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American Journal of  Financial 
Technology and Innovation (AJFTI)

Entrepreneurial Growth under Financial Inclusion: A Firm-Level Analysis of  
Microenterprises in Abeokuta Metropolis

Kamilu A. Saka1*, Rasaki A, Raji2

Volume 3 Issue 1, Year 2025
ISSN: 2996-0975 (Online)

DOI: https://doi.org/10.54536/ajfti.v3i1.4584
https://journals.e-palli.com/home/index.php/ajfti

Article Information ABSTRACT

Received: February 12, 2025

Accepted: March 19, 2025

Published: October 25, 2025

This study applies the Two-Stage Least Squares (2SLS) estimator to analyse the impact 
of  financial inclusion on micro-firms’ employment growth in the Abeokuta metropolis. 
A survey research design was employed to randomly select 384 owners and managers of  
microenterprises in the study area. The traditional Ordinary Least Squares (OLS) produces 
underestimated and overestimated impacts of  financial inclusion indicators on firm 
employment growth due to endogeneity issues with the predictors. However, the observed 
2SLS estimation outcomes show that when the financial inclusion of  a microenterprise is 
instrumented with education level, efficient and consistent estimates are obtained. From 
the 2SLS analysis, a one percent increase in access to and availability of  the formal financial 
system leads to a corresponding 1.13 percent and 1.76 percent decrease in the employment 
growth of  the sampled firms at two significance levels (5% and 10%), respectively. The study 
then affirms that high access to and availability of  formal financial products and services 
significantly slow down employment growth among microenterprises in the study area. 
These results imply that increasing levels of  financial inclusion are not palatable for micro-
firms in the study area due to the significant financial challenges they face. It is recommended 
that bespoke formal financial products and services be provided for micro-firms, including 
addressing the daunting financial challenges these firms face. 

Keywords
2SLS, Employment Growth, 
Financial Inclusion, Instrumental 
Variable, Micro-Firm

INTRODUCTION
The importance of  financial inclusion is increasingly 
recognized among governments, and financial institutions, 
including international financial and development 
organizations like the International Monetary Fund 
(IMF), World Bank, African Development Bank, and 
others. With financial inclusion (FI), more previously 
financially excluded people and businesses can access 
and use financial products and services at affordable 
prices. Academics and industry stakeholders argue that FI 
offers gains to firms by decreasing liquidity or financial 
constraints, increasing investments and ensuring higher 
firm growth (Bricknell & Kertay, 2024; Nizam et al., 2020; 
Chauvet & Jacolin, 2017). Broadly, at the macro level, FI 
is believed to enhance employment generation, poverty 
reduction, contribute to economic growth and promote 
income redistribution (Anastesia et al., 2020; Park & 
Mercado, 2018b; Omar & Inaba, 2020). 
Despite wide recognition and importance of  financial 
inclusion to all economic agents including national 
economy micro, small scale enterprises, and smallholder 
farmers still face acute credit constraints in developing 
economies (Bricknell & Kertay, 2024; Global Findex, 
2021; African Development Bank, 2019; Chandio 
& Jiang, 2018; International Monetary Fund, 2020; 
Osabohien et al., 2020c; Mayorga et al., 2024; World Bank, 
2020). Even in rural areas of  developed countries or 
among low-income-oriented micro businesses in these 
economies, the credit gap is still an issue. In particular, 
credit gap financing is more evident in Nigeria where a 

large number of  micro and small-scale enterprises record 
a lack of  access to investible funds as a major business 
obstacle in the country (Anga et al., 2021; Anastesia et 
al., 2020; Ogidi & Pam, 2021; Agbim, 2020). Meanwhile, 
the credit financing gap that impedes a sustainable level 
of  entrepreneurship and small-scale enterprises’ growth 
and development in sub-Saharan Africa is a major 
financial inclusion concern in these countries, particularly 
economies where abject poverty is prominent (Triki & 
Faye, 2013). 
In Nigeria, previous studies that focus on the relationship 
between financial inclusion and entrepreneurship growth 
and development (Anga et al., 2021; Anastesia et al., 2020; 
Ogidi & Pam, 2021; Ibekwe et al., 2021; Anisiuba et al., 
2020) observed positive relationship between financial 
inclusion and entrepreneurial growth in the country. 
However, these previous studies suffer from certain 
empirical strategy flaws and weak measurements of  
variables, particularly regarding financial inclusion. For 
instance, given the data time, this study argues that macro-
level data employed by Anga et al. (2021); Anastesia et al. 
(2020); Ibekwe et al. (2021), and Anisiuba et al. (2020) 
for financial inclusion analysis for microenterprises is a 
misplaced priority and purely an empirical flaw. This is 
because a study establishing the macroeconomic impact 
of  financial inclusion needs sufficient long-time-series 
data on financial inclusion measures (Demirguc-Kunt 
et al., 2017). Again, using total trade sector output by 
Anastesia et al. (2020) to measure retail and wholesale 
productivity as a proxy for entrepreneurial growth is 

1 Department of  Banking and Finance, The Federal Polytechnic, Ilaro, Nigeria
2 Department of  Business Administration and Management, The Federal Polytechnic, Ilaro, Nigeria
* Corresponding author’s e-mail: kamilu.saka@federalpolyilaro.edu.ng



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less reliable for standard research that aims to establish 
the real impacts of  financial inclusion on micro-firm 
growth. This poor measurement of  variables could 
lead to wrong policy formulation on developing micro-
firm productivity through financial inclusion. This 
study employs an Instrumental Variable (IV) regression 
estimator to correct the endogeneity issue which has 
been grossly overlooked by most previous studies in the 
field. This study conducted in Abeokuta, a metropolitan 
city in Ogun State, Nigeria is organised as follows. The 
first section introduces the background, the research 
problem, the main issue with the previous works, and the 
context for the study. In the second section, a review of  
the literature was conducted. This section is followed by 
a discussion of  the methods adopted by the research in 
section three. Section four presents the results, interprets, 
and discusses the obtained findings from data analysis. 
The study concludes in section five and ends with 
recommendations. 

LITERATURE REVIEW
The issue of  financial inclusion is more important to micro 
and small enterprises and entrepreneurship at large. The 
reason is that most poor people or less privileged adults 
often engage in these kinds of  businesses. Thus, improved 
access to an array of  savings and risk mitigation products 
can help these theoretically financially excluded segments to 
be more active economically and contribute significantly to 
the economic growth of  a country (Triki & Faye, 2013). An 
entrepreneur is a person with the ability to transform his/
her potential into the creation of  business opportunities 
to earn a living while his/her productive effort is regarded 
as entrepreneurship. By and large, entrepreneurship is 
viewed in this study as those operated by microenterprise 
operators. In this manner, microenterprises are defined 
here as firms that employ not more than five (5) employees. 
This approach is similar to the business classification 
method by the World Bank (2014). 
In Nigeria, some strategies for financial inclusion have 
been designed by Regulatory Authorities, Development 
Organisations, and non-governmental organisations 
(NGOs) to promote and extend financial products and 
services to poor people, entrepreneurs, and micro and 
small-scale enterprises. According to Central Bank of  
Nigeria (2012), these strategies include Bank Verification 
Number (BVN), Digital Financial Services (DFS) 
initiatives, Agent Banking framework, National Collateral 
Registry, Know Your Customer (KYC) framework, Micro, 
Small and Medium Enterprises Development Fund (a 
sum of  ₦220 billion), Financial Literacy and Capital 
Market Literacy, a 5-year financial inclusion targets for 
commercial banks (2016 – 2020), innovative insurance, 
and the passage of  Pension Reform Act 2014 premised on 
the belief  that millions of  Nigerians in the informal sector 
will be financially included through pension contribution 
and investment.  Further, the seemingly numerous 
literature on financial inclusion measurement is yet to 
recommend a standard or comprehensive measurement 

approach for financial inclusion. It has been argued over 
time that such a standard measure is required to account 
for the coverage of  financial inclusion and monitor the 
progress of  policies on financial inclusion at both macro 
and micro levels. Even with few attempts that have been 
made to the development of  financial inclusion measures 
efforts have largely been made at the macro level for 
cross-country comparisons (Amidzic et al., 2014; Camara 
& Tuesta, 2014; Sarma, 2008; Sarma, 2010; Sarma, 2012; 
Sarma & Pais, 2011; Omar & Inaba, 2020) and for regions 
in Brazil (Banco Central Do Brasil, 2011) or country-
focused analysis (Anastesia et al., 2024; Mayorga et al., 
2024). The most intuitive idea on the financial inclusion 
measurement is provided by Sarma (2012). 
Sarma proposed that financial inclusion can be better 
understood if  viewed with a multidimensional lens by 
taking into consideration three important dimensions 
of  financial inclusion. To achieve his objective, Sarma 
developed the Composite Financial Inclusion Index (CFI). 
The CFI index by Sarma outlined these three important 
dimensions of  financial inclusion. These include 
accessibility, availability and usage of  financial services by 
members of  a country’s population. The Supply-Leading 
Hypothesis (SLH) is the theory underpinning the current 
study. SLH was pioneered by Schumpeter (1911) and 
derived more recognition from the works of  Mckinnon 
(1973) and Shaw (1973) who empirically confirmed a link 
between finance and economic growth. According to the 
principle of  SLH, the economic growth of  a country is 
facilitated by the level of  financial development due to 
its role in the real sector. This implies that high financial 
development enhances or promotes the growth of  an 
economy.  At the micro level, greater financial inclusion 
of  microenterprises would contribute to developing 
a country’s formal financial sector and consequently 
improve the productivity and growth of  micro and small 
businesses. When a country’s financial system deepens, the 
supply of  financial products and services will also increase. 
Thus, better accessibility of  formal financial products 
and services by underserved and excluded segments of  
the informal sector is critical to promoting micro-firm 
productivity in developing countries like Nigeria. 
Empirically, many studies have been conducted on the 
direction of  the relationship between financial inclusion 
and entrepreneurship growth in different continents and 
across countries. From Latin America, Mayorga et al. (2024) 
employed panel model regression to analyse longitudinal 
data drawn from 21,825 Columbian manufacturing 
microenterprises on the relationship between financial 
inclusion and firm growth. The study found that financial 
inclusion positively and significantly influences micro 
firms’ growth in Columbia. In the Middle East, Zreik, 
Marzuki, and Iqbal (2023) used a qualitative approach 
to analyse the effects of  microfinance on Chinese small 
business owners and discovered that microcredit is very 
important for supporting micro-business owners in 
marginalized Chinese communities. The research study 
highlights the significance of  financial inclusion through 



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microfinance to small business owners in China.  In Africa, 
Bricknella and Kertay (2024) employed content analysis 
to analyse primary data obtained through focus group 
discussions and in-depth interviews on the impact of  
financial inclusion on entrepreneurship in South Africa. 
The study establishes that greater accessibility of  financial 
services promotes entrepreneurship activities in the study 
area. The work of  Bricknella and Kertay reinforces the 
evidence provided by Anthanasius-Fomum and Pieter 
(2023) who found through quantile and ordered logit 
model regressions that financial inclusion when measured 
by access to financial services and savings practices has 
positive and noticeable impacts on the annual profits of  
micro firms in Eswatini.  
In the context of  Nigerian microenterprise, Anga et 
al. (2021) uncovered through Error Correction Model 
(ECM) analysis of  time series data that there is a 
positive relationship between financial inclusion and 
the performance of  the SME sector. This research 
study implies that financial inclusion promotes 
entrepreneurship in Nigeria. However, such evidence 
is macro-data based and may not accurately reflect 
real financial inclusion at the micro level.  The study 
by Anastesia et al. (2020) also used macro secondary 
data and the ECM approach to estimate the effects of  
financial inclusion on entrepreneurship growth in Nigeria 
and found that commercial bank branches have positive 
and significant consequences for the output growth of  
retail and wholesale subsectors in Nigeria. However, 
even though education (e.g. financial education) tends 
to influence the economic behaviour of  potential credit 
users to access and use formal services as established by 
Mayorga et al. (2024) no study from available literature has 
treated education as a possible cause of  endogeneity issue 
that can lead to misleading and biased result between 
financial inclusion and development of  micro-businesses 
particularly in developing countries like Nigeria. 
Consequent to the development, this study considers 
the possible incidence of  endogeneity concern in the 
statistical estimation process using an IV estimator. 
Again, this study attempts to fill the void in most past 
Nigerian studies on macro data usage. As stated earlier, 
macro data employed by Anga et al. (2021); Anastesia et 
al. (2020); Ibekwe et al. (2021), and Anisiuba et al. (2020) 
for financial inclusion analysis for microenterprises is 
a misplaced priority and purely an empirical flaw. As 
a result, this study uses primary data via a structured 
questionnaire to capture financial inclusion and growth 
of  entrepreneurship at the micro level. To overcome the 
entrepreneurship growth measurement issue, this study 
follows the approach of  Fowowe (2017) which had 
earlier been employed by Dinh et al (2012), and Aterido 
et al (2011) to measure microenterprise growth by using 
a three-year employment growth variable before the 
current research survey year.

MATERIALS AND METHODS
This study causal effect of  financial inclusion on 

entrepreneurship growth specifically microenterprises 
growth in Nigeria within the Supply Leading Hypothesis 
(SLH) framework.  The study adopts a survey research 
design. This research design allows a researcher to gather 
opinions and perceptions of  units of  analysis on certain 
measured variables of  interest in a research study. The 
study area in focus is Abeokuta Metropolis. The study 
city, Abeokuta, is the capital of  Ogun State, Nigeria. The 
ancient city is a commercial centre with a large number 
of  microenterprises including both formal and informal 
small outlets. 
Relatively, this study specifically focuses on formal 
microenterprises in the study area. In this study, formal 
microenterprises in the selected environment are those 
little capital-based (between 1 naira and 5 million 
naira) businesses registered with the Corporate Affairs 
Commission (CAC) and obtained business certificates 
as evidence. In other words, the total number of  all 
formal microenterprises in the study area represents the 
population. 
However, in terms of  the figure, the population size 
is unknown and infinite. This situation led to the 
researchers’ decision to use a sample size formula for an 
unknown population size as recommended by Krejcie 
and Morgan (1970). Consequently, a sample size of  384 
microenterprises was determined. These microenterprises 
are represented by firm owners or managers where 
appropriate. The study uses a systematic random sampling 
technique to select every fifth microenterprise approach 
during the observational data collection process. In line 
with the study’s goal, an empirical financial inclusion-
induced growth model based on the Supply-Leading 
Hypothesis is stated below.
EMGi= α+ β1 FICi+ εi                                                       ………….(2)
Where;
EMG= Employment growth;
EMGi= (EMGn-EMG(n-3))/EMGn; 
EMGn= firm employment level three years ago (2021) 
and EMG(n-3)= firm employment level in the current year 
(2024)
α = model intercept; 
FIC = Financial Inclusion; 
β1 = slope coefficient of  FIC; 
ε = error term; 
i = individual microentrepreneur.
Furthermore, relying on three dimensions of  financial 
inclusion as previously established in the literature review 
section equation (2) can be expanded in equation (3) as:
EMGi= α+ β2ACCi+β3AVLi+β4FAGi+εi                  ………(3)
Where;
ACC= Accessibility (financial inclusion dimension); 
AVL= Availability (financial inclusion dimension); 
FAG= Firm Age (control variable); 
β2- β4  are slope coefficients of  the three dimensions of  
financial inclusion and β2 = slope coefficient of  control 
variable.
Consequent upon equation (3), the study adopts 
educational level as an appropriate instrumental variable 



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to correct for possible endogeneity issues in an expanded 
equation (3). Without this practice, all slope coefficients 
in equation (3) will yield biased and unrealistic estimates 
as there is the possibility of  a correlation between the 
predictor (financial inclusion) and education level as part 
of  the residuals in equation (3). Hence, equation (4) is 
instrumented as:
EMG i=α+β 5ACCi+β 6AVLi+β 7FAG i+β 8EDLi+β 9 
FAGi+εi                                   ………….(4)
Where 
EDL = Education Level (the instrumental variable)
The instrumented equation (4) with educational level is 
intuitive for two reasons. First, it corrects the endogeneity 
issue in financial inclusion as the main predictor of  the 
study through the instrumental variable (EDL). Second, 
the equation accounts for all covariates that would have 
obscured the causal relationship between financial 
inclusion and the growth of  microenterprises in the study 
area. Furthermore, the study adopts a two-stage least 
squares method (2SLS) to estimate instrumental variables 
in equation (4). The first stage is to clean up by regressing 
each of  the endogenous variables in equation (4) on other 
predictors, the instrumental variable (EDL) and the control 
variable (FAG) being the study covariate. The procedures 
are contained in the following equations 5 to 6.

ACCi= α +β10AVLi+β11EDLi+β12FAGi+εi                           …(5)
AVLi= α + β13ACCi+ β14EDLi+ β15FAGi + εi                         …(6)
The econometric estimations of  equations 5 and 6 yielded 
predicted values of  ACC and AVL (ACC) and (AVL) 
which represent the exogenous parts of  ACC and AVL, 
respectively. In the second stage, the researchers replace 
ACC and AVL as the main dimensions of  financial 
inclusion in equation 3 (OLS Model) with (ACC) and (AVL) 
to estimate equation 8 (Instrumental Variable Model).
EMGi = α + π(ACC)i + (ρAVL)i + β16FAGi + εi                  …(8)
The researchers determine if  endogeneity occurs in 
realistic terms by comparing β2,β3,and β4 in equation 3 with 
π and ρ (causal effects) in equation 8. This comparison is 
conducted through the Hausman Test (Hausman, 1978). 
All statistical estimations are performed at three levels of  
significance (1%, 5% and 10%) with empirical expectation 
that β2, β3, β4, π, ρ, and δ yield positive coefficients.

RESULTS AND DISCUSSIONS
Presentation of  Results
This sub-section showcases the estimation outcomes of  
Instrumental regression. Information in Table 1 presents 
inferential estimations of  the study through traditional 
OLS and two-stage regression (IV) analyses.

Table 1: Two-stage Least Squares Regression (Instrumental Variable) Estimation
Predictor / Statistic Traditional OLS (DV: EMG) Second-stage OLS Regression

DV: ACC DV: AVL DV: EMG
ACC 0.17**

(0.08)
-0.12***
(0.04)

AVL -0.70***
(0.12)

-0.24***
(0.08)

FAG
2 -1.12***

(0.20)
0.91***
(0.11)

0.81***
(0.08)

-0.06
(0.37)

3 -1.96***
(0.36)

0.82***
(0.22)

0.69***
(0.15)

-4.48***
(0.58)

EDL 0.19***
(0.04)

0.09***
(0.03)

Constant 1.24***
(0.11)

-0.78***
(0.12)

0.63***
(0.08)

0.81***
(0.19)

(ACC) -1.13***
(0.27)

(AVL) -1.76***
(0.27)

No. of obs. 342 342 342 342
Model Fitness F(5, 336) 34.54*** 35.68*** 33.90*** 55.33***
R-squared 0.34 0.35 0.34 0.44
Endogeneity test
Durbin (score) chi2(1) 61.41*** 49.47***
Wu-Hausman F(1, 336) 73.53*** 56.82***
Instrument Validity F(1, 337) 20.68*** 10.20***



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Interpretation and Discussion of  Results
Furthermore, Table 3 reveals the outcome of  the 2SLS 
estimations performed with 342 observations after 
system adjustments. At the initial stage, traditional 
OLS was performed to estimate Equation 3 on the 
impacts of  financial inclusion on employment growth 
in microenterprises that ply their trade in the Abeokuta 
metropolis. The results show that ACC (accessibility) 
positively and significantly impacts the employment 
growth of  micro-firms in the study area. That is, a 1% 
increase in access to formal financial services and usage 
increases micro-firm employment growth by 0.17% and 
0.66% respectively at three significance levels. Again, the 
positive impact of  the accessibility (ACC) is significant at 
two significance levels (5% and 10%) among the selected 
microenterprises is obtained at all three significance 
levels.  In contrast, the standard OLS estimation shows 
that the availability (AVL) of  formal financial services 
has a negative but significant impact on the micro-firm 
employment growth (EMG) at the three significance 
levels. The result indicates that when AVL increases by 
1% the employment growth of  the study area micro-
firms decreases by 70 per cent. 
Firm age (FAG) with three sub-indicators (new firm, 
growing or matured firm) is used as a control variable in 
Equation 3 and Table 1 reveals that in the traditional OLS 
estimation, new firms (reference category coded “1”) 
significantly employ more workers during the research 
period than the growing firm (coded “2”) and mature 
firm (coded as “3”) by 1.12% and 1.96% respectively. One 
intriguing outcome of  the estimated traditional OLS is 
the high magnitude of  the impacts of  financial inclusion 
measures on firm employment growth. This incidence 
may be associated with a lack of  adequate information 
from observational data on the true exogeneity of  
conditions of  interest (financial inclusion). In other 
words, if  caution is not taken, this result may mislead the 
policymakers about the real effects of  financial inclusion 
on microenterprises growth in Nigeria using the study 
area as the frontier. Therefore, an efficient estimation 
is required for informed policy-making decisions on 
financial inclusion among micro-firms in Nigeria via the 
use of  education as an instrumental variable. The analysis 
is critical to ascertain if  financial inclusion measures 
(accessibility, availability and usage of  formal financial 
services) used by the study have high correlations with 
unobserved factors (error term) – an incidence of  
endogeneity. 
Consequently, the study uses “education” as an 
instrumental variable in Equations 5 and 6 where each 
predictor serves as an outcome variable explained by a set 
of  other predictors, instrumental variable (education) and 

the control variable (firm age).  These analyses represent 
the first stage of  the 2SLS estimation.  However, the 
significant results of  Durbin (score) and Wu-Hausman in 
columns 3 and 4 of  Table 1 confirm that the relationship 
between financial inclusion and employment growth of  
microenterprises in the study area is endogenous. This 
indicates a high correlation between financial inclusion 
and error terms in equations 3-5 specified in the 
methodology section. However, the instrumental validity 
tests show that the instrument used in each of  the two 
equations under the first-stage estimation is valid in two 
cases as F-statistic values are greater than 10 being the 
threshold. Thus, the 2SLS technique will produce more 
efficient and consistent estimates than the traditional 
OLS. Therefore, financial inclusion measures were then 
instrumented and new predicted values were created 
through the first stage. Subsequently, the predicted scores 
are then used to represent scores for the predictors in the 
second stage of  the 2SLS procedure.  
From the second stage estimation, accessibility (ACC hat) 
of  formal financial services is observed as a negative but 
significant predictor of  growth in the worker additional 
employment by microenterprises in the study area. By 
implication, a 1% increase in access to the formal financial 
system will significantly lead to a corresponding 1.13% 
decrease in the employment growth of  the sampled firms 
at three significance levels (1%, 5% and 10% respectively). 
The observed significant negative result contradicts 
the positive result obtained on accessibility under the 
traditional OLS. Again, it is shown in column 5 of  Table 
1 that the result obtained earlier from the classical OLS 
is overestimated. Thus, the standard OLS method yields 
misleading results on the impact of  micro-firm workers’ 
employment on access to formal financial services in the 
study area. 
Similarly, the second stage result in column 5 of  Table 1 
further reveals that the predicted score of  formal financial 
services and products for availability produces a negative 
but significant impact on the worker employment growth 
among the population of  microenterprises in the study 
area. It shows that a 1% increase in the rate of  availability 
of  formal financial services and products will significantly 
cause a 1.76% decrease in the employment growth of  
micro-firms in the Abeokuta metropolis. However, 
when compared, the result confirms that standard 
OLS produces an underestimated result on the true 
impact of  formal financial system services availability 
on employment growth among micro-businesses in the 
study area. This evidence also corroborates biased and 
inconsistent estimation by the traditional OLS and thus 
buttresses the relevance of  the 2SLS approach used by 
the current study. The test of  overall model significance 

Notes: (1) Variables such as ACC (Accessibility) and AVL (Availability) are the endogenous predictors; (2) FAG (Firm Age) as a 
categorical control variable (covariate)is measured on three levels with “young firm” ((less than 3 years) coded as 1 (the reference group), 
“mature firms” (above 3 years to 6 years) coded as 2 and “senior firms” (7-10 years) coded third category; (3) Standard errors are 
contained in the parentheses; (4) Significance levels are represented ***(1%), **(5%) and *(10%) respectively. 
Source: Authors’ Computations from STATA 12.1 Outputs (2025)



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shows in Table 1 that the 2SLS outperforms the standard 
OLS approach. Again, in terms of  R-squared comparison, 
financial inclusion from the 2SLS model (second 
stage) explains 55.33% of  the total variance in worker 
employment growth among microenterprises in the study 
area, whereas in the standard OLS, the total amount of  
variation explained was 34 per cent. Therefore, using 
2SLS in this study is deemed appropriate and efficient.
In the real sense, the 2SLS estimation outcomes imply 
that accessibility and availability of  formal financial 
services are negative but significant predictors of  growth 
in the additional employment by microenterprises in the 
study area.  This result is surprising and inconsistent with 
the study’s prior expectations. This is because the study’s 
theoretical foundation (Supply-Leading Hypothesis) 
attests to the positive contribution of  financial 
development to the growth of  an entity’s economy. 
More so, such evidence contradicts previous findings 
by Bricknella and Kertay (2024); Mayorga et al. (2024); 
Zreik et al. (2023); Anga et al. (2021); and Anastesia et al. 
(2020); However, this unexpected result might not be 
unconnected with the likely insufficient account balance 
that cannot sustain a firm’s operations for a long period 
or limits its expansion. Firms with enough money in the 
bank account or any financial institution account tend 
to desire expansion and modernization of  operations 
that can ultimately lead to the employment of  marginal 
workers. Thus, an increase in the number of  accounts 
with different financial institutions without adequate cash 
balance or access to multiple loans may drain meagre 
financial resources of  micro-firms and lead to loss of  
workers as salaries may not be sustained over time. 
Again, numerous challenges often experienced by 
microenterprises in obtaining finance may prevent them 
from benefiting from the higher availability of  formal 
financial products and services. When these financial 
challenges faced by micro-firms are not effectively 
addressed access to more available formal financial 
services may also drain their resources as many providers 
can request commitment balance in accounts owned 
by these micro-firms. More importantly, the failure of  
previous studies to instrument financial inclusion variables 
with user education in their respective estimations could 
have also contributed to the observed different results. 
However, state-wide or national datasets can be used to 
confirm these observed results among microenterprises 
at the state or national level. 

CONCLUSION
This study uses a 2SLS regression estimator to examine 
342 cross-sectional data on the relationship between 
financial inclusion and firm employment growth 
among microenterprises in the Abeokuta metropolis. 
The estimation results show that, in the absence of  
education as an instrument variable, a high correlation 
occurs between financial inclusion and other extraneous 
variables (captured by the stochastic term) if  standard 
OLS is only applied. Based on the factual evidence from 

2SLS analysis, this study affirms that high access to and 
availability of  formal financial products and services 
significantly slow down employment growth among 
microenterprises in the study area. The methodological 
implication of  this study is that efficient and consistent 
estimates of  the relationship between financial inclusion 
and firm job growth are guaranteed when Instrumental 
Variable (IV) regression or 2SLS is considered. Again, 
this study provides a better opportunity for formal 
financial services to gain significant empirical insight 
into the appropriate financial inclusion dimensions that 
facilitate employment creation among micro-firms. It is 
recommended that bespoke formal financial products 
and services be provided for micro-firms, including 
addressing the daunting financial challenges these firms 
face. 

Acknowledgement
This work is supported by the Nigeria Tertiary Education 
Trust Fund (TETFUND) Institution-Based Research 
(IBR) Grant in 2024.

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