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Volume 13 Issue 1, January -March 2025 

ISSN: 2836-9416 

Impact Factor: 6.41 

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VENTURE CAPITAL FINANCING AND PERFORMANCE OF 

SMALL AND MEDIUM SCALE ENTERPRISES IN NIGERIA 

 
Dr. Amakor, Ifeoma Chinelo and Chimarume Blessing Uba 

1Department of Banking and Finance Nnamdi Azikiwe University, Awka 

Email: ic.amakor@unizik.edu.ng / chimarume@gmail.com 

Phone: 08036222388 / 08168097651 / +15066398890 
DOI: https://doi.org/10.5281/zenodo.15296429 

 

Abstract: This study examined the relationship between venture capital financing (VCF) and 

performance of Small and Medium-scale Enterprises (SMEs) in Nigeria from 2011 to 2023. The study 

used SMEs profitability, job creation of SMEs and the number of SMEs to proxy performance of SME’s. 

The relevant data was sourced from Central Bank of Nigeria (CBN) statistical bulletin and World Bank 

database and analysed using unit root test and least square regression. The result revealed that SMEs 

profitability and number of SME’s, exhibit significant relationship with venture capital financing, while 

non-significant relationship exist between venture capital financing and SME performance in terms of 

job creation. The growth in profitability and number of SME’s without growth in job creation is viewed 

as lopsided growth pattern. The study advocates for SME’s extensive and sustainability growth policies 

from the Federal Government of Nigeria in order to enhance job creation among the SME’s.  

Keywords: Venture Capital financing, SME’s profitability, Number of SME’s, Job creation  

 

INTRODUCTION 

The pursuit of long-term economic growth and development has reemphasized the importance of 

financial access, particularly for small and medium-sized enterprises (SMEs), which are regarded as 

critical drivers of economic growth, employment generation, and innovation in both developed and 

developing economies  

Small and Medium Scale Enterprises (SMEs) are businesses or enterprises that operate on a smaller 

scale, with limited investment and turnover (Aremu & Adeyemi, 2011). These enterprises typically have 

fewer personnel and generate lower revenues compared to larger enterprises (Organization for 

economic cooperation and development OECD, 2021). As defined by CBN small and medium scale 

enterprise is any enterprise with a maximum asset base of N500 million (excluding land and working 

capital). This decline has severely impacted key sectors such as wholesale and retail, ICT, and 

manufacturing, affecting employment and overall economic growth. (PWC 2020) 

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American Research Journal of Economics, Finance and Management 

Volume 13 Issue 1, January -March 2025 

ISSN: 2836-9416 

Impact Factor: 6.41 

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Small and Medium scale Enterprises are considered to be one of the principal driving forces in 

economic development of both developed and developing nations, as they generate employment, help 

in diversifying the economic activity and makes a significant contribution to export trade through 

utilization of locally available resources, absorbing labour, penetrating new market and generally 

expanding the economy in creative and innovative way (Usman, Isah &Tanko, 2018). However, if SME’s 

will remain relevant in achieving social economic development in any economy, they need productivity 

increase which can be achieved through financing (Akingnnola, 2011).  

Nevertheless, one of the major challenges faced by the SME’s in Nigeria is inadequate funding, 

characterized by their inability to access credit from many financial institutions due to their stringent 

lending policies, making most of them to rely on their retained earnings for their investment, hence 

difficult to achieve growth and sustainable development (Mboto, Offiong and Udoka 2018). To that 

effect, venture capital finance has emerged as a crucial source of funding for SMEs, allowing them to 

innovate, grow, and compete in a more globalized environment.  

Venture capital financing are capital provided by firms who invest alongside management in young 

companies or early start-up businesses that are not quoted on the stock market in exchange for stock 

or shares in the future (Biney 2018). The origins of venture capital can be traced back to the post-World 

War II era, when investors began to realize the potential of funding high-risk, high-reward projects 

(Daramela, 2012). 

The first VC firm, American Research and Development Corporation (ARDC) was founded in 1946 by 

Georges Doriot. ARDC’s most notable investment was in Digital Equipment Corporation, which 

provided a massive return on investment and helped establish the potential of VC funding (Mike Mc 

Peak 2023). 

These institutions are designed to provide medium and long term financing, with provision of technical 

and managerial services, in addition to monitoring effectively the progress of the investee firms (Effiom 

& Edet, 2018). If properly managed, Venture capital has the tendency to encourage entrepreneurship, 

job creation, and diversification of the economy (Nigeria corporate finance, 2024). Though the role of 

VCs is well documented in western developed economies, limited attention has been paid to it by SMEs 

in emerging markets like Nigeria (Jiang et al, 2014), thus the need for this study. 

Again, previously, researchers like Ojo and Adegboye (2020) focus primarily on the financial benefits 

of venture capital investments, while Eniola (2021) considers the role of VC in providing financial 

backing to SMEs, without thoroughly investigating its impact on job creation, and operational 

sustainability and profitability. Thus, this study seeks to fill these gaps by ascertaining the effect of 

venture capital financing on SMEs profitability, examining the effect venture capital financing on job 

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American Research Journal of Economics, Finance and Management 

Volume 13 Issue 1, January -March 2025 

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creation of SMEs and determining the effect of venture capital financing on the number of SMEs in 

Nigeria from 2011 to 2023.    

REVIEW OF LITERATURE 

Venture Capital Financing 

Venture capital (VC) financing refers to investment provided by venture capitalists to startups and 

small businesses with high growth potential but high risk. Venture capitalists typically provide funding 

in exchange for equity in the company, offering not only financial resources but also strategic guidance 

and managerial support. This funding is vital for startups that lack access to traditional forms of 

financing, such as bank loans or public equity offerings (Davies & King, 2018). 

The venture capital process generally involves several stages, beginning with seed capital and 

progressing through early-stage and growth-stage investments. Seed capital is the initial funding 

provided to help startups develop their business idea into a viable product or service. Early-stage 

investments support companies that have developed a prototype and are beginning to enter the market, 

while growth-stage investments are intended to scale operations and expand market reach 

(Chemmanur & Fulghieri, 2019). Each stage involves different levels of risk and return, with venture 

capitalists carefully evaluating potential investments based on a company's growth prospects, market 

potential, and management team (Zhang & Jang, 2020). 

One of the important aspects of venture capital financing is the evaluation process. Venture capitalists 

use a combination of quantitative and qualitative criteria to assess potential investments. Financial 

metrics such as projected revenue growth, profit margins, and return on investment are critical factors, 

but qualitative aspects such as the entrepreneur's experience, market opportunity, and competitive 

landscape are also significant. This comprehensive evaluation helps venture capitalists identify 

promising startups with the potential for substantial returns (Black and Gilson, 2019). 

Venture capitalists often take an active role in the companies they invest in, providing strategic advice, 

mentoring, and access to their networks. This involvement can significantly enhance the likelihood of 

a startup's success by improving its business model, market strategy, and operational efficiency. 

Furthermore, venture capitalists may also influence key business decisions, including hiring practices, 

product development, and market entry strategies (Emerah et.al, 2020). 

The impact of venture capital financing extends beyond individual startups to the broader economy. 

Venture capital-funded companies are often at the forefront of technological innovation and economic 

growth. Firms backed by venture capital are more likely to introduce new products and services, create 

jobs, and contribute to economic development. The presence of a robust venture capital sector can 

stimulate entrepreneurial activity, attract additional investment, and foster a culture of innovation 

(Hsu, 2020). 

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Venture capital investments are inherently risky, with a significant proportion of startups failing to 

achieve their growth targets. Additionally, the expectations and demands of venture capitalists can 

sometimes lead to conflicts over business direction and control. Effective communication and 

alignment of goals between investors and entrepreneurs are crucial for mitigating these risks and 

ensuring successful outcomes (Baldwin and Rafiqzzaman, 2020). 

Effects of Venture Capital Financing On SMEs Profitability 

Venture capital financing often provides the necessary capital for SMEs to scale their operations, invest 

in research and development, and expand their market reach. This increased capacity for growth can 

lead to higher revenues and improved profitability. Venture capital-backed SMEs tend to experience 

faster revenue growth compared to non-VC-backed firms, primarily due to the substantial investment 

in innovation and market expansion. Additionally, venture capitalists often bring valuable expertise 

and networks to the table (Achugbu, 2017).  

The active involvement of venture capitalists in strategic decision-making, management practices, and 

operational improvements can positively influence SME performance. This support includes 

mentorship, business development advice, and connections to potential customers, partners, and 

suppliers. Such involvement can enhance the efficiency and effectiveness of SME operations, thereby 

contributing to higher profitability (Black & Gilson, 2019). VC investors typically require detailed 

reporting and performance monitoring, which encourages SMEs to adopt best practices and focus on 

key performance indicators. This rigorous approach to performance management can lead to improved 

operational efficiency and profitability by ensuring that SMEs are aligned with their business goals and 

market demands (Eke, 2019). 

Venture Capital Financing and SMEs Job Creation 

Venture capital financing aids SMEs, particularly those in their early stages, as it provides the necessary 

capital to scale operations and pursue growth opportunities that might be inaccessible through 

traditional financing sources. This type of financing involves equity investments made by venture 

capitalists in exchange for ownership stakes in high-potential startups. Venture capital funding enables 

SMEs to expand their operations, develop new products, and enter new markets, all of which contribute 

to job creation (Egu et.al, 2024). 

One of the primary ways venture capital financing impacts job creation is by supporting business 

expansion. SMEs receiving venture capital funding often use the capital to increase their production 

capacity, enhance their technological capabilities, and expand their market reach. These growth 

activities typically require hiring additional staff, which directly creates new jobs. Venture capital-

backed SMEs tend to experience faster growth in employment compared to non-VC-backed firms, 

primarily due to their enhanced capacity for scaling operations (Biney and Gan, 2018). 

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The presence of venture capital financing has a broader impact on the job market beyond the individual 

SME. Successful venture capital-backed SMEs can stimulate job creation within their local economies 

and industries by fostering innovation and driving economic growth. This ripple effect can create 

additional employment opportunities in related sectors, such as supply chains, service providers, and 

ancillary businesses (Aman, 2023). 

Venture capital financing contributes to job creation through its focus on high-growth sectors and 

industries, such as technology and biotech. These sectors often have high potential for innovation and 

expansion, leading to significant job creation opportunities. Venture capital-backed firms are more 

likely to introduce new products and technologies, which can create a wide range of jobs, from research 

and development positions to manufacturing and sales roles (John, 2023). 

Venture Capital Financing and sustainability of SMEs 

The availability of venture capital financing can significantly influence the existence of SMEs by 

enabling them to undertake various business activities that are vital for their sustainability. For 

instance, Venture capital funding often supports research and development (R&D) initiatives, which 

are essential for innovation and product development. By investing in R&D, SMEs can develop new 

products and services, improve their competitive edge, and adapt to changing market conditions, 

thereby increasing their chances of long-term survival (Manyani, 2014). 

The influence of venture capital financing on SME existence also extends to market expansion and 

scaling efforts. Venture capital funding enables SMEs to enter new markets, increase production 

capacity, and explore additional revenue streams. These activities can help SMEs diversify their 

business operations and reduce dependency on a single market or product line, thereby strengthening 

their position and resilience in the market (Kauffman & Lee, 2019). 

The dependency on venture capital can also pose risks for SMEs. The need to meet the expectations of 

venture capitalists can sometimes lead SMEs to adopt aggressive growth strategies or make short-term 

decisions that may not align with their long-term goals. This pressure can affect the stability and 

sustainability of the business, potentially impacting its existence in the long run (Achugu, 2017). 

Challenges of Venture Capital financing   

However, Venture capitalists usually expect rapid returns on investment, which can put undue pressure 

on SMEs to prioritize short-term gains over long-term growth, often resulting in unsustainable business 

practices as SMEs accepting venture capital often means giving up significant equity and control in 

their company, which can limit decision-making flexibility and affect profitability. Again, founders 

might prioritize the venture capitalist’s agenda over what is best for the company (Adedeji and Yusuf, 

2018) 

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Venture capitalists may push for automation and lean staffing to increase profitability at the expense of 

job creation (Olaniyi and Olayemi, 2020). The formal application and vetting process for receiving 

venture capital is often complicated, making it difficult for small-scale entrepreneurs to access funds. 

This reduces the overall number of SMEs that could benefit from venture capital (Adekunle, 2021).  

The high expectations and pressures from venture capitalists can sometimes lead to conflicts over 

business strategies and priorities. These conflicts can affect decision-making processes and potentially 

impact profitability if not managed effectively. Additionally, the need to meet aggressive growth targets 

and financial performance expectations can place significant pressure on SMEs, which might affect 

their overall stability and profitability (Gikomo, 2013). 

The focus of venture capitalists on achieving high returns can lead to short-termism, where SMEs 

prioritize immediate financial gains over long-term sustainability. This emphasis on short-term 

performance might drive SMEs to pursue high-risk strategies that could compromise long-term 

profitability and business viability. Therefore, while VC financing can provide significant benefits, it is 

essential for SMEs to balance the pursuit of rapid growth with sustainable business practices (David, 

2023). 

Theoretical Review 

The Resource Based Theory 

The Resource based theory of entrepreneurship, propounded by Birger Wernerfelt in the year (1984), 

argues that access to resources by founders is an important predictor of opportunity-based 

entrepreneurship and new venture growth. This theory stresses the importance of financial, social and 

human resources as cited by Kwabena Nkansah Simpeh (2011). Financial, social and human capital 

represents three classes of theories under the resource-based entrepreneurship theories. This theory 

suggests that people with financial capital are more likely to acquire resources to effectively exploit 

entrepreneurial opportunities and set up a firm to do so. If Venture capital (VC) financing provides 

SMEs with access to critical financial resources, which are often scarce and difficult to obtain through 

traditional financing methods, according to the Resource based theory, these financial resources can be 

considered valuable and rare, giving SMEs a competitive edge in their respective markets. The infusion 

of capital allows SMEs to invest in growth opportunities, innovate, and expand operations, directly 

impacting their performance. For example, the ability to finance research and development, marketing, 

and scaling operations can differentiate an SME from its competitors, contributing to superior 

performance (Barney, 2011). 

Empirical Review 

Aman (2020) explored the impact of Venture Capital Funding on the Performance of Small and 

Medium-Sized Enterprises (SMEs) in Russia using correlation matrix and focusing on internal 

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organizational structuring and human resources management. The findings affirmed that venture 

capital funding significantly and positively influences the growth and performance of SMEs. John 

(2023) conducted a study investigating the influence of venture capital financing on Start-up Success 

through a comprehensive review articles, conference papers, and relevant academic publications. The 

study concluded that venture capital financing substantially contributes to start-up success by 

providing not only financial resources but also valuable managerial expertise, industry connections, 

and guidance. David (2023) examined the relationship between venture capital and other Sources of 

Finance through a literature review of both qualitative and quantitative studies. The findings 

highlighted the significance of venture capital financing in conjunction with other financial sources. 

Baldwin & Rafiquzzaman (2020) explored the role of financial management skills in the performance 

of SMEs in Malawi using OLS method. The study revealed that proficiency in financial management 

supports various aspects such as capital raising, profitability, investor confidence, risk mitigation, 

strategic decision-making, access to credit and financing, and tax compliance. Effective financial 

management contributes to long-term sustainability while balancing growth objectives with 

profitability. Biney and Gan (2018) investigated the impact of venture capital financing on small and 

medium enterprises’ growth and development in Ghana using both propensity score matching and 

difference-in-difference estimation techniques. The result showed a positive and significant correlation 

between venture capital financing and SMEs’ growth in the context of employment and sales in Ghana.  

Achugbu (2017) investigated the impact of venture capital (VC) financing on the growth of innovative 

30 start-up companies in Nigeria using content analysis method. It was found that venture capital 

financing had an impact on the growth of innovative start-ups.  

Manyani (2014) investigated effect of venture financing on small and medium scale enterprises in 

Bindura Urban, Zimbabwe using content analysis and the results indicated that the majority of SMEs 

in Bindura used their own savings, family and friends to finance their businesses. This is because, the 

financing options available to Bindura SMEs are impracticable to support the capital required for their 

operation because of stringent requirements and lack of collateral security. Gikomo (2013) investigated 

the effect of venture capital financing on the growth of top 100 medium sized SMEs in Kenya using 

cross sectional research design. Using a regression model the study found out that there was a positive 

and significant relationship between growth in SMEs and venture capital financing. Memba, Gakure & 

Karanja (2012), studied the impact of venture capital on growth of Small and Medium Enterprises 

(SME) in Kenya and the findings revealed that venture capital had an impact on growth of SME they 

financed and that use of venture capital can be profitable in Kenya even in an inauspicious political and 

economic climate.  

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Volume 13 Issue 1, January -March 2025 

ISSN: 2836-9416 

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Dalberg Global Development Advisors (2012) assessed the impact of Multilateral Investment Fund’s 

Venture Capital Program in Latin America using time-series data. The study examined impact of 

Venture Capital on companies’ revenue and job growth using a pre and post analysis. The result 

revealed that Venture Capital-backed firms in the sample under. Afua (2011) studied the impact of 

venture capital financing on SMEs in the Tema Metropolis in Ghana using primary data and frequency 

counts and percentages as main statistical techniques.  It was generally observed that SME‟s prefer 

self-financing and occasionally received support from financial institutions. While firms that had 

benefited from venture capital financing stated that they did not only receive capital inflow but was 

accompanied with monitoring, technical skills and expertise, access to management, marketing and 

distribution and reputation for attracting further finance.  

Juha (2010) examined the effect of venture capital investment on small and medium enterprises in 

Finland using regression analysis. The result showed that venture capitalists have a positive effect on 

SMEs in Finland. Yap (2009) analyzed the effect of venture capital firm's reputation on its start-up 

company's long term operating performance and survivorship in Singapore. Using cross sectional data 

and regression method. The result showed that venture capital companies’ market share and IPO share 

have strong and positive association with the post-IPO long-term performance metrics, and the effects 

are statistically significant even after accounting for self-selection bias. Dagogo & Ollor (2019) 

examined the effect of venture capital financing on the economic value added profile of Nigerian SMEs 

using Paired t-tests and multiple regression analysis. The result showed that the percentage growth of 

average economic value added of Venture Capital -backed SMEs from 2003 to 2007 was 1,678 percent, 

whereas there was a reduction in the average of economic value added of non VC-backed SMEs by 3.3 

percent. The result of the multiple regression analysis indicated that management support was the 

major driver in the high performance of VC-backed SMEs. Egu et.al (2024) examined the effect of 

venture capital financing on the Net sales, net profit and Return on Assets of SMEs in Cross River state, 

Nigeria. Data was collected from SMEs in Cross River State that registered with Corporate Affairs 

Commission and have used venture capital and analyzed using descriptive statistics of mean and 

standard deviation. The findings revealed that there was significant difference in net sales, net profit 

and return on assets after using venture capital financing. Emerah et.al (2020) explored the effect of 

venture capital on the performance of small and medium scale enterprises which have received 

assistance from VC in Nigeria using primary data and linear regression. The results showed that venture 

capital had a significant positive effect on the performance of small and medium scale enterprises in 

Nigeria.  

METHODOLOY 

Research Design 

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This study adopts an ex-post facto research design to explore the relationship between venture capital 

financing and performance of SMEs. This approach allows for the analysis of historical data to 

understand how venture capital financing influences the performance of SMEs. The study utilized 

secondary data sourced from World Bank Database and CBN Statistical Bulletin from 2011-2023. 

Model Specification 

The study adapted regression model of Emerah et.al (2020) which states thus; 

Profit = bo +b1NA+b2S+ut………………………..eq 2 

Where: 

Profit= Performance (dependent variable). 

NA= Net Assets (independent variable) 

S = Sales (independent variable 

VC = Venture capital 

The model was modified based on the objectives of this study as follows:  

SMEP = β0 + β1VCF +  ε 

JC = β0 + β2VCF + ε 

NSME = β0 + β3VCF + ε 

Where: 

PFR = Performance of SMEs 

VCF = Venture Capital Financing  

SMEP = Small and Medium Scale Enterprises (SMEs) Profitability  

JC = Job Creation  

NSMEs = Number of Smsall and Medium Scale Enterprises (SMEs). 

Β0 is the intercept, β1, β2 and β3 are the coefficients of the models explanatory variables, and ε  is the 

error term, capturing other factors that influence SME performance not included in the model. 

Method of Data Analysis 

Data was analyzed using correlation matrix, unit root test and simple regression analysis with the help 

of E-views 19 statistical software to ensure robustness and accuracy of results. 

4. DATA PRESENTATION AND ANALYSIS  

In this section, the descriptive statistics for the independent and dependent variables under 

consideration are analysed in table 1 in terms of its mean, median, maximum, and minimum values.  

 

 

 

 

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Table 1: Descriptive statistics of the model variables  

 TVF SMEP EMPR NSME 

 Mean  341.1000  75.48801  56.45291  93596.64 

 Median  104.1000  44.82284  56.65900  86309.00 

 Maximum  893.7000  355.0400  57.59100  129980.0 

 Minimum  24.40000  10.74789  55.02600  70441.00 

 Std. Dev.  366.1616  100.7340  0.801387  24904.86 

 Skewness  0.569576  2.126215 -0.313778  0.673362 

 Kurtosis  1.488715  6.612544  2.049998  1.774567 

     

 Jarque-Bera  1.641590  14.26958  0.594152  1.519538 

 Probability  0.440082  0.000797  0.742988  0.467775 

     

 Sum  3752.100  830.3681  620.9820  1029563. 

 Sum Sq. Dev.  1340743.  101473.3  6.422219  6.20E+09 

     

 Observations  11  11  11  11 

Source: E-Views 11 

Key: TVF-Total Venture Financing ($’ million); SMEP-SME Profitability (N’ Billion); 

EMPREmployment Rate; NSME-Number of SMEs. 

Table 1 shows that Total Venture Financing (TVF) had a mean value of $341.1 million, indicating the 

average level of venture financing across the 11 observations. The median value, at $104.1 million, is 

significantly lower than the mean, suggesting that the data is skewed by a few higher values, which is 

confirmed by a positive skewness of 0.57. The standard deviation of 366.16 highlights considerable 

variability in venture financing amounts, with the maximum reaching $893.7 million and the minimum 

being as low as $24.4 million. The Jarque-Bera test value of 1.64 and the probability of 0.44 indicate 

that the data is not significantly different from a normal distribution. SME Profitability (SMEP) displays 

a mean of ₦75.49 billion, with a median value of ₦44.82 billion, showing that the profitability figures 

are positively skewed, as indicated by the skewness value of 2.13. This positive skewness, coupled with 

a maximum value of ₦355.04 billion, suggests a small number of highly profitable periods significantly 

influence the average. The standard deviation of 100.73 indicates substantial variation in SME 

profitability across the observations. The Jarque-Bera statistic for SMEP is 14.27 with a probability of 

0.0008, which suggests that the distribution is not normal. Employment Rate (EMPR) showed a mean 

value of 56.45%, with a median of 56.66%, indicating that the data is closely clustered around the 

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central value, with a narrow range between the maximum (57.59%) and minimum (55.03%). The 

standard deviation is relatively small at 0.80, showing minimal variation in the employment rate. A 

negative skewness of -0.31 suggests a slight skew towards lower values. The Jarque-Bera statistic is 

0.59, and the associated probability of 0.74 indicates a normal distribution. The Number of SMEs 

(NSME) has a mean value of 93,596.64, with a median of 86,309, indicating that the data is moderately 

skewed, with a skewness of 0.67. The maximum value is 129,980 SMEs, while the minimum is 70,441, 

resulting in a relatively large standard deviation of 24,904.86, showing significant variability in the 

number of SMEs across the periods. The Jarque-Bera statistic of 1.52 and a probability of 0.47 imply 

that the number of SMEs is normally distributed. 

Correlation Matrix  

To examine the association among the variables, the Pearson correlation coefficient is used and the 

results shown below.  

Table 2: Correlation analysis of the model variables  

 TVF SMEP EMPR NSME 

TVF 1.0000 0.3926 -0.2089 0.6879 

SMEP 0.3926 1.0000 -0.0148 0.7026 

EMPR -0.2089 -0.0148 1.0000 -0.3163 

NSME 0.6879 0.7026 -0.3163 1.0000 

Source: E-Views 11 

TVF has a moderate positive correlation with SME Profitability (SMEP) at 0.3926, suggesting that 

higher levels of venture financing are somewhat associated with improved profitability in SMEs. 

Additionally, there is a strong positive correlation between TVF and the Number of SMEs (NSME) at 

0.6879, implying that increased venture financing is linked to a rise in the number of SMEs. However, 

TVF is weakly and negatively correlated with the Employment Rate (EMPR) at -0.2089, indicating that 

higher venture financing does not directly translate to improvements in employment. 

SME Profitability (SMEP) exhibits a moderate positive correlation with TVF (0.3926) and a strong 

positive correlation with the Number of SMEs (0.7026). This indicates that higher profitability fosters 

the expansion of SMEs. The correlation between SMEP and Employment Rate (EMPR) is near zero (-

0.0148), suggesting no significant relationship between SME profitability and employment levels. 

The Employment Rate (EMPR) shows a weak negative correlation with most variables in the model. It 

has a slightly negative correlation with TVF (-0.2089) and NSME (-0.3163), indicating that increases 

in venture financing and the number of SMEs might not directly improve employment rates. The 

correlation of SMEP with EMPR (-0.0148) further supports the lack of a significant relationship. 

 

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The Number of SMEs (NSME) has a strong positive correlation with both TVF (0.6879) and SMEP 

(0.7026), showing that more SMEs are associated with higher venture financing and profitability. 

However, it is negatively correlated with EMPR (-0.3163), suggesting that an increase in the number of 

SMEs may not necessarily lead to higher employment rates, and could be related to other economic 

factors. 

Unit Root Test 

Null Hypothesis (Ho):  The variable X has a unit root 

Alternate Hypothesis (H1):  The variable X has no unit root   

Table 3: ADF test for model variables  

Variable   ADF Prob 

TVF Level   1(0) -2.241621 0.2031 

 First difference  1(1) -3.544585 0.0335 

SMEP Level 1(0) 0.824572 0.9894 

 Second difference 1(2) -5.160095 0.0051 

EMPR Level 1(0) -1.804293 0.3593 

 Second difference 1(2) -3.828532 0.0225 

NSME Level 1(0) 0.001716 0.9367 

 Second difference 1(2) -4.540349 0.0133 

Source: E-Views 11 

The data was subjected to unit root test through Augmented Dickey-Fuller (ADF). The result in Table 

3 below showed that TVF is stationary at first difference while others were stationary after the second 

differencing 

Test of Hypothesis One 

H0:  There is no significant effect of venture capital financing on SMEs’ profitability. 

H1: There is a significant effect of venture capital financing on SMEs’ profitability. 

The robust regression output for the test of hypothesis one is shown below as follows: 

Table 4: Regression output for the test of hypothesis one  

Dependent Variable: SMEP   

Method: ML ARCH -  (BFGS / Marquardt steps)  

Date: 10/04/24   Time: 21:16   

Sample: 2011 2023   

Included observations: 13   

Method: M-estimation   

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M settings: weight=Bisquare, tuning=4.685, scale=MAD (median centered) 

Huber Type I Standard Errors & Covariance  

     
     Variable Coefficient Std. Error z-Statistic Prob.   

     
     C 13.62293 6.640446 2.051508 0.0402 

TVF 0.088560 0.014787 5.989167 0.0000 

     
      Robust Statistics   

     
     R-squared 0.516273     Adjusted R-squared 0.472298 

Rw-squared 0.891493     Adjust Rw-squared 0.891493 

Akaike info criterion 39.54740     Schwarz criterion 41.92473 

Deviance 4187.662     Scale 10.66823 

Rn-squared statistic 35.87012     Prob(Rn-squared stat.) 0.000000 

     
      Non-robust Statistics   

     
     Mean dependent var 66.14179     S.D. dependent var 94.74549 

S.E. of regression 94.08482     Sum squared resid 97371.49 

     
     Source: E-Views 11 

The R-squared value of 0.516273 implies that the model explains about 51.6% of the variability in SME 

profitability. The adjusted R-squared value of 0.472298 accounts for the number of predictors, slightly 

lowering the explained variability to 47.2%.  The R-squared value of 0.891493 indicates that the model’s 

robustness check shows a very high degree of fit when considering the robustness adjustments (e.g., M-

estimation). The constant term (C) is 13.62293, with a standard error of 6.640446 and a z-statistic of 

2.051508, which is statistically significant at the 5% level (p-value = 0.0402).   The coefficient for TVF 

is 0.088560, with a very low standard error of 0.014787 and a highly significant z-statistic of 5.989167 

(p-value = 0.0000). This indicates that for every 1-unit increase in venture financing, SME profitability 

increases by approximately 0.089 units. The highly significant relationship between TVF and SMEP 

underscores the importance of venture financing in driving SME profitability, making it a critical factor. 

Decision Rule: 

The results of the robust model provide valuable insights into the relationship between Total Venture 
Financing (TVF) and SME Profitability (SMEP). Since the p-value is less than .05; we reject the null 

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and accept the alternate; thus, “There is a significant effect of venture capital financing on SMEs 
profitability”. 
Test of Hypothesis Two 
H0: There is no significant relationship between venture capital financing and SME performance 
in terms of job creation. 
H1: There is a significant relationship between venture capital financing and SME performance 
in terms of job creation. 
The robust regression output for the test of hypothesis two is shown below as follows: 
Table 5: Regression output for the test of hypothesis two  
Dependent Variable: EMPR   
Method: ML ARCH -  (BFGS / Marquardt steps)  
Date: 10/04/24   Time: 21:26   
Sample: 2011 2023   
Included observations: 13   
Method: M-estimation   
M settings: weight=Bisquare, tuning=4.685, scale=MAD (median centered) 
Huber Type I Standard Errors & Covariance  
     
     Variable Coefficient Std. Error z-Statistic Prob.   
     
     C 57.08170 0.366898 155.5792 0.0000 
TVF -0.001062 0.000817 -1.299791 0.1937 
     
      Robust Statistics   
     
     R-squared 0.144681     Adjusted R-squared 0.066925 
Rw-squared 0.197117     Adjust Rw-squared 0.197117 
Akaike info criterion 18.13191     Schwarz criterion 19.28805 
Deviance 7.770636     Scale 0.740841 
Rn-squared statistic 1.689456     Prob(Rn-squared stat.) 0.193673 
     
      Non-robust Statistics   
     
     Mean dependent var 56.68923     S.D. dependent var 0.933489 
S.E. of regression 0.914156     Sum squared resid 9.192498 
     
     Source: E-Views 11 

The R-squared value of 0.144681 indicates that the model explains only 14.5% of the variability in the 

employment rate. The adjusted R-squared of 0.066925 suggests that after accounting for the number 

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of predictors, the model’s explanatory power drops to about 6.7%. The R-squared value of 0.197117 

indicates a slight improvement in model fit when robust methods are applied, but the overall fit remains 

modest. The constant term is 57.08170, with a very small standard error of 0.366898 and an extremely 

high z-statistic of 155.5792 (p-value = 0.0000). This indicates that when TVF is zero, the employment 

rate is expected to be around 57.08%. The coefficient for TVF is -0.001062, indicating a small negative 

effect of venture financing on the employment rate. However, the z-statistic of -1.299791 and p-value 

of 0.1937 indicate that this relationship is not statistically significant. This suggests that venture 

financing does not have a meaningful direct impact on the employment rate in this model, as the 

negative coefficient is not strong enough to infer a clear effect. 

Decision Rule: 

The model results provide insights into the relationship between Total Venture Financing (TVF) and 

EMPR. Since the p-value is greater than .05; we reject the alternate and accept the null; thus, “There is 

no significant relationship between venture capital financing and SME performance in terms of job 

creation”. 

Test of Hypothesis Three 

H0: There is no significant effect of venture capital financing on the number of SMEs in

 Nigeria. 

H1: There is a significant effect of venture capital financing on the number of SMEs in Nigeria. 

The robust regression output for the test of hypothesis three is shown below as follows: 

Table 6: Regression output for the test of hypothesis three 

Dependent Variable: NSME   

Method: ML ARCH -  (BFGS / Marquardt steps)  

Date: 10/04/24   Time: 21:43   

Sample (adjusted): 2013 2023   

Included observations: 11 after adjustments  

Method: M-estimation   

M settings: weight=Bisquare, tuning=4.685, scale=MAD (median centered) 

Huber Type I Standard Errors & Covariance  

     
     Variable Coefficient Std. Error z-Statistic Prob.   

     
     C 73557.91 5183.673 14.19031 0.0000 

TVF 70.70524 10.62025 6.657585 0.0000 

     
     

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 Robust Statistics   

     
     R-squared 0.405339     Adjusted R-squared 0.339266 

Rw-squared 0.920088     Adjust Rw-squared 0.920088 

Akaike info criterion 27.84287     Schwarz criterion 27.20228 

Deviance 7.87E+08     Scale 5928.051 

Rn-squared statistic 44.32344     Prob(Rn-squared stat.) 0.000000 

     
      Non-robust Statistics   

     
     Mean dependent var 93596.64     S.D. dependent var 24904.86 

S.E. of regression 21646.35     Sum squared resid 4.22E+09 

     
Source: E-Views 11 

The model addresses heteroskedasticity concerns and provides both robust and non-robust statistics to 

evaluate the strength and significance of the variables. The R-squared value of 0.405339 means that 

the model explains about 40.5% of the variation in the number of SMEs. The adjusted R-squared value 

of 0.339266 shows that after accounting for the number of predictors, i.e., 33.9%. The R-squared value 

of 0.920088 demonstrates a very strong fit when robustness adjustments are applied. The model 

appears to explain 92% of the variability in the number of SMEs. 

The constant term is 73,557.91, with a standard error of 5,183.673 and a z-statistic of 14.19031 (p-value 

= 0.0000), which is highly significant. This implies that when TVF is zero, the number of SMEs is 

expected to be around 73,558. The significance of this constant shows that, independent of venture 

financing, there is a baseline number of SMEs. The coefficient for TVF is 70.70524, with a small 

standard error of 10.62025 and a very high z-statistic of 6.657585 (p-value = 0.0000). This indicates, 

that for every $1 million increase in venture financing, the number of SMEs increases by about 70.71.  

Decision Rule: 

The model results provide insights into the relationship between Total Venture Financing (TVF) and 

the no. of SMEs. Since the p-value is less than .05; we reject the null and accept the alternate; thus, 

“There is a significant effect of venture capital financing on the number of SMEs in Nigeria”. 

Conclusion and Recommendation  

From the result of the analysis, the was revealed that venture capital financing plays a crucial role in 

enhancing the performance of small and medium-sized enterprises (SMEs) through increment in 

profitability and number of SME’s though, no significant relationship exited between venture capital 

financing and job creation.  

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The study concludes that non-existence of significant relationship between VCF and job creation in 

SME’s in Nigeria despites the existence of positive significant relationship that exist between VCF and 

SME’s profitability and number of SME’s is an indication of lopsided growth pattern, as economically, 

increase in number of SME’s and profitability supposed to create more job opportunities.  

Based on the findings, the study recommends for an intensive and sustainability growth rate policies in 

favour of SME’s in Nigeria that will bring significant and sustainable growth in SME’s which will lead 

to job creation.   

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https://doi.org/10.1177/1042258719874106 

APPENDICES I 

Year Early 

Stage 

Later 

Stage 

Seed 

Stage 

Total 

Venture 

Financing 

NSME EMPR SMEP 

2011 10.2 5.2 3.5 18.9 
 

58.133 15.61  

2012 15.8 8.4 4.8 29 
 

57.845 13.86  

2013 20.5 12.6 7.2 40.3 72838 57.591 15.35  

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https://smedan.gov.ng/
https://doi.org/10.11648/j.jfa.20180601.15
https://doi.org/10.1002/smj.4250050207
https://data.worldbank.org/
https://doi.org/10.1177/1042258719874106


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Volume 13 Issue 1, January -March 2025 

ISSN: 2836-9416 

Impact Factor: 6.41 

Journal Homepage: https://americaserial.com/Journals/index.php/ARJEFM, 

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2014 25.6 15.2 8.6 49.4 72838 57.341 16.07  

2015 30.2 18 9.9 58.1 70441 57.054 12.95  

2016 32.4 21.4 11.1 64.9 75380 56.659 10.75  

2017 701.5 124.1 10.1 835.7 73081 56.293 10.75  

2018 20 0 4.4 24.4 86309 56.006 44.82  

2019 224.1 0 23.3 247.4 90748 55.805 123.93  

2020 44.9 56.6 2.6 104.1 97988 55.026 62.51  

2021 81.3 781.6 30.8 893.7 129980 55.507 83.74  

2022 60.3 703 27.5 790.8 129980 56.703 94.46 

2023 80.5 551 11.8 643.3 129980 56.997 355.04 

 

Source: Statistics Database/World Bank Database/CBN Statistical Bulletin 

 

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