224 © 2020 by the authors; licensee Asian Online Journal Publishing Group Asian Journal of Economics and Empirical Research Vol. 7, No. 2, 224-234, 2020 ISSN(E) 2409-2622 / ISSN(P) 2518-010X DOI: 10.20448/journal.501.2020.72.224.234 © 2020 by the authors; licensee Asian Online Journal Publishing Group The Provision of Long-Term Credit and Firm Growth in Developing Countries Jennifer Watson Texas A & M University, USA. Abstract This study evaluates the impact of the provision of long-term credit (LTC) on the growth of small and young firms in developing countries. The growth of firms is evaluated on the basis of employment growth and total sales. Credit provisions have also been collected from the short- and LTC extended to the private sector. This study uses data on firm levels from more than 19000 firms in 52 countries between 2006–2016. In order to avoid the endogeneity issues that usually occur in such studies, this study has implemented a cross-country model to evaluate the significance of total bank credit, both long- and short-term, on the growth of sales and employment. The econometric results indicate that the availability of short-term credit (STC) is more beneficial for the growth of the firms, i.e. STC was found to have a significant impact on employment growth and sales in small and young firms. Although positive, LTC seemed to have no significance in the growth of the small and young firms. This study suggests that the prime reason behind these results is the availability of long-term loans for small and young firms. Keywords: Developing Countries; Bank Credit; Growth Development. Citation | Jennifer Watson (2020). The Provision of Long-Term Credit and Firm Growth in Developing Countries. Asian Journal of Economics and Empirical Research, 7(2): 224-234. History: Received: 3 July 2020 Revised: 5 August 2020 Accepted: 8 September 2020 Published: 28 September 2020 Licensed: This work is licensed under a Creative Commons Attribution 3.0 License Publisher: Asian Online Journal Publishing Group Funding: This study received no specific financial support. Competing Interests: The authors declare that they have no conflict of interests. Transparency: The author confirms that the manuscript is an honest, accurate, and transparent account of the study was reported; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. Ethical: This study follows all ethical practices during writing. Contents 1. Background of the Study .............................................................................................................................................................. 225 2. Literature Review .......................................................................................................................................................................... 225 3. Research Methods .......................................................................................................................................................................... 227 4. Findings ........................................................................................................................................................................................... 229 5. Discussion ........................................................................................................................................................................................ 233 6. Conclusion ....................................................................................................................................................................................... 233 References ............................................................................................................................................................................................ 233 http://crossmark.crossref.org/dialog/?doi=10.20448/journal.501.2020.72.224.234&domain=pdf&date_stamp=2017-01-14 http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ https://www.asianonlinejournals.com/index.php/AJEER/article/view/2186 Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 225 © 2020 by the authors; licensee Asian Online Journal Publishing Group Contribution of this paper to the literature This study contributes to existing literature by evaluating the impact of the provision of long-term credit (LTC) on the growth of small and young firms in developing countries. 1. Background of the Study In developing countries, the main focus is long-term credit (LTC) and the growth of an organization (Leroy, Baumung, Boettcher, Scherf, & Hoffmann, 2016). For this purpose, different strategies and policies have been developed by different organizations in developing countries to make it possible to increase productivity and economic growth. Developing countries focus on the achievement of LTC without focusing on the subsequent effects on the environment and other factors (Susilowati, Fuddin, Pramuja, Anindyntha, & Primitasari, 2019). Some organizations are able to consume innovative technology and tools by having greater access to long-term loans, which could also result in higher returns (Alam & Murad, 2020). Badayi, Matemilola, Bany-Ariffin, and Theng (2020). This illustrates the fact that a greater provision of LTC helps to benefit new firms at the country level. The overall process and phenomenon of LTC and its impacts have been gaining considerable attention from academic experts and other analysts over the past few years (Ansah et al., 2016). Nevertheless, the performance of firms has been noticed by several scholars and analysts in different developing nations and regions, as there are a significant amount of firms and organizations that are performing successfully (Léon, 2020). Andrade, Cahn, Fraisse, and Mésonnier (2019) recommended that, in order to address any gaps or shortcomings in a firm’s performance (FP), some contextual factors and variables like LTC and STC, which affect the quality of a firm, need to be identified and evaluated in detail. Research on the impact of the growth of employment (GoE) on FP is limited, so studies needs to be conducted on firms and businesses in different developing regions and countries (Leon, 2019). As of yet, no studies have evaluated the direct impact of GoE on LTC and STC performance; therefore, this research is new and justified in understanding the direct influence of GoE and sales of total sales (STS). With regard to external debt, Figure 1 shows that the ratio of debt was different over different time periods. Figure 1. Average external debt payments. In line with the above justification statement, the aims of the paper are: • To examine the exclusive impact of GoE on STC and LTC in developing nations. • To analyze the influence of STS on the STC and LTC in developing countries. • To explore the impact of GoE and STS on bank credit (BC) in developing countries. The given study empirically identifies whether or not a higher degree of LTC provision influences the development of small and medium organizations and businesses. Therefore, the given effort has profound theoretical benefits, as well as practical impacts. Theoretically, the results of the given study contribute to the current knowledge on the above variables through an analysis of the effects of GoE on LTC and STC in developing countries. The remainder of the research study is framed as follows: Section two discusses and presents current literature on long-term and short-term finance, as well as the organization’s overall performance and presentation; Sections three and four consist of the methodology of the study and the data of the paper; Section five presents the main econometric outcomes and findings, as well as robustness checks; Finally, section six provides a significant demonstration on the types of access to credit and a logical conclusion. 2. Literature Review 2.1. Theory of Long-Term Finance (LTF) This theory is mainly studied and developed within the disciplines of management, finance, economics, and accountancy (Schoenmaker & Schramade, 2019). Theoretically, this theory is concerned with the investment and deployment of assets and liabilities over time, as it is predominantly about performing valuation and asset or money allocation that is based on risk, challenges, and uncertainty over future consequences, while incorporating the time value of money (Schroeder, Clark, & Cathey, 2019). According to this theory, financing and crediting play a crucial role in the development of every business and firm, mainly because, according to Schoenmaker and Schramade (2019), firms often need financing to pay for assets, equipment, and other significant items for their business. This theory also states that LTC and support are usually needed to acquire new assets and resources for the overall development of the business and firm expansion (Andersen, 2020). Moreover, this theory demonstrates the fact that LTF is expected to have a direct impact on overall business development by stimulating some forms of investment. This leads to an increase in employment in the region. In other words, organizations incorporate LTC Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 226 © 2020 by the authors; licensee Asian Online Journal Publishing Group to buy fixed resources and assets to finance working capital, which leads to an increase in sales and employment (Dou & Ji, 2019). 2.2. The Relationship between Employment Growth and Bank Credit Sharifi, Haldar, and Rao (2019) describe the fact that the relationship between bank credit and employment growth as complicated because the variables that play a vital role in measuring the access of an organization to finance, which also reflects its petition for labor. Botev, Égert, and Jawadi (2019) have examined the fact that organizations that have access to finance are more likely to experience employment growth than those that do not have access to finance. The research conducted by Aghion, Bergeaud, Cette, Lecat, and Maghin (2019) has stated that the relationship between bank credit and employment growth can be determined with the help of credit bureaus that act as an exogenous shock for the supply of credit. This also leads to employment growth of up to 5%, compared to countries where CB has not been introduced yet. It has been proved by the theory of LTF that this relationship focuses on the deployment of resources and accountabilities. Therefore, this paper poses the following hypothesis: H1: There is a direct and significant connection between bank credit and employment growth. 2.3. The Interdependence between the Growth of Employment and Short-Term Credit According to Aghion et al. (2019), an STC is a form of credit that is developed to support short-term personal credit, as well as business and firm capital. According to Cecchetti and Kharroubi (2019), this directly impacts levels of employment. Moreover, Palacín-Sánchez, Canto-Cuevas, and di-Pietro (2019) demonstrate that short-term credit (STC) is a type of credit that mainly includes a borrowed wealth quantity and interest that must be paid by a given period—usually within a year from getting the loan. These factors all directly and significantly impact the GoE in firms and businesses. According to Mian, Sufi, and Verner (2020), STC is a value option and opportunity, especially for small firms or startups in developing countries, which results in a huge amount of employment and firm growth. Moreover, according to the corporate financial institute (CFI), an STC is a form of loan and credit that is entirely generated to support small business capital requirements because STC provides fast cash and capital when the cash flow of a business is deficient (Ferrando & Mulier, 2013). These types of credits and loans have shorter repayment periods than traditional credit, which is why they are extremely attractive and positive options for employment generation in small firms. According to Li, Loutskina, and Strahan (2019), this directly affects the overall development and performance of the business. The above theory of financing supports the interdependence between STC and GoE and the growth of the firm because the theory of LTF states that credit and financing prove to be significant for the creation of employment in businesses, as they provide quick capital to firms. H2: There is a significant connection between employment growth and STC. 2.4. The Nexus between the Development of Employment and Long-term Credit LTC and financing can be described as any financial credit tools with a maturity limit of one year, such as bank credits, leasing and bonds, and public and private equity tools. According to Monaghan and Ingold (2019), maturity refers to the amount of time between the conception of a financial claim (bond, financial tools, and loan) and the final payment date and the point at which the remaining interest is due. Extending the capability design of capital is typically seen to be the basis of substantial employment expansion and firm growth because LTC contributes to faster employment growth, significant welfare, and the stability of the business in two favorable ways—by minimizing rollover challenges for borrowers and by improving the availability of LTC tools. This allows employees and businesses to respond life-cycle risks (Aghion et al., 2019). Consequently, the above discussion leads to the establishment of the following hypothesis: H3: There is a favorable connection between employment growth and LTC. 2.5. The Association between Sales of Total Sales and Bank Credit The performance of a firm is primarily dependent on the positive relationship between the growth of total sales and bank credit. Nurmawati, Rahman, and Baridwan (2020) state that the access of a firm to finance will help it to acquire financial assets and instruments that help it to increase its economic growth Capasso, Gianfrate, and Spinelli (2020). Banks are considered to be the best engine for the increment of the economic growth of a firm. Dai, Byrnes, Liu, and Vasarhelyi (2019) describe the positive impact of bank loans on the development of a business if finance is available and if the added value that has been created by those sectors is available. The LTF theory has supported this relationship by stating that bank credit plays a direct role in the development of a firm, along with the sales of total sales, because finance is required by organizations to pay for equipment and assets. Thus, the present research poses the below hypothesis: H4: There is a positive interdependence between the sales growth of firms and bank credit. 2.6. The Interrelation between Sales of a Total of Sales and Short-Term Credit STC and finance prove to be very beneficial and advantageous for firms and businesses who need cash flow for further growth and sales; STC can be an invaluable process to get a business through a difficult period until additional resources become available. According to Capasso et al. (2020), the major advantage of STC in terms of sales is that, upon approval, a business can receive benefits within a month, as well as receiving a higher level of total sales and revenue benefits. The amount of STC is optimal for the overall sales of the business, which further impacts the entire economy of the firm. In well-structured markets and businesses, borrowers will enter short-term contracts based on their financial requirements and how they agree to distribute the issues involved at various maturities. This directly influences the sales process and positively impacts the sales of total sales ratio (Fuertes- Callen & Cuellar-Fernandez, 2019). What matters for the financial capability of the contracts is that borrowers have complete access to financial tools that allow firms to experience a significant degree of sales and revenue. Therefore, this study proposes the following hypothesis: H5: There is a positive relationship between the growth of a firm’s sales and STC. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 227 © 2020 by the authors; licensee Asian Online Journal Publishing Group 2.7. The Connection between the Sales of Total Sales and Long-Term Credit According to Wang, Wu, Yin, and Zhou (2019) the advantages and benefits offered by LTC compared to STC are mostly related to their different maturities and procedures, as long-term financing offers longer benefits, in terms of financial benefits and sales, at a fixed-rate. As described by Chaudhuri, Voorhees, and Beck (2019), LTC enables businesses and firms to align their capital structures with their long-term strategic objectives, which provides direct benefits in terms of sales and revenue, thereby affording the firm more time to realize a return on investment (RoI). The maturity linked to long-term financing effectively affects sales, as well as improving the revenue generated from total sales. Empirical papers have pointed out that a firm can gain huge sales and revenue benefits from long-term connections with the same investor (Karabarbounis & Macnamara, 2019). Recent research papers have demonstrated that LTC provides greater flexibility in terms of sales and resources to fund capital demands. Hence, based on the above arguments, this study hypothesizes that: H6: There is a direct and favorable connection between long-term financing and the sales growth of firms. 3. Research Methods This study used methods introduced by Fafchamps and Schündeln (2013) and applied them to a multiple country framework. This method differentiates from the original strategy in two ways. The method developed by Fafchamps and Schündeln (2013) considers municipalities and, in line with recent work by Léon (2020), this study considers countries. The method followed for calculating growth opportunities is perceived to be a bit different than the original method. A specific measure for each sector-country has been developed. The growth opportunity index has been calculated on the basis of the method followed by Fafchamps and Schündeln (2013), which considers two measures of inculcation for each reference group. Firm size and age have been considered as the characteristics for the reference groups. The basic econometric model is as follows: 𝑔𝑖𝑠𝑐𝑡 = 𝛽(𝐺𝑠𝑐𝑡 × 𝐹𝑐𝑡) + 𝛿𝐺𝑠𝑐𝑡 + 𝛼𝑠𝑡+𝛼𝑐𝑡 + 휀𝑖𝑠𝑐𝑡 (1) where the subscripts i, s, c and t refer to firm, country, sector and year. The term 𝑔𝑖𝑠𝑐𝑡represents the annual rate of growth for the firm (i) belonging to sector (s) in country (c) and in the year (t). The term 𝐹𝑐𝑡represents the development of the banking sector in each country. The study introduces vectors of sector-year dummies and country year dummies so that the unobserved country and sectoral factors can be controlled. The term 𝐺𝑠𝑐𝑡 is included in the regression, in order to account for shocks affecting the sectors and countries that are measured by growth opportunities. Equation 1 has been extended to include short- and long-term loans and credit availed by the organizations: 𝑔𝑖𝑠𝑐𝑡 = 𝛽𝑆𝑇(𝐺𝑠𝑐𝑡 × 𝐹𝑐𝑡 𝑆𝑇) + 𝛽𝐿𝑇(𝐺𝑠𝑐𝑡 × 𝐹𝑐𝑡 𝐿𝑇) + 𝛿𝐺𝑠𝑐𝑡 + 𝛼𝑠𝑡+𝛼𝑐𝑡 + 휀𝑖𝑠𝑐𝑡 (2) The term 𝐹𝑐𝑡 𝑆𝑇 represents the ratio of the STC to the GDP of country (c) in time (t), and the term 𝐹𝑐𝑡 𝐿𝑇 represents the ratio of the LTC of a firm to the GDP in a certain country (c) and time (t). The literature supports the supposition that the availability of STC is beneficial for firm growth. 3.1. Variables Firm level data was extracted from the ES database of the World Bank. The firm level data was used to build the dependent variables: employment growth and total sales growth. The data on total sales and the number of employees from the preceding year and a further three years before the surveys were also included. Data regarding sales has also been collected on the same grounds. However, the sales values were deflated using a base year (2010) and the values for each country’s GDP deflator was sourced from WDI. The index of growth opportunity was calculated using the average rate of growth of the reference group that comprises less constrained firms. In the basic model, 50 employees were considered. Some sectors in developing economies do not include firms with more than 50 or 100 employees; Therefore, they are both considered to be the benchmark size. Recent research has proven that older firms are more capable of gaining access to bank loans than younger organizations, irrespective of size. Therefore, the reference threshold for a firm’s age has been mandated at 25 and 20 years. The growth opportunity in this scenario reflects the growth of the organizations’ employment and sales. Dummy variables regarding the sector of the firm, i.e. whether it is a subsidiary, exporter, privately held, or government owned, are also introduced in the study. The independent variables represent the maturity of the bank credits allowed for firms under consideration. Data regarding these variables were collected from the credit structure database. The independent variables in this study are: The total bank credit over GDP as a sum of short- and LTC, STC, defined as the credit extended by the banking sector over GDP to organizations with a maturity period of one year or less, and LTC, defined as the credit extended by the banking sector over GDP with a maturity of over a year. The variable total credit accounts for the total loans extended to organizations by banks. 3.2. Sample The total sample consisted of 52 countries characterized by their size and age. The period under consideration was 2006–2016. The sample consisted of firms from 43 countries, with the final sample representing a total of 19282 firms from countries under consideration. In Table 1, the first column represents the name of the country from which the data was collected; the second column details the year in which the data was collected; the third column represents the total number of firms registered on the database; and the next two columns (size and age) represent the total number of firms characterized according to specifications of age and size. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 228 © 2020 by the authors; licensee Asian Online Journal Publishing Group Table 1. Sample Country Year Obs. Benchmark Size>50 Size>100 Age>20 Age>25 Albania 2007 216 19 7 1 1 Albania 2013 227 31 8 6 0 Azerbaijan 2009 265 56 30 59 55 Azerbaijan 2013 291 37 16 24 12 Bahamas 2010 130 33 17 64 47 Barbados 2010 132 36 26 52 35 Belarus 2008 222 75 54 38 35 Belarus 2013 294 71 47 68 34 Botswana 2006 242 42 21 40 24 Botswana 2010 216 48 24 61 41 Bulgaria 2007 942 273 160 42 33 Bulgaria 2009 238 48 30 13 12 Bulgaria 2013 272 60 35 68 11 BurkinaFaso 2009 283 39 20 45 34 Burundi 2006 211 14 3 24 13 Burundi 2014 131 20 7 34 22 Chile 2004 872 366 239 385 300 Chile 2006 802 278 160 418 318 Chile 2010 913 375 253 569 467 Congo 2009 57 6 3 12 10 Croatia 2013 303 50 29 92 25 Czech Republic 2009 187 64 38 6 5 Czech Republic 2013 227 47 26 91 4 Coˆte d’Ivoire 2011 257 32 25 36 18 DR Congo 2007 265 17 9 42 36 DR Congo 2011 286 45 28 72 41 DR Congo 2012 362 38 14 57 34 Djibouti 2014 131 4 4 51 34 Dominica 2011 145 14 5 33 24 Estonia 2008 221 89 55 19 11 Estonia 2014 210 34 19 58 3 Fyr Macedonia 2006 283 80 47 45 36 Fyr Macedonia 2012 318 31 15 84 18 Gabon 2007 91 15 9 24 19 Georgia 2006 282 54 25 11 9 Georgia 2011 251 31 12 24 11 Grenada 2012 121 18 9 61 46 Guinea 2008 185 8 4 11 8 Guinea Bissau 2009 131 6 4 14 7 Hungary 2006 278 111 74 18 8 Hungary 2014 240 47 31 57 11 Jordan 2013 372 103 71 129 87 Kazakhstan 2010 415 140 93 10 7 Kazakhstan 2012 485 82 52 42 13 Kosovo 2008 226 21 12 30 16 Kosovo 2011 156 15 6 47 11 Kyrgyz Republic 2008 181 42 22 28 32 Kyrgyz Republic 2012 241 55 25 27 8 Latvia 2006 210 94 58 7 7 Latvia 2012 237 34 21 38 4 Lithuania 2007 239 71 49 14 11 Lithuania 2012 186 45 23 38 8 Madagascar 2007 38 17 9 6 5 Madagascar 2007 380 98 51 126 88 Madagascar 2014 278 62 45 63 42 Malaysia 2016 537 223 123 169 92 Mali 2008 421 12 7 46 26 Mali 2011 216 14 2 24 14 Mali 2015 104 32 10 35 25 Morocco 2014 282 92 52 112 88 Nigeria 2007 95 13 2 24 22 Nigeria 2013 1,257 95 43 313 185 Poland 2007 248 73 45 53 32 Poland 2012 384 82 46 158 51 Romania 2008 362 127 83 12 12 Romania 2012 466 97 52 105 11 Russia 2008 783 383 264 116 102 Russia 2011 3,167 628 324 253 115 Rwanda 2007 141 13 8 29 18 Rwanda 2012 183 37 17 30 32 Senegal 2002 36 15 9 10 7 Senegal 2008 400 28 11 69 52 Senegal 2013 410 52 27 102 65 Serbia 2008 318 98 70 80 75 Serbia 2012 287 65 42 104 28 Ukraine 2009 661 189 133 90 81 Ukraine 2012 670 130 78 77 23 Yemen 2011 312 57 33 93 71 Yemen 2012 272 44 27 122 72 Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 229 © 2020 by the authors; licensee Asian Online Journal Publishing Group 4. Findings The descriptive statistics have been reported in Table 1. It can be seen that the mean employment growth is 4.4, whereas the sales growth is 0.8 percent. Moreover, the descriptive analysis showed that most firms wer 15 years old and the average number of employees appointed was eleven. Moreover, 17 percent of these firms belong to the export sector, 14 percent operate as subsidiaries, 5.6 percent operate as private organizations and 0.39 percent are owned by the government. The average amount of total credit extended to organizations is 37 percent; of this percentage, 12 percent has been characterized as a short-term loan and 25 percent has been considered to be a long-term loan. Table 2. Descriptive statistics Variable Mean Std. Dev Min Max Dependent Variable Growth of employment 4.4207 11.359 -31.951 47.144 Growth of total sales 0.8468 20 -53.594 65.369 Independent variables F (total credit over GDP) 36.813 27.501 0.7265 122.57 FST (STC over GDP) 11.842 8.64 0.703 51.764 FLT ( over GDP) 25.342 23.051 0.027 92.049 Control variables Size (in log) 2.4109 0.7935 0 3.8919 Age 15.189 11.147 0 100 Export 0.1759 0.3805 0 1 Subsidiary 0.1443 0.3511 0 1 State-owned 0.0039 0.0612 0 1 Privately-held 0.5624 0.496 0 1 Table 2 summarizes the credit representation of the total sample, i.e. the 52 developing countries that have been taken into consideration. The basic descriptive statistics displayed in Table 2 show that the total credit represents 47 percent of the GDP of the developing countries, and about 60 percent of the loans have credit maturities that are greater than one year; In other words, it is predominantly long-term loans that have been issued. It can be seen from the trends presented in the table that the level of LTC increases with the relative level of income. For example, we can see that, in low income countries, long-term bank loans represent less than 5 percent of the total loans, although they exceed 50 percent in high-income countries. Table 3. Credit information by country Credit over GDP Perc. of Sample Total Short-t. Long-t. Long-t.a Obs Country All countries 46.8 13.7 33.7 59 1,200 52 By income level Low income 11.5 7.1 4.4 33.7 194 10 Lower middle income 21.7 9.5 12.2 48.0 168 10 Upper middle income 42.7 11.8 30.9 65.3 297 12 High income 70.4 19.2 51.2 70.1 541 20 4.1. Total Credit First, the effects of the total credit on employment growth have been analyzed and are presented in Table 3. The coefficient of interest is the interaction term G*F. The positive coefficients imply that small firms are growing more successfully, especially if they are positioned in a country with a high level of credit. The results also point out that total credit doesn’t necessarily stimulate employment growth in small firms. The computed coefficients of interaction terms are positive, yet insignificant. The young firms (the results are shown in columns 6–10) provide more positive conclusions, indicating that the impact of total credit on employment growth is significant at the 10 and 5 percent level of significance. The firm level control variables are reliable and consistent with expectations. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 230 © 2020 by the authors; licensee Asian Online Journal Publishing Group Table 4.Total credit and employment growth Benchmark large firms (Employees > 50) Benchmark old firms (Age >20) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) G*F 0.000253 0.000472 0.00104 0.00395 0.0041 0.00035 0.000728 0.000635 0.00543** 0.00465* (-0.26) -0.48 -0.86 -1.2 -1.37 -0.34 -0.66 -0.51 -2.04 -1.69 G 0.0685* 0.0368 0.00512 0.01 0.0975 0.0457 0.0204 0.0349 0.0166 0.242 -1.71 -0.86 -0.2 (-0.32) -0.46 -1.06 -0.4 -0.62 (-0.31) (-1.19) Empl 4.302*** 3.966*** 3.967*** 3.966*** 2.282*** 2.071*** 2.073*** 2.078*** (-11.08) (-8.31) (-8.30) (-8.31) (-9.61) (-7.55) (-7.57) (-7.57) Age 0.0891*** 0.0967*** 0.0967*** 0.0979*** 0.268*** 0.301*** 0.303*** 0.302*** (-7.25) (-7.44) (-7.45) (-7.48) (-7.91) (-8.78) (-8.81) (-8.81) Export 1.947*** 2.042*** 2.038*** 2.038*** 1.765*** 1.861*** 1.860*** 1.861*** -6.46 -7.37 -7.2 -7.3 -7.42 -7.38 -7.38 -7.3 Subsidiary 0.972*** 1.191** 1.191*** 1.193*** 0.935*** 1.062*** 1.066*** 1.064*** -2.75 -2.62 -2.62 -2.63 -2.85 -2.73 -2.73 -2.73 State-owned 0.108 1.276 1.293 1.28 0.392 2.286** 2.301** 2.295** (-0.06) (-0.84) (-0.85) (-0.85) (-0.27) (-2.54) (-2.57) (-2.56) Privately-held 0.642** 0.652* 0.654* 0.653* 0.592** 0.572* 0.575* 0.571* -2.17 -1.87 -1.88 -1.87 -2.38 -1.84 -1.85 -1.83 R2 0.003 0.101 0.098 0.098 0.098 0.003 0.078 0.09 0.08 0.09 Note: ∗, ∗∗ and *** depicts 0.01, 0.05 and 0.10 levels of significant respectively. Table 5. Total credit and sales growth Benchmark large firms (Employees > 50) Benchmark old firms (Age >20) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) G*F 0.000732 0.000961 0.00062 0.000681 0.000172 0.000756 0.000172 0.000439 0.000419 0.00028 -0.68 -0.91 -0.47 (-0.26) (-0.05) (-0.91) (-0.22) (-0.52) -0.16 -0.07 G 0.0322 0.0241 0.032 0.0472 0.183 (0.93) 0.0356 0.0157 0.0176 0.00822 0.0256 -1.27 -0.88 -0.83 -1.06 -1.17 -0.48 -0.41 -0.18 (-0.13) Empl 2.101*** 2.044*** 2.033*** 2.032*** 1.275*** 1.235*** 1.256*** 1.237*** (-5.03) (-3.92) (-3.92) (-3.92) (-5.33) (-4.62) (-4.62) (-4.62) Age 0.127*** 0.132*** 0.132*** 0.132*** 0.457*** 0.498*** 0.498*** 0.498*** (-7.08) (-6.32) (-6.31) (-6.31) (-7.23) (-7.08) (-7.07) (-7.07) Export 1.864*** 2.388*** 2.386*** 2.384*** 1.688*** 2.202*** 2.198*** 2.201*** -3.08 -3.87 -3.86 -3.86 -3.77 -4.54 -4.53 -4.53 Subsidiary 1.526** 1.223* 1.222* 1.221* 1.097** 0.892 (1.56) 0.893 (1.56) 0.892 (1.56) -2.45 -1.71 -1.71 -1.71 -2.15 State-owned 1.032 (0.35) 3.908 (1.55) 3.921 (1.56) 3.931 (1.58) 0.668 (0.32) 2.252 (1.04) 2.238 (1.03) 2.241 (1.03) Privately-held 0.0412 0.113 0.113 0.106 0.727 (1.17) 0.655 (0.92) 0.658 (0.92) 0.654 (0.91) -0.06 (-0.15) (-0.15) (-0.14) R2 0.005 0.021 0.023 0.023 0.023 0.003 0.024 0.028 0.028 0.028 Note: ∗, ∗∗ and *** depicts 0.01, 0.05 and 0.10 levels of significant respectively. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 231 © 2020 by the authors; licensee Asian Online Journal Publishing Group Table 6. Long- and short-term credit and growth of employment. Benchmark large firms (Employees > 50) Benchmark old firms (Age >20) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) G*FST 0.00635* 0.00603+ 0.0102** 0.0105** 0.0104** 0.00341 0.00186 0.00686 0.00972** 0.0109** -1.74 -1.52 -2.28 -2.36 -2.32 -0.67 -0.38 -1.32 -2.22 -2.36 G*FLT 0.00158* 0.000643 0.00032 0.00102 0.0012 0.000189 0.000582 0.000216 0.00482+ 0.00287 (-1.78) (-0.58) (-0.25) -0.32 -0.32 (-0.13) -0.3 (-0.13) -1.48 -0.79 G 0.0332 0.00688 0.0513 0.0562 0.0348 0.0282 0.0126 0.00473 0.043 0.377+ -0.72 -0.13 (-0.83) (-0.91) (-0.14) -0.52 -0.25 (-0.07) (-0.76) (-1.58) Empl 4.312*** 3.967*** 3.967*** 3.967*** 2.282*** 2.072*** 2.073*** 2.074*** (-11.06) (-8.32) (-8.32) (-8.32) (-9.61) (-7.54) (-7.58) (-7.59) Age 0.0888*** 0.0969*** 0.0968*** 0.0966*** 0.268*** 0.301*** 0.302*** 0.302*** (-7.23) (-7.43) (-7.43) (-7.43) (-7.91) (-8.78) (-8.81) (-8.82) Export 1.948*** 2.042*** 2.041*** 2.042*** 1.766*** 1.861*** 1.862*** 1.863*** -6.48 -7.42 -7.41 -7.41 -7.42 -7.38 -7.42 -7.42 Subsidiary 0.971*** 1.198*** 1.199*** 1.197*** 0.935*** 1.062*** 1.065*** 1.064*** -2.74 -2.64 -2.64 -2.64 -2.87 -2.73 -2.73 -2.73 State-owned 0.0874 1.236 1.246 1.246 0.392 2.282** 2.293** 2.286** (-0.07) (-0.82) (-0.82) (-0.82) (-0.28) (-2.57) (-2.56) (-2.55) Privately-held 0.645** 0.655* 0.658* 0.658* 0.594** 0.589* 0.586* 0.581* -2.17 -1.99 -1.88 -1.88 -2.32 -1.87 -1.89 -1.87 R2 0.003 0.101 0.2 0.2 0.2 0.003 0.077 0.07 0.06 0.07 Note: ∗, ∗∗ and *** depicts 0.01, 0.05 and 0.10 levels of significant respectively. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 232 © 2020 by the authors; licensee Asian Online Journal Publishing Group Table 7. Short- and long-term credit and sales growth Benchmark large firms (Employees > 50) Benchmark old firms (Age >20) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) G*FST 0.00583+ 0.00692* 0.00842+ 0.00867+ 0.00941+ 0.00815* 0.0101** 0.00918** 0.00888* 0.00854* -1.61 -1.92 -1.48 -1.5 -1.57 -1.93 -2.43 -2.05 -1.88 -1.82 G*FLT 0.000557 0.000537 0.000728 0.00544* 0.00632+ 0.00148** 0.00101* 0.000942 0.00227 0.00323 (-0.38) (-0.36) (-0.46) (-1.77) (-1.62) (-2.45) (-1.78) (-1.33) (-1.12) (-1.26) G 0.00458 0.00785 0.023 0.00442 0.0966 0.0187 0.0454 0.0496 0.0422 0.172 -0.15 (-0.27) (-0.46) (-0.08) (-0.42) (-0.52) (-1.17) (-0.94) (-0.77) (-0.85) Empl 2.098*** 2.054*** 2.048*** 2.048*** 1.287*** 1.252*** 1.248*** 1.250*** (-5.04) (-3.92) (-3.91) (-3.91) (-5.34) (-4.64) (-4.63) (-4.63) Age 0.127*** 0.133*** 0.133*** 0.132*** 0.457*** 0.501*** 0.501*** 0.501*** (-7.08) (-6.32) (-6.33) (-6.32) (-7.25) (-7.11) (-7.11) (-7.11) Export 1.868*** 2.393*** 2.388*** 2.386*** 1.687*** 2.198*** 2.198*** 2.198*** -3.2 -3.87 -3.86 -3.88 -3.78 -4.52 -4.52 -4.52 Subsidiary 1.513** 1.217* 1.212* 1.212* 1.104** 0.908 (1.61) 0.901 (1.61) 0.907 (1.61) -2.42 -1.72 -1.72 -1.72 -2.17 State-owned 1.076 (0.36) 3.998 (1.58) 4.086 (1.63) 4.102 (1.63) 0.606 (0.27) 2.202 (1.02) 2.217 (1.02) 2.226 (1.02) Privately-held 0.0441 0.106 0.102 0.104 0.757 (1.21) 0.694 (0.96) 0.695 (0.97) 0.691 (0.96) -0.07 (-0.15) (-0.14) (-0.15) R2 0.004 0.021 0.023 0.023 0.023 0.001 0.022 0.026 0.026 0.026 Note: ∗, ∗∗ and *** depicts 0.01, 0.05 and 0.10 levels of significant respectively. Asian Journal of Economics and Empirical Research, 2020, 7(2): 224-234 233 © 2020 by the authors; licensee Asian Online Journal Publishing Group Table 4 represents the evaluation of the impact of total credit on total sales growth. The growth opportunity, i.e. the level of the sales growth, is evaluated by calculating the average growth rate of the total sales of large firms (firms with more than 50 employees) and old firms (firms that are older than 20 years). The interaction term F*G, i.e. the evaluation of the sales growth and total credit, were positive; however, the coefficients weren’t significant. The firm level control variables are reliable and consistent with expectations. Small and young firms were observed to have grown significantly faster than their counterparts. Firms belonging to the export sector and subsidiaries presented consistent growth rates that were significant at the 10 and 5 percent levels. 4.2. Effects of Short-Term and Long-Term Credit Table 5 represents the impact of the availability of short-term loans on firm growth from the perspective of employees. Long-term loans, however, seem to have no impact. In particular, the coefficients of the interaction term generated by short-term loans and the growth of employment were statistically significant and positive, irrespective of the size of the firm. The effects of STC were also appeared to be economically significant. On the other hand, it can be seen that the impact of LTC and the interaction terms generated between LTC and employment growth values were positive yet insignificant. Table 6 presents the impact of short- and LTC on the firms’ growth of sales. First, it can be seen that short- term loans benefit the growth of the firm. Second, the results also indicate that the ratio of LTC over GDP isn’t significant; it does not seem to have a reasonable impact on the performance of firms. These results imply that STCs are beneficial for the growth optimization of young and small firms. 5. Discussion This study evaluated the impact of the long- and STC on the employment and sales growth opportunities of firms in 52 developing countries. A wide number of studies have analyzed the effects of long- and STC on the overall performance and growth of organizations. A significant proportion of studies, however, found an insignificant link between LTC and firm growth. A reasonable explanation is that LTC isn’t crucial for daily operations, as working capital requirements of small and young firms is markedly important (Field, Pande, Papp, & Rigol, 2013; Getachew, 2016; Lay, 2020; Leon, 2018; Leon, 2019). Studies by Fisman and Love (2007) and Fafchamps and Schündeln (2013) studied the impact of growth opportunities by including it in the base model and analyzing its relationship with credit growth maturity. These studies also reported the insignificance of LTC extensions and their relevance to firm growth. A study by Léon (2020) focused on the external financial dependence of organizations and credit maturity, and the results indicated that external financial dependence is significant for the STC of firms. This study also pointed out that young firms are significantly correlated with external financial dependence and the provision of STC. A study by Khan, Ghafoor, Qureshi, and Rehman (2018) empirically investigated the role of the banking market, evaluating developments in the financial structure and the growth of financial dependence in the manufacturing sector of china. The study evaluated growth between1999– 2014. The study employed structural and non-structural methods to evaluate the impact of the banking market structure and its relationship with the growth of the manufacturing sector. The results indicated that competition between banks inspires the growth of the industry. Chauvet and Jacolin (2017) explored the effects of firm performance from the perspective of bank concentration or credit extension activities, and the financial inclusion of firms in emerging and developing countries. This particular study employed the use of firm level data from 79 developing and emerging countries. The results indicated that the distribution of financial services across firms seems to have a positive impact on the overall growth of organizations. This positive impact or growth becomes greater when the bank’s concentration is less significant. 6. Conclusion This study evaluated the impact of the provision of long- and STC on the growth of the firms. The study was performed on a dataset of 52 developing countries with a total of 19282 firms characterized on the basis of size (number of employees) and age. The growth of the firms was evaluated on the basis of employment growth and sales. It appears that entrepreneurs in developing economies should be able to benefit from the provision of LTC so that investments can be extended. However, this study found that LTC doesn’t have an impact on the sales and employment growth of small and young firms in developing economies. The results also indicated that the availability of STC is beneficial for the growth of small and young firms. The evaluation of the total bank credit pointed out that growth in sales and employment is significant over shorter periods of time because of capital requirements. The results of this study can be applied when developing policies. The results have indicated that access and availability of STC is of considerable importance for the growth of small firms. Therefore, policies that are developed in favor of LTC may have a negative impact on the growth of new firms. As a result, banking policies in developing economies need to be adjusted so that the client base can be widened, and loans can be extended to parties other than existing clientele. One limitation of this study is the fact that it explores LTC and how it isn’t beneficial for the growth of small firms, but it doesn’t explore the rationale behind this occurrence. Moreover, the data set was only 52 developing countries, so future studies should focus on diversifying and increasing the sample size. References Aghion, P., Bergeaud, A., Cette, G., Lecat, R., & Maghin, H. (2019). Coase lecture-the inverted-U relationship between credit access and productivity growth. Economica, 86(341), 1-31.Available at: https://doi.org/10.1111/ecca.12297. Alam, M. M., & Murad, M. W. (2020). The impacts of economic growth, trade openness and technological progress on renewable energy use in organization for economic co-operation and development countries. 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