A Survey of Factors Affecting Financing of Small and Medium-Sized Businesses in the Tehran Stock Exchange (TSE)

The purpose of this research was to identify the factors affecting financing of small and medium-sized enterprises in the Tehran Stock Exchange (TSE). The method of this study was to use the multiple regression model and panel data to test the hypotheses. The statistical population included 63 small and medium-sized companies admitted to the TSE, which were tested for the period of 2006 to 2021. The contribution was the use of market cap as a criterion for determining small and medium-sized companies. According to the findings, company size has a significant effect on internal financing. In addition, company size had a significant relationship with external financing through debt and share issuance. Also, there was a significant relationship between intangible assets and internal financing, while the ages of the small and medium sized enterprises did not have a significant relationship with external financing. It is suggested that small and medium-sized enterprises pay more attention to the significant variables for financing. Keywords: Financing, Debt, Equity, Intangible Assets, Small and Medium-Sized Enterprises. Introduction The primary focus of this study was to investigate the financing of the capital structure of Small and Medium-sized Enterprises (SMEs) in Iran. SMEs play a crucial role in the economies of both developed and developing countries. According to the theory posed by Schumacher, a renowned German economist, as presented in the book "Small is Beautiful", creating job opportunities in rural areas and small towns can be achieved by making modest investments to generate employment, utilizing relatively simple production methods and leveraging local resources to establish small industries. SMEs serve as the backbone of the developing world's economy (Memarnejad, 2019). In today's world, financing has become a significant concern for countries, whether they are developing or developed. A well-designed capital structure possesses the potential and capacity to adapt to changes in the surrounding environment and, in turn, influences its surroundings by generating appropriate returns. SMEs play a crucial role in poverty alleviation, wealth creation, and fostering greater participation of marginalized sections of society, such as youth and women, in the economic development of nations. The growth of these enterprises strengthens the democratic ethos and civil society, while also encouraging entrepreneurs to actively engage in the economic, political, and social fabric of their countries. In fact, in most nations, the majority of employment opportunities are generated by SMEs. For instance, in the 30 high-income countries belonging to the Organization for Economic Cooperation and Development, two-thirds of the total workforce can be attributed to SMEs (Memarnejad, 2019). This study aimed to highlight the significance and role of SMEs in Iran's economy. However, certain selection criteria were applied, such as: a) selecting companies with fiscal years ending in March and no changes in their fiscal year, b) encountering incomplete data for some companies, and c) excluding banks, financial institutions, and financial investment companies due to their distinct nature of operations. Consequently, the number of companies studied was reduced to 63. Therefore, caution should be exercised when generalizing the findings of this study to other entities within the industry under consideration. Moreover, it is important to note that financing is influenced by various macroeconomic factors, including the inflation rate, gross domestic product, interest rates on facilities, and exchange rates. However, these factors were not incorporated into this study, and consequently, might impact the results. Various factors, such as asset structure, age, profitability, growth, and industry, have been identified as key determinants that can significantly influence the capital structure (Hall, 2002). Indeed, a wide range of variables have been found to impact the choice of an appropriate capital structure (Chen, 2004; Çekrezi, 2013). Additionally, this study examined factors that could potentially affect both the capital structure and profitability of companies. Recognizing that the capital structure can impact the overall value of a company, it is crucial to investigate the factors that effectively and predictably influence it. Numerous authors have conducted studies in this area, leading to the development of theories, such as the static equilibrium theory, the pecking order theory, and the agency theory. The static equilibrium theory emphasizes the balance between the tax shield of interest rate and the costs associated with debt issuance. According to this theory, a company should strive to achieve an optimal level of debt that maximizes its profitability. When the value of the tax benefit exceeds the present value of the costs associated with debt issuance, the company is considered to be at an optimal equilibrium point. Therefore, a manager aiming to maximize shareholders' wealth should carefully select a level of debt for the company that ensures the resulting tax shield outweigh the current value of the costs associated with debt creation (Rasiah & Kim, 2011). Another prominent theory of capital structure is the pecking order theory, initially proposed by Myers and Majluf. This theory suggests a preference for financing investment projects using internal funds, such as retained earnings (internal financing), rather than relying on external resources obtained through equity issuance and debt issuance. According to this theory, managers prioritize utilizing retained earnings for funding their projects. Once the accumulated earnings are depleted, they turn to debt issuance as a source of financial resources. Finally, when it becomes impractical to take on additional debt, they resort to share issuance to meet their financial needs (Rasiah & Kim, 2011). On the other hand, the agency theory posits that the optimal capital structure is achieved by minimizing the costs arising from conflicts of interest between stakeholders (Jensen and William, 1976). In this context, agency costs play a significant role in funding decisions due to the potential conflicts that may arise between shareholders and debt holders. The size of an enterprise has a profound impact on its capital structure (Rajan & Zingales, 1995; Titman & Wessels, 1988). Small firms, in particular, face unique challenges compared to larger businesses as they have often limited access to external sources of capital, such as debt. Consequently, they are compelled to make alternative financing decisions (Ang, 1991). This supports the notion that SMEs are more susceptible to financial difficulties and confront higher levels of uncertainty and risk compared to newer, smaller firms (Engel & Stiebale, 2013; Rosenbusch Brinckmann & Müller, 2013). Based on the proposed conceptual framework, the following hypotheses were put forth: Hypothesis 1: The size of small and medium-sized enterprises exhibits a significant relationship with internal financing. Hypothesis 2: The size of small and medium-sized enterprises demonstrates a significant relationship with external financing in the form of debt. Hypothesis 3: The size of small and medium-sized enterprises displays a significant relationship with external financing through equity issuance. Intangible assets possess the potential to create valuable knowledge-based competitive advantages, thereby fostering future growth (Barney, 1991; Hitt et al., 2001). However, these assets are often challenging to transfer to other businesses, making it difficult to secure external funding sources (Brierley, 2001; Revest and Sapio, 2012). Firms with intangible assets face a greater problem of asymmetric information as these assets are difficult to value. This, in turn, reduces their opportunities to obtain external financing (Clarysse et al., 2003; Harris et al., 1991). Based on the above, the following hypothesis was proposed: Hypothesis 4: Intangible assets exhibit a significant relationship with internal financing in small and medium-sized enterprises. The age of a company also plays a crucial role in determining its capital structure. Faulkender (2005) highlights an interesting point, suggesting that younger firms have less established track records and may not be as recognized by their more experienced competitors. Consequently, small and medium-sized enterprises often struggle to secure sufficient financial resources (Demirel & Parris, 2015). The pecking order theory further supports the notion that internal financing should be prioritized followed by debt financing (Myers & Majluf, 1984). Based on the aforementioned cases, the following hypotheses were proposed: Hypothesis 5: The age of small and medium-sized enterprises exhibits a significant relationship with external financing through equity issuance. Hypothesis 6: The age of small and medium-sized enterprises demonstrates a significant relationship with external financing in the form of debt. Materials & Methods The aim of this study was to examine the impact of size, age, and intangible asset variables on the dependent funding variable. Additionally, control variables, such as the operating cash, operating income ratio, current account ratio, fixed asset ratio, and working capital, were included. This study was conducted through a literature review, analyzing relevant literature and employing descriptive and inferential analyses of the data. The statistical population for this study consisted of small and medium-sized collected listed in the Tehran Stock Exchange (TSE). A sample of 63 companies was selected for the period of 2006-2021. The hypotheses were based on the models proposed by Neville & Lucy (2022) and Aghaei (2015). Regression analysis was employed to test the effect of factors on the models of internal financing, external financing, and ownership ratio. Three regression models were utilized and their definitions and methods of obtaining the variables were explained as follows: INTRNLit=β0+β1INTANGPERCit+β2CURRENTRATIOit+β3FIXEDASSETit+β4SIZEit+β5OPERATINGCASHTOINCOMEit+β6WORKINGCAPITALit+eit Model (1) Model 2 was employed to test the hypotheses regarding the factors influencing external financing (debt). In this model, the following variables were considered: INTRNL is internal financing represented as a percentage of the total capital. It is calculated by dividing the capital increase from reserves, cash inflows, and current receivables by the total capital. INTANGPER is intangible asset ratio determined by dividing the value of intangible assets by the total assets listed on the balance sheet. CURRENTRATIO is current ratio calculated by dividing current assets by current liabilities. FIXEDASSETRATIO is fixed asset ratio obtained by dividing fixed assets by total assets. SIZE is size of the enterprises measured by using the logarithm of the book value of assets. OPERATINGCASHBYINCOME is the relationship between operating cash and operating profit calculated by dividing operating cash by operating profit. WORKINGCAPITAL is net working capital calculated as the difference between current assets and liabilities. These variables were analyzed in Model 2 to assess their impacts on external financing (debt) and test the hypotheses. DEBTit=β0+β1AGEit+β2CURRENTRATIOit+β3FIXEDASSETit+β4SIZEit+β5OPERATINGCASHTOINCOMEit+β6WORKINGCAPITALit+eit Model (2) In the above model, DEBT represents the proportion of total debt to total assets, indicating the extent to which the company is financed through debt. AGE refers to the age of the enterprises calculated based on the logarithm of the number of years of activity. In addition to these variables, other control variables, such as the capital ratio, current ratio, operating cash ratio, and working capital were included. Model 3 was developed to test and validate the assumptions regarding the factors influencing the ownership ratio. The aim of this model was to investigate the variables that contributed to determining the ownership structure of the sample enterprises. EQUITYit=β0+β1AGEit+β2WORKINGCAPITALit+β3CURRENTRATIOit+β4FIXEDASSETit+β5SIZEit+β6OPERATINGCASHTOINCOMEit +eit Model (3) EQUITY represents the shareholder ratio, which is calculated by dividing the total funding by the total capital. Selection of the dependent and independent variables was based on the study conducted by Neville and Lucy (2022). Findings The data used in this study were combined at the enterprise-year level and econometric diagnostic tests were conducted. Based on the evidence, Hypothesis 1, which posited a significant relationship between the size of SMEs and internal financing, was confirmed. Additionally, Hypothesis 4, which suggested a significant relationship between intangible assets and internal financing, was also supported. The results of Model 1 can be observed in Table 1. Table 1: The results of estimating model 1 Variable Coefficient t statistic Significance level OPERATINGCASHTOREVENUE -0.73 -2.00 0.04 SIZE 0.03 3.01 0.00 WORKINGCAPITAL -4.18 -1.39 0.16 CURRENTRATIO -0.04 -1.13 0.25 FIXEDASSETRATIO -0.14 -0.94 0.34 INIBLETANGIBLEASSETRATIO 7.46 2.19 0.03 C -0.76 -2.34 0.02 AR(1) 0.01 0.47 0.63 F statistic probability 0.00 4.27 Durbin Watson statistics 2.39 Coefficient of Determination 0.58 Adjusted coefficient of determination 0.44 According to the Table 1, the coefficient of the variable of working capital is found to be significant at the given significance level, indicating a direct relationship with external financing (debt). On the other hand, the variables, such as size, operating cash ratio, current ratio, and fixed asset ratio, exhibit a significant and inverse relationship with external financing. Based on the evidence, Hypothesis 2, which suggested a significant relationship between the size of small and medium-sized enterprises and external financing (debt), was confirmed. However, Hypothesis 6, which proposed a significant relationship between the age of small and medium-sized enterprises and external financing (debt), was not supported. The results of Model 2 are presented in Table 2. Table 2: The results of estimating Model 2 Variable Coefficient t statistic Significance level AGE 0.03 1.57 0.11 SIZE -0.24 -15.09 0.00 OPERATINGCASHTOINCOME -0.043 -2.40 0.01 CURRENTRATIO -0.07 -11.68 0.00 FIXED ASSETRATIO -0.14 -4.14 0.00 WORKINGCAPITAL 1.91 2.11 0.03 C -51.90 -1.53 0.12 AR(1) 0.74 21.90 0.00 F statistic probability 0.00 69.31 Durbin Watson statistics 2.11 Coefficient of Determination 0.89 Adjusted coefficient of determination 0.87 Based on the Table 2, the variables of size, fixed asset ratio, current ratio, and operating cash ratio are found to be significantly and positively associated with the ownership ratio, while the working capital ratio exhibits a significant and negative relationship. Based on the evidence, Hypothesis 3, which suggested a significant relationship between the size of small and medium-sized enterprises and external financing (proprietary rights), was confirmed. However, Hypothesis 5, which proposed a significant relationship between the age of SMEs and external financing (proprietary rights), was not supported. The results of Model 3 are presented in Table 3. Table 3: The results of Hypothesis Test Model 3 Variable Coefficient t statistic Significance level AGE -0.02 -0.24 0.80 SIZE 0.21 15.41 0.00 WORKING CAPITAL -2.00 -3.14 0.00 FIXED ASSET RATIO 0.15 4.45 0.00 CURRENT RATIO 0.07 12.42 0.00 OPERATING CASH TO INCOME 0.03 1.97 0.04 C 29.80 0.24 0.81 AR(1) 0.71 22.70 0.00 F statistic probability 0.00 0.01 Durbin Watson statistics 2.01 Coefficient of Determination 0.87 Adjusted coefficient of determination 0.85 Discussion & Conclusions The findings of this study supported the 1st and 3rd hypotheses, which suggested a positive and significant relationship between company size and the dependent variables of internal financing and ownership ratio, respectively. Conversely, company size exhibited a negative and significant relationship with debt, in line with the second hypothesis. Additionally, the results indicated a significant positive relationship between intangible assets and internal financing, aligning with the 4th hypothesis. These findings suggested that small and medium-sized companies relied more on internal financing and utilize less debt, which aligned with the pecking order theory. This is consistent with the study conducted by O'Brien (2003). Furthermore, the study did not find a significant relationship between the age of SMEs and internal and external financing (capital structure), contradicting the 5th hypothesis. In conclusion, the results of this study highlighted the importance of company size and intangible assets in determining the financing choices of SMEs. These findings contributed to our understanding of the capital structure decisions made by SMEs. Regarding the relationship between the size of small and medium-sized enterprises and their internal and external financing, the findings align with the studies conducted by Neville and Lucy (2022), Sunaina (2020), and Aghaei et al. (2014). However, the results differ from those of Ozkan (2001), which can be attributed to variations in the economic structure, such as inflation rate and exchange rate, of the countries. Furthermore, the results support the findings of Neville and Lucy (2022) and O'Brien (2003), regarding the relationship between intangible assets, such as ideas, intellectual property, brands, business methods, and internal financing. It was confirmed that companies with a higher proportion of intangible assets faced more challenges and barriers when seeking external financing, which is consistent with the hierarchical theory. Regarding the relationship between the age of small companies and external financing, specifically through debt and ownership rights, the findings of this study are consistent with the studies conducted by Gregory (2005), Neville and Lucy (2022), and Wasiuzzaman and Nurdin (2019). However, the results differ from the study conducted by Faulkner et al. (2006), which focused on credit limits and the distinction between the public debt market (bonds) and the private debt market (banks). In their study conducted in England, they found a negative relationship between debt and age of company. The disparity in findings could be attributed to the different economic structures of the countries. This variation highlighted the importance of considering the specific context and economic conditions when analyzing the relationship between company age and external financing.