Financial development and business growth: A case of the Southern Key Economic Region

Abstract

This paper employs generalized methods of moment (GMM) to analyze the enterprise data set collected from the General Statistics Office in the period 2005–2018 to provide insight on the influence of financial development on business growth: the case of the Southern Key Economic Zone (SKEZ). The empirical results indicate that financial development plays an important role in business growth. However, providing financing to offset scale has the potential to increase sales but reduce business growth. Thus, businesses in the SKEZ need to carry out some following points. First, corporate managers not only focus on growth and considering as important as sales and productivity throughout their operations but on strengthening the depth of the financial system to allow businesses to get favorable conditions to receive external financial sources. Second, policymakers should promote a well-developed financial system that can ease credit constraints for businesses.

Keywords:

• financial development
• business growth
• Southern Key Economic Region

JEL code:

• C23
• D01
• G30
• I25

1. Introduction

The Southern Key Economic Region (SKER) includes the following provinces and cities: Ba Ria—Vung Tau, Binh Duong, Binh Phuoc, Long An, Tay Ninh, Tien Giang and Ho Chi Minh City. In 2017, the population of the SKER accounted for only 21.14% and the labor force accounted for 20.14%, but contributed to 37.48% of GDP and 40.94% of the country’s total budget revenue. (General Statistics Office, 2019). This achievement is largely attributed to the industrial sector and local businesses. According to the General Statistics Office (2019), the SKER has 236.6 thousand business entities, accounting for 36.14% of the number of businesses and contributing more than 41.74% of tax and fee revenues in the whole country in 2017. This shows that business growth in the SKER is important not only for the southern region but also the whole country.

Academically, corporate growth is an essential feature of a market economy (Dosi et al., 2020) and businesses can only create value through growth (Vaz, 2021). At the micro level, corporate growth creates many new jobs and at the macro level, corporate growth not only creates wealth and develops society (Ahlstrom, 2010; Vaz, 2021) but also drives industry development (Dosi et al., 2020). As a result, high-growth firms make large contributions to economic prosperity (Vincent et al., 2021). Therefore, many empirical studies have measured and evaluated business growth (Vaz, 2021). Studies demonstrate the importance of entrepreneurial motivations in the development of enterprises (Zhou & Wit, 2009); examine the impact of factors affecting business growth through testing Gibrat’s law (Burger et al., 2017); the influence of enterprise resources (capital, labor, assets, etc) on growth (Gilbert et al., 2006; Zhou & Wit, 2009); the role of financial resources in business development (Arellano et al., 2012; Lee et al., 2019).

Although the relationship between financial development and growth has been studied for decades, most studies have looked at financial development at the country level and assessed its impact of financial development on economic growth by national or transnational data (T.V. Tran et al., 2020; Topcu & Çoban, 2017). Understanding of the impact of financial development on corporate growth is limited (Mishra & Deb, 2018) and assessments are modest (O’Toole & Newman, 2017; Topcu & Çoban, 2017). Although finance is important to businesses, the link between financial development and business growth is not the same as the strong link between the financial sector and firms in corporate finance theory (Mishra & Deb, 2018). Financial development to reduce financial difficulties is to minimize the sensitivity of investment cash flows, thereby having a positive impact on business investment (Gupta & Mahakud, 2019).

Although there have been some studies discussing the role of financial development in business growth abroad but so far it has not been conducted in Vietnam. Although the research gap is clear, due to the limited resources, the paper is the first study to attempt to broaden understanding of the role of financial development on business growth in the most important region in Vietnam that of Southern Key Economic Region. This overcomes the limitations on the influence of financial development on firm investment intensity in O’Toole and Newman (2017), Gupta and Mahakud (2019), generalizing the financial influence space in the leading financial hypothesis of Topcu and Çoban (2017), financial development affects firm’s financial resources and growth through credit availability by Arellano et al. (2012). Furthermore, the paper uses data on economic indicators of enterprises aggregated to the provincial level and GMM method to assess the effect of financial development on enterprise growth. This both ensures data consistency and limits the exaggeration of the financial sector for the firms in the research sample.

2. Literature review

According to Tingler (2015), corporate growth is a term widely used in academic research, but there is still no generally accepted definition. This is because corporate growth reflects a complex, heterogeneous process, many strategic issues, and involves very different perspectives (Brenner & Schimke, 2015). Penrose (1995) suggests that it can be defined in two different ways, including: (1) the increase of a particular quantity such as sales, production or exports; (2) a process of growing in scale or improving in quality. Meanwhile, Dosi et al. (2020) argue that corporate growth is a process by which firms not only pursue market opportunities but also organize activities to acquire and accumulate resources needed to exploit those opportunities. Thus, enterprise growth can be understood as an increase in scale such as revenue, added value or assets and labor.

Meanwhile, financial development can be defined as improvements in the financial sector (Pradhan et al., 2014) for efficient allocation of resources efficiently in the economy (Cherif & Dreger, 2016). Financial development is described as the combination of depth, accessibility, efficiency and stability in financial activities (Gupta & Mahakud, 2019) to achieve development for the entire financial sector. (Zaman et al., 2012). Therefore, King and Levine (1993) pointed out that the financial development of a country is important for business performance and economic growth. This is because the financial system has an effect on the real economy through increasing savings and investment rates or improving efficiency in capital accumulation (Topcu & Çoban, 2017). In which, the outstanding functions of the financial system are allocating resources, mobilizing savings, supporting risk management, controlling enterprise and contributing to promoting transactions of goods and services (Levine, 2005). Abu-Bader and Abu-Qarn (2008) found that financial development is important for long-term economic growth through the impact of financial sector services on capital accumulation and technology innovation. Simultaneously, financial development allows enterprises to maintain production and business (King & Levine, 1993), improve access to capital (Owen & Pereira, 2018; Rajan & Zingales, 1998), improve capital structure (Fafchamps & Schündeln, 2013) and accelerate growth (Nabamita & Daniel, 2021; O’Toole & Newman, 2017). Therefore, financial development allows firms to create favorable conditions to improve operational efficiency and increase profits (King & Levine, 1993; Levine, 2005), reduce asymmetric shocks and growth fluctuations through favorable and smooth private investment activities (Aghion et al., 2010; Chauvet & Jacolin, 2017). Thus, financial development will boost sales growth, productivity, investment rate and export intensity of enterprises (Harrison et al., 2014).

In addition, financial development creates competition among financial institutions in diversifying products, providing volume and credit pricing for businesses (Chauvet & Jacolin, 2017). Financial development promotes growth (King & Levine, 1993; Levine et al., 2000), improves financial constraints, and promotes investment for businesses (O’Toole & Newman, 2017). In particular, the establishment and expansion of financial institutions will compensate for the imperfections and biases of credit markets. Financial intermediaries reduce the cost of information collection and processing, thereby improving resource allocation (Levine, 2005; T.V. Tran et al., 2020). Without financial intermediaries or financial arrangements, businesses face many limitations in mobilizing credit and savings. Therefore, information and transaction costs, financial contracts can generate favorable conditions for transactions, hedging risks (T.V. Tran et al., 2020) leading to good resource allocation and business growth (Levine, 2005). Furthermore, the absence of financial intermediaries exposes investors to high fixed costs associated with asset valuation, business valuation, and economic conditions. This makes it impossible for capital to flow into profitable investments (Levine, 2005). Thus, the financial system provides functions that promote business and economic growth by increasing the amounts of financial resources to invest and by improving the efficiency of resource allocation (Levine, 2005; T.V. Tran et al., 2020). Salah et al. (2021) found that the presence of regime shifts in the cointegrating relationship and asymmetry between growth volatility and financial deepening in UAE. Moreover, they indicated a significant difference in the response of business cycle to negative or positive changes in the financial deepening, which are more pronounced in the short run.

3. Models and methodology

3.1. Model and data

Evans (1987a) proposes a method of determining firm growth as follows:

(1) $\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}\mathrm{h}=\mathrm{L}\mathrm{n}\left(\frac{{\mathrm{S}}_{\mathrm{t}}}{{\mathrm{S}}_{\mathrm{t}-1}}\right)=\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{t}}-\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{t}-1}$(1)

Simultaneously, the relationship between the variables that generate business growth is described by the Evans equation (Evans, 1987b) as:

(2) ${\mathrm{S}}_{\mathrm{i}\mathrm{t}}=\mathrm{G}\left({\mathrm{A}}_{\mathrm{i}\mathrm{t}},{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right){\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}{\mathrm{e}}_{\mathrm{i}\mathrm{t}}$(2)

In which, S_it is the variable to determine business growth and being identified as the size of the enterprise, A_it is the vector of factors that create business growth, e_it is the error, is assumed to remain unchanged. Equation (2)(2) ${\mathrm{S}}_{\mathrm{i}\mathrm{t}}=\mathrm{G}\left({\mathrm{A}}_{\mathrm{i}\mathrm{t}},{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right){\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}{\mathrm{e}}_{\mathrm{i}\mathrm{t}}$(2) can be rewritten as:

(3) $\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\mathrm{t}}-\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}=\mathrm{l}\mathrm{n}\mathrm{G}\left({\mathrm{A}}_{\mathrm{i}\mathrm{t}},\hspace{0.17em}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)+{\mathrm{u}}_{\mathrm{i}\mathrm{t}}$(3)

The error u_it is assumed to have zero mean, constant variance and be independent with A_it, S_i(t-1). At the same time, Evans (1987b) argues that lnG(A,S) is expanded as a quadratic polynomial, so (1) and (3) are rewritten as:

(4) $\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}{\mathrm{h}}_{\mathrm{i}\mathrm{t}}=\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\mathrm{t}}-\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}=\hspace{0.17em}{\mathrm{b}}_0+{\mathrm{b}}_1\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}+{\mathrm{b}}_2\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{b}}_3{\left(\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)}^2+{\mathrm{b}}_4{\left(\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}\right)}^2+{\mathrm{b}}_5\left(\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)\left(\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}\right)+{\mathrm{u}}_{\mathrm{i}\mathrm{t}}+$(4)

Coad (2009) and Vaz (2021) suggest that there are different measures of firm growth such as employment, total revenue, value added, total assets or total profit. However, many studies suggest that sales or total revenue is the most suitable indicator to measure business growth (Shepherd & Wiklund, 2009; Tingler, 2015). This is first because sales are applicable to almost all types of businesses. Second, every business depends on generating sales to survive in market. Moreover, sales is the main indicator of interest for managers, investors and entrepreneurs. Simultaneously, the fact of the increase in sales raising the question of increasing the number of employees and assets of a business to further expand market share and profits (Shepherd & Wiklund, 2009; Tingler, 2015). Therefore, the paper uses total net revenue to measure business growth and research model (A) according to equation (4)(4) $\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}{\mathrm{h}}_{\mathrm{i}\mathrm{t}}=\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\mathrm{t}}-\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}=\hspace{0.17em}{\mathrm{b}}_0+{\mathrm{b}}_1\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}+{\mathrm{b}}_2\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}+{\mathrm{b}}_3{\left(\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)}^2+{\mathrm{b}}_4{\left(\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}\right)}^2+{\mathrm{b}}_5\left(\mathrm{l}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)\left(\mathrm{l}\mathrm{n}{\mathrm{A}}_{\mathrm{i}\mathrm{t}}\right)+{\mathrm{u}}_{\mathrm{i}\mathrm{t}}+$(4) as follows:

$\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}{\mathrm{h}}_{\mathrm{i}\mathrm{t}}={\beta }_0+{\beta }_1\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}+{\beta }_2{\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)}^2+{\beta }_3\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\beta }_4{\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)}^2+{\beta }_5\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)+{\epsilon }_{\mathrm{i}\mathrm{t}}\left(\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}\mathrm{A}\right)$

Where variable S describes the size and is determined by the firm’s net sales, FID is financial development, ε_it is the error. In addition, there are many approaches to financial development in terms of financial depth, accessibility, efficiency and stability. However, this paper assumes that the size and liquidity of the market have a direct impact on the internal liquidity conditions to determine investments that in turn drive corporate growth. Therefore, the paper uses financial depth as a proxy for the FID financial development index (Gupta & Mahakud, 2019; O’Toole & Newman, 2017). From a macro perspective, a measure of the overall depth of the financial sector is determined by total credit to gross domestic product (Guariglia & Poncet, 2008) or M2 money supply to GDP. However, this measure overstates the financial sector for firms in several provinces in a region. In fact, financial development is often approximated by domestic credit to the private sector (Choi & Park, 2017), so many studies use domestic credit to the private sector as a proxy for financial development (Ashraf, 2018). This paper, thus, uses a measure of financial depth developed by O’Toole and Newman (2017) for the corporate sector by determining total credit to total firm output in each province. This measure is close to the one of corporate-level financial depth that is widely accepted in the world scientific community proposed by Rajan and Zingales (1998).

The paper proposes to use two factors of human capital (HUM) and institutional quality (INS) of the provinces to control and regulate the business growth process in the provincial economy. This is because growth is not considered to be the result of a single lucky event that allows a business to grow, growth mainly depends on the ability to identify factors to increase the growth of the business (Vaz, 2021). In which, institutions and factors related to the implementation of public policies can affect business operations and growth. Political stability accompanied by strong institutions represents low risk that can stimulate investment and create an impetus for corporate growth (Vaz, 2021). In contrast, weak institutional constraints, unstable political structures, and uncertainty about policies make firms less likely to invest in growth (Boubakri et al., 2015). The institutional quality variable is determined by the provincial competitiveness index (PCI) of each province over the years (T.B. Tran et al., 2009). From there, research model (B) develops from model (A) is formed:

$\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}{\mathrm{h}}_{\mathrm{i}\mathrm{t}}={\beta }_0+{\beta }_1\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}+{\beta }_2{\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)}^2+{\beta }_3\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\beta }_4{\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)}^2+{\beta }_5\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)+{\beta }_{6}IN{S}_{it}+{\mu }_{\mathrm{i}\mathrm{t}}\left(\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}\mathrm{B}\right)$

In addition, human capital is an intangible asset capable of carrying out innovative activities that create sustainable competitive advantage (Barney, 1991) and promote business growth (Gilbert et al., 2006; Kumar, 2016). So, accessing and exploiting human capital in the locality and region will add valuable and important resources for businesses in establishing and implementing growth strategies. In this study, the paper uses the number of lower secondary school students in each province as a proxy for the human capital of a province (He et al., 2017). Therefore, the research model (C) develops from the model (A) and (B) is set as follows:

$\mathrm{G}\mathrm{r}\mathrm{o}\mathrm{w}\mathrm{t}{\mathrm{h}}_{\mathrm{i}\mathrm{t}}={\beta }_0+{\beta }_1\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}+{\beta }_2{\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)}^2+{\beta }_3\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}+{\beta }_4{\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)}^2+{\beta }_5\left(\mathrm{L}\mathrm{n}{\mathrm{S}}_{\mathrm{i}\left(\mathrm{t}-1\right)}\right)\left(\mathrm{L}\mathrm{n}\mathrm{F}\mathrm{I}{\mathrm{D}}_{\mathrm{i}\mathrm{t}}\right)+{\beta }_{6}IN{S}_{it}+{\beta }_{7}HU{M}_{it}+{\vartheta }_{\mathrm{i}\mathrm{t}}\left(\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}\mathrm{C}\right)$

The variables of size (sales), human capital and financial development are collected and calculated from the information in the Efficiency of domestic enterprises in the period 2005–2014; Production and business results of Vietnamese enterprises in the period 2010–2014; The development of Vietnamese enterprises in the period 2006–2011; Situation of enterprises through the survey results in the years 2006–2008; Statistical Yearbook over the years in the 2005–2019 period; Vietnam business white paper in 2019 and 2020 issued by the Ministry of Planning and Investment. The institutional quality variable was obtained from the Provincial Competitiveness Report for the period 2005–2018 published by the Vietnam Chamber of Commerce and Industry (VCCI). These are economic indicators of enterprises that are aggregated to the provincial level. This makes the data will focus on differences within the country to complement the transnational economic environment. At the same time, it facilitates the exploration of how financial market developments affect firms across different provinces in an economy (O’Toole & Newman, 2017). All variables were taken logarithmically before being included in the analysis as suggested by Evans (1987a,b). The results of the descriptive statistical analysis are presented in Table 1.

Table 1. Descriptive statistics

Variables	Observations	Max	Mean	Min	Standard Deviation
Size (sales—S)	98	6.7323	5.3011	3.9246	0.6508
Financial Development (FID)	98	1.1364	0.5183	0.1047	0.2281
Institutional Quality (INS)	98	1.8876	1.7805	1.6540	0.0396
Human Capital (HUM)	98	5.9967	4.9789	4.0222	0.2811

Source: Author’s calculation

Table 1 shows that there is no big difference between the maximum and minimum values of the variables. This implies that the data is fairly even and concentrated. Simultaneously, the value of scale (sales) fluctuates quite small, conveying information about business growth that tends to be relatively stable. At the same time, the relatively small value and volatility of the financial development index (FID) reflects a relatively low level of financial growth. This has reflected about the size and financial market capacity of the SKEZ, which is still in the early stages of development.

3.2. Methodology

The explanatory variables in models (A) (B) (C) may not be completely exogenous due to the presence of lagged dependent variables. In other words, the endogeneity problem can arise from the correlation between the residuals and the lagged explanatory variables. Furthermore, Rajan and Zingales (1998) and Greenwood and Jovanovic (1990) showed that the relationships between financial development and economic growth may be endogenous. This means that financial development can make investments more efficient and better identify investment opportunities that should drive growth. Good growth will provide the means to improve costly financial structures and realize financial development (Greenwood & Jovanovic, 1990; Rajan & Zingales, 1998). These problems make the Ordinary Least Square estimate inconsistent and biased, so the paper uses the Generalized Method of Moments (GMM) of Arellano and Bond (1991) to estimate the empirical models. Moreover, the number of cross-sectional units of the small sample and the goal of determining the lagged coefficients is close to the best linear estimate to evaluate the role of size in firm growth, so the paper uses difference GMM technique in the analysis (Bond, 2002). In addition, the robustness of the differential GMM method is examined through Sargan and Arellano-Bond statistics. Meanwhile, Arellano-Bond test is used to detect first-order and second-order autocorrelation errors in differential equations. Sargan test aims to determine the validity of instrumental variables or exogenous instrumental variables in the GMM model.

4. Empirical results

Regression results of the empirical models are presented in Table 2. In which, the Arellano test rejects the hypothesis that there is no first order auto-correlation, but accepts the hypothesis that there is no second order autocorrelation. Meanwhile, the Sargan test accepts the hypothesis that the instrumental variable is valid or the exogenous instrument variable, so the estimated results can be trusted and identified as presented in Table 2.

Table 2. Regression results

Variables	Model A	Model B	Model C
LnSt-1	− 0.2224**	− 0.1915**	− 0.2202**
	(0.0898)	(0.0859)	(0.0891)
(LnSt-1)^2	0.0220**	0.0215**	0.0248**
	(0,0073)	(0.0081)	(0.0085)
LnFID	0.9407**	0.8932**	0.8328**
	(0.3082)	(0.3867)	(0.3878)
(LnFID)^2	0.0848	0.2468	0.2350
	(0.1559)	(0.1961)	(0.1947)
LnFID*LnSt-1	− 0.2214**	− 0.2584**	− 0.2484**
	(0.0757)	(0.0925)	(0.0923)
INQ		0.4022*	0.4338**
		(0.2164)	(0.2165)
HUM			− 0.1048
			(0.0909)
Tests
Wald	563.63***	68.45***	70.75***
AR(1)	0.017	0.000	0.000
AR(2)	0.149	0.161	0.144
Sargan	0.104	0.139	0.132
Observation	88	88	88

Note: *, ** and *** denote statistical significance at 10, 5 and 1 percent, respectively; () are standard errors

The coefficients of LnS and (LnS)² are significant at the 5% level, indicating that firm growth is not independent of size (Brenner & Schimke, 2015; Evans, 1987b). In which, the statistically significant quadratic scale function describes that the business growth will depend on the size at different stages of development in the enterprise’s development process. Luttmer (2011) suggests that this is a weak version of Gibrat’s law. In which, the existing enterprises cannot grow on average because there is a fixed quantity of goods and many new enterprises continuously enter the market. That is, the quantity of a good can increase over time, and the growth rate shows signs of being dependent on the previous period (Luttmer, 2011). However, business growth may decline in size at first because young, small businesses face different contexts of the business cycle. Simultaneously, firm growth may be independent of size for mature firms (Evans, 1987a). Thus, this result is consistent with the view of Dosi et al. (2020) that growth is a dynamic process that takes place over time, not an immediate response to market opportunities but mainly monitor and exploit market opportunities.

The coefficient of LnFID is positive and statistically significant at 5%, showing that financial development has made a positive contribution to business growth in the SKER. This result is consistent with previous studies by Rajan and Zingales (1998), O’Toole and Newman (2017) on how financial development will support business growth. This combined with the coefficient (LnFID)² is not statistically significant, which implies that firms with growth rates are more sensitive to financial market movements. In other words, the development of local financial markets can be a source of comparative advantage for firms to focus on production and generate growth (He et al., 2017). Particularly, financial development through activities to improve access to investment credit brings rapid development to businesses and the market (O’Toole & Newman, 2017). Many businesses in Vietnam in general and the SKER in particular face serious challenges in terms of accessing external credit and exploiting the utilities of the financial market. O’Toole and Newman (2017) attribute this to asymmetric information, lack of collateral, and dependence on capital markets in the direct geographical location of businesses. Therefore, the research results are similar to He et al. (2017), Lee et al. (2019), Silva and Carreira (2012), and O’Toole and Newman (2017) on financial development can provide give businesses the credit they need to invest and grow.

The negative and statistically significant cross-coefficient of size and financial development at the 5% level reinforces the above argument about the negative effect of size on growth during early childhood and infancy. In which, providing finance to fill the scale gap can increase sales but reduce business growth. This may be due to the difference in the size of the financial rather than inefficiencies in financial provision. That is, financial development changes investment behavior in the direction that investment in development will be more useful than investment seeking short-term profits. Therefore, the study results are similar to He et al. (2017) on the explanation for the poor specialization in emerging market countries and indicate the mechanisms for financial development to contribute to specializing industries (He et al., 2017).

Meanwhile, the results presented in Table 2 are not enough strong to conclude that human capital in the provinces in the SKER affects business growth in the area. Lafuente and Rabetino (2011) argues that human capital is a decisive factor for the growth of enterprises, but the intensity of implementation must be adjusted accordingly. This is due to the large difference in the importance of education and career skills of managers and employees for business growth (Demir et al., 2017). Thus, local human capital and skill levels of workers are an important predictor of growth (Lopez-Garcia & Puente, 2012) but possibly shortages of qualifications and capacity managers is a significant impediment to firm growth (Demir et al., 2017).

However, local institutional quality has a positive effect on firm growth in the SKEZ at the 1% and 5% significance levels. Thus, a good institutional environment encourages enterprises to step up business, participate in economic activities and compete in the market (Acemoglu & Johnson, 2005; He et al., 2017). La Porta et al. (2000) argued that good institutions will regulate financial systems well. Good and strong institutions can effectively protect investors, creditors and minority shareholders and improve access to external financial markets, thereby increasing capital allocation efficiency for corporate growth (He et al., 2017; La Porta et al., 1997).

5. Conclusion

This paper examines the impact of financial development on business growth in the SKER. The empirical results indicated that business growth will depend on size at different stages in the development process. In particular, the paper finds that financial development plays an important role in business growth in the SKER. Therefore, financial development that meets the goal of changing investment behavior will bring many benefits to businesses. If financial development increases, the differential cost of capital between internal and external finance will decrease, thereby giving rise to conditions for firm growth (O’Toole & Newman, 2017). Additionally, this paper also finds that institutional quality plays an important role in promoting business growth. Good institutions not only create a good economic environment for business growth, but also protect potential financiers, expand the scope of capital markets, promote financial development, and promote economic development (La Porta et al., 1997). Stemming from the findings, this paper recommends the SKEZ in particular and the whole country in general as follows:

First, corporate growth is important to the economy and industries. Therefore, businesses should focus on growth, considering growth as important as sales and productivity throughout their operations. If the scale has not reached a reasonable level, increasing the scale can gradually reduce the growth rate. Therefore, businesses should structure their resources to effectively identify and exploit the next growth opportunities.

Second, corporate managers and policymakers should focus on financial development to promote corporate growth. It is necessary to strengthen the depth of the financial system to allow businesses to get favorable conditions to receive external financial sources, to help businesses access capital sources, loans of reasonable quality at reasonable costs. Furthermore, the credits obtained through the loans must be used to improve investment flows, develop equipment and technology to bring real growth benefits to businesses.

Third, focus should be made on improving institutions and creating a stable economic environment to help businesses grow. Particularly, it is necessary to promote a well-developed financial system that can ease credit constraints for businesses and allow them to exploit growth opportunities.

Fourth, the relevant agencies of the 7 provinces in the region need to come together to create a standing committee to develop an effective coordination mechanism. Moreover, this is also the unit that urges and monitors the progress of the implementation of the plan, and promptly fixes errors when necessary to make the coordination among the relevant agencies in the region become more and more effectively.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors received no direct funding for this research.