).

SME financing has attracted considerable attention from pol-

icymakers, researchers and development partners ( Beck and

Demirguc-Kunt, 2006 ; Fowowe, 2017 ; Quartey et al., 2017 ; Dao and

Liu, 2017 ; Asongu and Odhiambo, 2018 ; Asongu et al, 2020 ).

Within the literature on the constraints to productive en-

trepreneurship, this paper builds on the stream emphasizing the

limited access to credit due to either functioning of commer–

cial banks, institutional imperfections or entrepreneurs them-

selves. The topic has been widely covered for the advanced

economies. Several reports on UK SMEs have emphasized the

lack of competition in the supply of banking services to SMEs

( Cruickshank, 20 0 0 ; Independent Commission on Banking, 2011 ).

Siedchlag et al. (2014) and European Commission (2014) docu-

mented that small and young firms in the EU have more diffi-

culty than other firms to obtain bank credit, even if their financial

performance is the same, pointing to inefficiencies in the market

for bank credit. The limited access to credit hampers firms’ long-

term performance. Utilizing an SME panel for 12 European coun-

tries during 2014 –2016, Gomez (2018) showed negative effects of

4 Auriol (2014) showed that a low level of taxation and the lack of social protec-

tion that ensues have damaging consequences on the development of the formal

sector, and thus limit firm growth. The low level of tax collection can incentivize

the government to limit competition in the formal private sector, creating rents

that can be appropriated through entry fees and profit taxes. Moreover, because of

the lack of social protection, the local entrepreneurs in the formal sector have the

social obligation to subsidize their family including through employment, making

their firms less efficient than those of outsiders and ultimately discouraging local

entrepreneurship.

Z. Brixiová, T. Kangoye and T.U. Yogo / Structural Change and Economic Dynamics 55 (2020) 177–189 179

credit constraints on fixed asset investments, and a subdued im-

pact on firm growth and working capital.

The literature has extensively discussed the links between en-

trepreneurship and small firms’ growth constraints and their lim-

ited access to financial services. Beck et al. (2005) examined the

impact of financial constraints on SMEs’ growth and found that fi-

nancial obstacles are significantly and negatively linked to firms’

growth rate, with the smallest firms being consistently the most

adversely affected. Evidence has also shown that small firms con-

sistently report higher growth obstacles than medium-size or large

firms ( Schiffer and Weder, 2001 ; Beck et al., 2005; Beck and

Demirguc-Kunt, 2006 ). Berger and Udell (1998) and Galindo and

Schantiarelli (2003) have shown that both in developing and ad-

vanced countries, small firms have a more limited access to finance

and are more growth-constrained than their large firms coun-

terparts. Using firm-level survey data, Ayyagari, Demirguc-Kunt,

and Maksimovic (2008a) and Ayyagari, Demirguc-Kunt, and Mak–

simovic (2008b) found that access to finance is firmly linked to

the performance of firms. They also evidenced that entities with

access to formal financing grow faster than those with access to al-

ternative sources of financing. This evidence is supported by other

studies that show that financially-included firms tend to have a

more efficient allocation of their asset portfolio (Claessens and

Laeven, 2004; Ayyagari, Demirguc-Kunt, and Maksimovic, 2007 ). In

the same vein, Beck et al. (2005) provided evidence that higher ob-

stacles faced by smaller firms translate into a slower growth, with

small firms’ financing obstacles having almost twice the impact on

their annual growth as compared with large firms.

In the past decade, several studies on credit constraints in

emerging market countries have been published, with several

linking credit constraints with firm creation and performance.

Aghion, Fally and Scarpetta (2007) showed theoretically and em-

pirically – analyzing data from 16 industrialized and emerging

economies –that access to finance matters most for the en-

try of small firms and helps new firms expand if successful.

Fowowe (2017) , who examined the impact of access to finance

with firm-level data in 30 African countries drawing on subjective

measures of financing access, found that financing is key for firm

growth. Quartey et al. (2017) found that SMEs’ access to finance in

the West African sub-region is strongly impacted by factors such

as firm size, ownership, strength of legal rights and depth of credit

information, firm’s export orientation and managerial experience.

Formality was also found to impact strongly access to credit by

SMEs.

Fraser et al. (2015) emphasize that research on entrepreneurial

financing needs to go beyond the traditional supply-side bot-

tlenecks and examine the role of entrepreneurial cognition,

motivation, stage of the firm life-cycle and ownership type

in the firms’ access to finance and performance. Similarly to

Aghion et al. (2007) , this paper examines the effects of credit con-

straints on the entry of new firms and the expansion of successful

businesses. However, we focus on a sample of 42 African coun-

tries, in contrast to 16 industrial and emerging market countries

covered in their study. In African countries, financial constraints to

entrepreneurship are amplified by unclear property rights and re-

strictions on using assets such as land as collateral. To reflect these

constraints, the framework presented below shows how credit con-

straints slow down private sector development.

5 Grimm et al (2012) analyzed capital stocksofSME in low-income countries and

found that entrepreneurs’ risk attitudes impact the stock levels, in addition to credit

constraints.

6 Emerging market countries covered were Hungary, Romania, Slovenia, Ar–

gentina, Chile, Colombia and Mexico.

3. The model

The model builds on Brixiová and Kiyotaki (1997) , Aghion et al.

(2007), and Baliamoune-Lutz et al. (2011) . The key differences of

the framework in this paper are (i) a greater emphasis on the fi-

nancial sector imperfections, including the lack of savings oppor–

tunities and (ii) the focus of the analysis on the link between

the credit constraints and firm job creation and size. The em-

phasis on the links between credit constraints and the firm size

in terms of employment also distinguished this framework from

that of Aghion et al. (2007) , where the authors do not explicitly

model employment dynamics. Finally, while our model is micro-

based and underpins the empirical testing at the firm level, it also

allows aggregation and hence has macroeconomic implications in

terms of the aggregate output, employment, labor productivity and

inequality in income.

Our model is highly relevant especially for low-income African

countries where the productive private sector has been emerging

often amid an underdeveloped financial sector, in particular the

weak enforcement laws, which contribute to high collateral re-

quirements. At the same time, long-term tangible assets that could

serve as collateral are limited, in part due to unclear property

rights. By reflecting these facts, the framework below is consistent

with a situation in many transition and African countries where

the financial sectors are dominated by banks and binding credit

constraints co-exist with excess liquidity ( Brixiová and Kiyotaki,

1997 , Baliamoune-Lutz et al., 2011 , Beck et al., 2011 ).

The economy is populated by large number of infinitely lived

entrepreneurs and workers with the population normalized to one.

The population shares for entrepreneurs and workers are μand 1-

μ, respectively. Entrepreneurs are of two types, φand 1- φ: φis

the share of those endowed with high levels of net worth (a

) and

(1- φ) is the share of entrepreneurs with low levels of net worth

( a

), where a

> a

> 0 . The net worth, a

, i = h, l, is entrepreneur–

specific and constant as entrepreneurs consume their profits each

period, reflecting limited savings and investment options for SMEs

in Sub-Saharan Africa. Both entrepreneurs and workers have risk

neutral preferences in consumption, c. For workers the consump-

tion in each period depends on the wage, w , when they work for

firms in the formal sector or on income b from self-employment

in the informal sector.

7 For entrepreneurs it depends on the profit

from running a firm, π, which is fully consumed each period or on

the income, ω, from self-employment in the informal sector.

The entrepreneurs of type i = h, l search for a business opportu-

nity at cost d( x

) = x

/ 2 γunits of the consumption good per unit

of time, where γ> 0is the parameter of search efficiency. The en-

trepreneur of type i then finds a business opportunity according to

a Poisson process with the arrival rate of x

and produces output

in the formal sector with labor n

, business capital z and physical

capital k

according to the following production function:

1 −α(z k

)

α(

)

1 −α(1)

where α, 0 < α< 1 , is the share of the total capital in the output.

The gross profit i

of an entrepreneur i with net worth a

who em-

ploys capital k

i and labor n

i can be expressed as:

i

= ma x

(

−w n

)

= R (K) k

i (2)

where K =

∫

di is the aggregate capital and R (K) =

1 −αz w

−1( 1 −α) /αis the rate of return on investment for an in-

dividual entrepreneur; it is decreasing in the aggregate capital

7 The workers are working either in the formal private sector (in firms created

by the entrepreneurs) or in the informal sector, which we interpret as household

production. In either activity, they receive wage w .

180 Z. Brixiová, T. Kangoye and T.U. Yogo / Structural Change and Economic Dynamics 55 (2020) 177–189

stock.

8 If the rate of return on capital exceeds the real interest

rate, R ( K ) > r , the entrepreneurs who find a business opportunity

will borrow up to their credit limits and use their entire net worth

as collateral.

The entrepreneurs finance their project from own resources

(net worth) and by borrowing, using the net worth as collateral.

However, the output can be used only for consumption and the

capital (including the net worth) is entrepreneur-specific. This im-

plies that without the entrepreneur’s specific know-how, the liq-

uidation value of the net worth for outsiders is smaller than for

the entrepreneur. Hence in the event of the entrepreneur’ s de-

fault on borrowing, the lenders can recover only θproportion of

the value of the net worth

and restrict lending to an entrepreneur

i, b

, to the amount not exceeding this collateral value of the en-

trepreneur’s net worth, a

≤θa

i i = h, l (3)

where k

= a

+ b

i reflects that the entrepreneur i finances capital

( k ) from both borrowing ( b )and own net worth ( a ). Entrepreneurs

consume their profits, that is: c = y −wn −rb, w here c is the pri-

vate consumption, wn is the wage cost, and r is the real interest

rate on debt (which in equilibrium is equal to the rate of time pref-

erence).

When K < ¯

K , which is a common situation in developing coun-

tries, the rate of return on capital is above the real interest rate

on debt, R ( K ) > r . The entrepreneurs thus borrow up to the credit

limit for capital investment, i.e. the credit constraint is binding and

= θa

i and k

= ( 1 + θ) a

i The entire net worth is then spent on

the down-payment for capital. From (1) –(3) follows that firm em-

ployment rises with borrowing and hence with the net worth:

(

) (

)

−1

α= z

(

1 + θ)

(

)

−1

αand n

= f

(

z, a

, w, θ, α)

(4)

Private firms are destroyed at exogenously given rate δ> r .

Omitting the time subscripts and denoting V

i as a present dis-

counted value of an entrepreneur of type i (that is an entrepreneur

with net worth of value a

) searching for a business opportunity

and J

as an entrepreneur of type i, that is an entrepreneur running

a firm with net worth a

, respectively. The corresponding Bellman

equations are:

r V

= ω + max

−x

/ 2 γ+ x

[

−V

]

+ ˙

i = h, l (8)

r J

= πi

+ δ(

−J

)

+ ˙

i = h, l (9)

where r i s the discount rate. Eq. (8) states that a searching en-

trepreneur i receives the income from self-employment, b , finances

cost of search of x

/ 2 γand expects to open a firm at rate x

, where

i denotes change in V

over time, i = h, l . Put differently, (9) states

that the return from searching for a business opportunity equals

the expected return from running a business with the net worth

i net of search costs. Eq. (8) states that an entrepreneur of type

i running a firm receives profit πi

and expects the firm to exit at

rate δ. Again, ˙

i denotes change in J

i over time, i = h, l. The utility-

maximizing search intensity x

, which equates the marginal cost of

search with the expected marginal benefit, is derived from differ–

entiating Eq. (7) and given by:

= γ(

−V

)

i = h, l (10)

Defining the shadow value of the business opportunity of an

entrepreneur with net worth a

as = λi

= ( J

−V

) , i.e., the dif-

ference between the present discounted value of running a firm

and searching for a business opportunity, Eq. (9) can be written as

/γ= λi . The equilibrium conditions can then be described as:

λi

(

γ/ 2

)

λ2

(

r + δ)

λi

−(

πi

−b

)

i = h, l (11)

= γλ

μφi

−m

−δm

i = h, l (12)