Impact of Development Bank Credit Financing on Growth of SMEs in Nigeria

Impact of Development Bank Credit Financing on Growth of SMEs in Nigeria

Ajibola Yetunde Kayode, Mosunmola Jemilat Abdulwaheed

Federal Capital Territory Administration, Abuja, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2024.803096

Received: 15 February 2024; Revised: 01 March 2024; Accepted: 05 March 2024; Published: 09 April 2024

ABSTRACT

Over the years, small and medium enterprises (SMEs) have been considered as engines of growth. This has indeed been observed from available survey data from the World Bank and other development institutions. Access to finance has been recognized as a major factor affecting the growth and success of SMEs all over the world. Small and medium enterprises (SMEs) financial constraints limit their investment opportunity and stagnant growth. Therefore, a quest to find a solution to this necessitated the establishment of Development Banks which is saddled with the responsibility of making credit available to SMEs. Hence, the main objective of this study is to examine the impact of Development Bank credit financing on the growth of SMEs. A Survey research design was employed, 398 SMEs were randomly selected from the beneficiaries of Development Bank of Nigeria (DBN) loans. Binary logistic regression was employed to test the stated hypothesis. The estimated logistic regression showed that variables such as (HSBC) which is an increase in sales of the MSMEs and support and service training for SMEs before loans impacted positively and significantly on the profitability of the SMEs given their beta coefficients of (β)=0.570, 0.384 respectively. Their level of significance is shown by their respective p-values and Wald statistics of 0.049, 0.099, 3.889, and 2.7240.  These show that the variables are barely significant at 10%. However, all the other variables such as the age of the entrepreneur (AGE), gender of the entrepreneur (GENDER), amount of loan received (AOLR), and proportion of loan utilized (POLU) do not have a significant impact on the profit of the entrepreneurs.

Keywords – Development Bank, Credit Financing, Growth of SMEs.

INTRODUCTION

Over the years, small and medium enterprises (SMEs) have been considered as engines of growth. This has indeed been observed from available survey data from the World Bank and other development institutions. Small and medium enterprises account for 90% of all businesses globally. Likewise, SMEs were reported to generate 60% of employment worldwide and provide jobs to roughly 80% of the workforce in the developed world. (Peterhoff, Romeo and Calvey, 2014; Richard, 2015, World Bank, 2021). Africa too is not left out in this, as small businesses account for 90% of all businesses in Africa and represents 38% of the region’s Gross Domestic Product (GDP) thereby playing an important role in the growth and industrialization of the region.

The 2012 Global Entrepreneurship Monitor (GEM) has empirically identified Nigeria as one of the most entrepreneurial countries in the world. The study showed that 35 out of every 100 Nigerians (over a third) are engaged in some kind of entrepreneurial activity or the other. Also study by UNIDO-Nigeria, 2012 showed that Micro, Small and Medium Enterprises (MSMEs) have the propensity to drive the Nigerian Economy. Available data revealed that in 2013, about 17 million MSMEs were employing over 31 million which accounted for over 80% of enterprises that employ about 75 % of Nigeria’s total workforce. (NBS, 2013). However, in 2017 the number of registered MSMEs in Nigeria increased to 41.5 million employing about 59 millions of her population accounting for over 90 percent of the enterprise that employs about 86.3 percent of the national workforce. These have pointed to the fact that Nigeria is a SMEs-dominated economy. (SMEDAN and NBS, 2017) However, for SMEs to be able to fulfil their role as a tool for sustainable growth and development, the issue is far from the number but rather adequate financing. Finance is the life wire of any economy, whether developed or developing.

Access to finance has been recognized as a major factor affecting the growth and success of SMEs all over the world. Small and Medium Enterprises (SMEs) financial constraints limit their investment opportunity and stagnate growth. Access to finance is widely perceived as an essential factor for firms, especially small and medium enterprises (SMEs) to maintain their daily business operation as well as to achieve long-term investment opportunities and development targets (Onyiego, Namusonge, & Waiganjo, 2017).  Availability of finance determines the capacity of an enterprise in terms of choice of technology, access to markets, and access to essential resources, which in turn greatly influences the viability, and success of a business (Mugunchu, 2013; Marus, Fabian, Deus and Charles, 2017).

It has been observed from available survey data that access to credit has consistently ranked as one of the top constraints cited by firms (Fowowe, 2017). However, for SMEs to grow and be able to fulfil their role as a tool for sustainable growth and development the role of credit at an affordable price cannot be overemphasized because most entrepreneurs cannot even raise the initial capital to start a viable business.

Advocacy by major stakeholders on the need to reduce interest on loans to SMEs and encourage borrowing by SMEs to reduce the effect of Covid -19 pandemic on the Nigeria economy points to the fact that SME financing will have a significant impact on the growth of SMEs and also have a major role to play in the sustainability and development of Nigerian economy.

There has increased the attention of government, development agencies, and policymakers on the role of SMEs in diversification and development of an economy, most especially in Nigeria because of the volatility of the oil price in the international market and the need to look inwards in the process of growth and development. For SMEs to play a meaningful role in achieving these objectives, their performance in terms of growth is very important.

As a result of this, several policies have been rolled out by the CBN and other agencies in the area of financing by successive governments in Nigeria to improve the performance of SMEs because inadequate credit financing has been identified as one of the major constraints to the growth of SMEs. (Ezeaku, Anidiobu and Okolie, 2017; Danjuma, 2017; Anyawu,2003; Lawson, 2007; Babajide, 2012). Despite these policies, the majority of the micro and small enterprises (MSEs) in Nigeria are still at a low level of growth and development. Not more than 15% of newly established businesses survive the first five years in Nigeria; even the performance of the ones that survive after this period is not encouraging. (SMEDAN, 2018; Fatoki, 2014; Abiodun,2014; Olotu, 2014). Even though SMEs in Nigeria dominate more than 90% of Nigerian firms, their role and contribution to the national GDP is still less than expected. (Gbandi and Amissah, 2014, Oyedokun and Micha, 2019).

A continuous quest for a solution to inadequate finance for SMEs to improve their growth led to the establishment of the Development Bank of Nigeria. It also aims to bridge the financial gap that has been created by other financial institutions in the area of finance to SMEs and Hitherto improve their growth. Therefore, the question that comes to mind is whether this public financial institution has been able to achieve the objective of improving the growth of SMEs in Nigeria through its credit financing. This is the question this paper seeks to answer.

Research Questions

Therefore, this research question was raised in line with the problem stated above:

Does Development Bank credit financing impact the growth of SMEs in Nigeria?

Hypothesis

H0: Development bank credit financing does not have a significant impact on the growth of SMEs in Nigeria.

LITERATURE REVIEW AND THEORETICAL FRAMEWORK

Development Bank and Development Bank Credit Financing

A Development Bank is a government financial institution that is saddled with the responsibility of providing short to medium-term loans that will foster the productivity of enterprises in the country, they alleviate capital scarcity and promote entrepreneurial action to boost new or existing industries (Cameron, 1961; Gerschekron,1962).

Credit is borrowing money from an outside source with a promise to return the principal in addition to an agreed-upon level of interest. (Richard, Devinney, Yip, and Johnson, 2009). The sources of the credit may be internal such as friends and relatives or external such as financial institutions like deposit money banks, specialized banks, and cooperative societies. However, the most popular source of credit financing is the bank. Credit financing can likewise be regarded as a strategy that involves borrowing money from a lender with an understanding that the full amount will be paid in the future with interest. (Stearns,1997).

Development Bank credit financing can therefore be defined as the provision of loans from a government-owned financial institution known as a development bank to SMEs for the running of their businesses.

The first attempt to define small businesses was that of Bolton 1971 using two approaches to defining SMEs which are quantitative and qualitative approaches.

Generally, differences in SMEs can be categorized into three different groups, definition by international institutions, definition by national laws, and definition by industry. (Berisha and Paula, 2015).

The World Bank Enterprise Survey (WBES) classifies enterprises according to their number of employees. They categorize enterprises with 5-19 employees as small enterprises and those with 20-99 employees as medium-scale enterprises. Whereas the World Bank Group gives a slightly different categorization by giving three quantitative criteria for defining SMEs which are the number of employees, total assets in U.S. dollars, and annual sales in U.S. dollars. (Institute of Economic Growth, 2008). European Union classified enterprises with 50-249 employees and turnover not exceeding 50 million Euro as medium-sized, 10-49 employees and turnover not exceeding 10 million Euro and small-sized enterprises as enterprises with less than 10 employees and turnover of not more than 10 million Euro as micro enterprise. (OECD,2015).

Classification of MSMEs varies across countries. In countries such as the USA, Britain, and Canada, small-scale business is defined in terms of annual turnover and the number of paid employees. In Britain, small-scale business is defined as an industry with an annual turnover of 2 million pounds or less with fewer than 200 paid employees. In Japan, small-scale industry is defined according to the type of industry, paid-up capital, and a number of paid employees. (Ayuba and Zubairu, 2015). In Africa, an upper bound of 100 employees is the most common classification of SMEs (Kushnir, Mirmulstein, and Ramalho, 2010). In Nigeria, there is no clear-cut definition that distinguishes a purely small-scale enterprise from a medium-scale enterprise. The Central Bank of Nigeria, in its Monetary Policy Circular No. 22 of 1988, defined small-scale enterprises as having an annual turnover not exceeding 500,000 naira. However, in 2010, it was further reviewed as any enterprise with an asset base between 5 million and 500 million excluding land and a labour force between 11 and 300 employees. Meanwhile, the definition of MSMEs in Nigeria as contained in the National Policy on Micro, Small and Medium Enterprises produced by the Small and Medium Enterprises Development Agency of Nigeria SMEDAN, (2010) is as follows:

Microenterprises are those enterprises with less than 10 employees and assets of less than N5 million while small enterprises are enterprises with 10-49 employees and between 5- N50 million assets whereas medium enterprises are enterprises with 50-199 employees and assets of between 50- 500 million. This is what is used as the definition of SMEs for this study.

SMEs Growth

Growth can be regarded as a condition of survival for young and small businesses, as growing firms are found less vulnerable to failure than non-growers (Stam., Suddle., Hessels., & Von Stel., 2006). Generally speaking, SME growth can mean several things, such as an increase in total sales volume, increase in production capacity, an increase in employment, an increase in production volume, an increase in the use of raw material and power. (Yeboah,2015). An entrepreneurial venture is successful if it is growing.  It should however be noted that growth can be defined in terms of revenue generation, value addition, and expansion in terms of volume of the business. It can also be measured in the form of qualitative features like market position, quality of product, and goodwill of the customers (Kruger 2004). Business growth has been measured by various scholars using various variables such as relative or absolute changes in sales, assets, employment, productivity, profit, market share, and physical output. However, these indicators are not as widely used as sales and employment because of their limited applicability. Therefore, sales and employment are two important indicators in measuring firm growth.

Theoretical Framework

The theoretical framework for this study is hinged on the theory of firm growth propounded by Storey, 1994. Determinants of firm growth can be categorized into three main groups which are:

(a) Those related to the entrepreneur, which can also be regarded as the entrepreneur’s inherited and learned abilities like motivation, experience, age, gender, education, and family history.

(b) Those related to the firm which means owner/manager like age, sector, legal form, location, size and ownership.

(c) Those related to strategy such as management training, workforce training, state support and others.

However, all of these elements should be combined in an appropriate proportion so that the firm grows rapidly; in other words, all these factors jointly influence the growth of firm as depicted by the diagram below.

Fig. 1. Source: Storey, (1994).

From the diagram above, high-growing firms are found in the shaded region, those are firms that combine the three interacting groups of factors that impact enterprise growth effectively. However, this study and the nature of the available data for each group will be used, but more specifically, state support, which is one of the data points in the group, will be the focus of our study. Other data from the other groups such as the firm are used as our control variables to the impact of strategy (state support which is the Development Bank credit financing to SMEs in Nigeria) on their growth. It should also be noted that to measure growth, the profit of the SMEs will be used.

Empirical Review

Kanu and Nwadiubu (2021) analyzed the commercial bank loans and performance of SMEs in Nigeria using a least square analysis of time series data. The outcome of the study indicated that there existed a relationship between commercial bank loans to SMEs and the output of SMEs in Nigeria

Agyeman, Quarshie, and Telari Bonn (2021) in their study “Does access to credit impact the performance of Small and Medium Enterprises” examined whether access to credit impacts the performance of small and medium enterprises in Ghana. Survey methodology was used to collect data for the study through the administration. Purposive techniques were used to arrive at the sample of 65. Data was analyzed through the use of the Analytics Software (PASW) version 20. Pearson’s correlation was used to find the relationship between access and performance of small and medium enterprises and the finding revealed a positive relationship of 0.368. This shows a strong relationship between access to finance and the performance of SMEs.

Khan (2020) studied microfinance banks’ credit financing and its impacts on Small and Medium Scale Enterprises in Nigeria with specific reference to Damaturu in Yobe state. The study used representative random and administered fifty (50) questionnaires out of which forty-one (41) were correctly filled and returned. For the analysis of data, the research used the Chi-square tool to test the formulated hypotheses. It was concluded that microfinancing does have a significant effect on the growth of small and medium-scale enterprises in Damaturu and there is a significant relationship between the severity of borrowing conditions of Microfinance Banks and the development of small-scale enterprises in Damaturu.

Robert (2019) analyzed firm characteristics and growth of small and medium enterprises in Nyeri county, Kenya. The study targeted 840 Small and medium enterprises and since the number of small and medium enterprises is huge, stratified random sampling was used to arrive at 126 Small and medium enterprises. Semi-structured questionnaires were used for collecting data which was analyzed using descriptive and inferential statistical tools and presented using tables. The study found that the size of the firm and the age of the firm had positive and statistically significant effects on the growth of small and medium enterprises. Particularly, large firms were found to perform better than small firms due to their ability to source more funds from external sources, increase in sales turnover and value of capital employed leads to growth of firms. The industry sector had a positive but statistically insignificant effect on the growth of small and medium enterprises.

Ezeaku et al. (2017) assessed the effect of SME financing on manufacturing sector growth in Nigeria using annualized data from 1981 to 2014. A co-integrating relationship was determined using the Engel and Granger residual-based approach which showed evidence of a long-run relationship between SMEs credit and manufacturing output growth in Nigeria. The results of the error correction model showed that SME financing had exerted a positive influence on the manufacturing sector’s growth. The finding indicated that when credits to the SMEs increased by 1%, manufacturing output rose by 14.5%. The results also revealed that interest rates and inflation rates had negative effects on manufacturing sector growth. A unit change in interest rate led to a 15.7% fall in output growth of the manufacturing sector. They concluded that while SMEs are an important sector that can drive the Nigerian economy, rising interest rate stifles their growth and overall economic impact.

Ayuba and Zubairu (2015) examined the impact of banking sector credit financing on the growth of small and medium enterprises in Nigeria. The main objective of the study is to investigate whether banking sector credit has a significant impact on the growth of small and medium enterprises in Nigeria. As part of the methodology, annual data between 1985 and 2010 were collected and used in the study while descriptive statistics, correlation matrix, and error correction model were used to test the formulated hypotheses which revealed that banking sector credit has a significant impact on the growth of small and medium enterprises in Nigeria as it has a positive impact on some major macro-economic variables of growth such as inflation, exchange rate, trade debts.

Babajide (2012) analyzed the effects of microfinance credit financing on Micro and Small Enterprises (MSEs) Growth in Nigeria by employing panel data and multiple regression analysis to analyze a survey of 502 randomly selected enterprises financed by microfinance banks in Nigeria. The result showed that access to microfinance does not enhance the growth of micro and small enterprises in Nigeria. However, other firm-level characteristics such as business size and business location, are found to have a positive effect on enterprise growth in Nigeria.

METHODOLOGY

The target population for this study was SMEs that have benefitted from Development Bank of Nigeria (DBN) loans out of which a total of 398 were drawn as samples using the Taro Yamani formula. Questionnaires were used to elicit relevant information on DBN loans, firm characteristics, and entrepreneur characteristics from SMEs. Firm characteristics and entrepreneur characteristics variables were included as control variables. The data used was sourced from the Monitoring and Evaluation Department of the Development Bank of Nigeria. The data collected were coded on a Microsoft excel sheet and were further copied to SPSS for analysis using binary logistic regression.

Model Specification

Analyze the impact of development bank credit financing on the level of profit of SMEs in Nigeria.

To achieve this objective, we adapted the model of Vedaste and Ruranga (2020), although the model was not explicitly stated but the variables were stated and explained as follows:

The dependent variable, SME financial performance (profit) was a binary variable; taking the value of 0 and 1.  The independent variables were overdraft, line of credit, contract finance, number of employees, and type of organization. However, due to the literature reviewed, the nature of our data, and the availability of data, our dependent variable is profit which is a binary variable while our independent variables included finance variables, variables on entrepreneurs’ characteristics, and firm characteristics.  Our model is explicitly stated as:

DATA ANALYSIS AND INTERPRETATION

Binary Logistic Regression Analysis of Impact of Development Bank Credit Financing on SMEs Profit

Table. 1. Source: Authors computation

Summary Stat.-2Loglikelihood (-2LL) =484.035

 X2=20.289., df=8, p<0.05,

Nagelkerke R2=.069 (6.9%), Classification accuracy = 68.8%,

Hosmer and Lemeshow Test = 2.969, p-value = 0 .936

The model three of the study measured the impact of credit financing on the profit of the small and medium-scale enterprises (SMEs) in Nigeria. To achieve this, the variables business size (BIZSIZ), increase in business sales (HSBC), average monthly tax payments (AVMTL), age of the entrepreneur (AGE), gender (GENDER), duration of business (BIZAGE), amount of loan received (AOLR), support and service training received (SSTB) and proportion of loans utilized (POLU) were used as the predictors. The estimated coefficient revealed that Size of business (BIZSIZE), age of business (BIZAGE), support, and service training before loan (SSTB) impact positively SMEs Profit. It denotes that a unit change in business size and business age and support and service training received while holding other things constant led to about 0.344, 0.09, and 0.014 increase in the logit, SMEs profit though they are not statistically significant given their respective p- values of 0.174, 0.444 and 0.099. However, SSTB was barely significant at 10%. Therefore, they cannot be used for inference purposes.

The increase in the sales of SME business (HSBC) was found to have a positive impact on the level of profit making of the SMEs (HPIAL). Its estimated coefficient (β)=0.570 (57.0%) indicates that a unit change in the level of sales while holding other variables constant led to about 0.57 increase in the logit, profit of SMEs. It was found to be barely statistically significant as can be drawn from the computed Wald Stat.= 3.889 with p-value = 0.049. The   Exp(β) = 1.768 estimated yielded the odds ratio (OR) = 0.768 which means that SMEs that witness growth in sales are 0.768 times more likely to have an increase in their profit than SMEs that do not witness growth in sales.

The average monthly tax payment (AVMTL) made by the SMEs was established to negatively impact SMEs’ profit.  The coefficient(β) = – 1.004 (100.4%) showed that a unit change in the average monthly tax payment while holding other variables constant led to about 1.004 unit decline in the logit, SMEs profit. Specifically, it means SMEs’ profit will decrease by the exact amount of what is paid as tax.   It was found to be statistically significant as revealed by the computed Wald test Stat = 6.908 with p-value = 0.009 which is less than 0.05(5%) level.  The Exp(β) = 0.366 which yielded the odds ratio (OR) = 0.634 indicating that SMEs that pay tax monthly are more likely to have their profit reduced 0.634 times more than those that do not pay tax

Variables of the age of the entrepreneur (AGE), gender of the entrepreneur (GENDER), amount of loan received (AOLR), and proportion of loan utilized (POLU) all showed a negative relationship with logit, SMEs profit. However, none of the variables are significant. The value of the -2loglikelihood=484.035 means that the model fits the data better. This was also confirmed by the Hosmer-Lemeshow test (X2) = 2.969 p-value =0.936 > 0.05.

From the foregoing analysis, the study tests hypothesis number three of the study using Wald test statistics with its p-value, and it is restated as thus:

H01: Development bank credit financing does not have a significant impact on the level of profit of SMEs in Nigeria.

Since the computed Wald stats of our variables of interest that is variables of DBN credit financing which are AOLR, SSTB, and POLU are 0.072, 2.724, and 0.037 with their respective p-values of 0.788, 0.099 and 0.847, then we do not have sufficient reason to reject the null hypothesis that development bank credit financing does not have a significant impact on the level of profit of SMEs because it is only SSTB that is barely significant at 10% level of significance. We may therefore accept the null hypothesis that development bank credit financing does not have a significant impact on the level of profit of SMEs in Nigeria. The study concluded that development credit financing does not have a significant impact on the level of profit of SMEs in Nigeria this might be as a result of the burden of the loan repayment and payment of tax.

CONCLUSION

The estimates of the impact of Development Bank credit financing and MSMEs’ profitability revealed that variable (HSBC) which is an increase in sales of the MSMEs and support and service training for SMEs before loan impacted positively and significantly on the profitability of the SMEs. All the other variables such as the age of the entrepreneur (AGE), gender of the entrepreneur (GENDER), amount of loan received (AOLR), and proportion of loan utilized (POLU) do not have a significant impact on the profit of the entrepreneurs.

RECOMMENDATION

Based on the conclusion of our findings, the study thereby recommends that tax reduction or tax holiday should be given to the beneficiaries of this credit financing until the full repayment of their loan as it was discovered that the average amount of tax paid by SMEs have a negative and significant impact on the profit of SMEs.

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