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Abstract

Transition economies, marked by institutional reforms, often exhibit lower rates of entrepreneurial activity in comparison to both developed and developing economies. However, some transition economies have experienced sustained high economic growth, as observed in countries like China and Vietnam. In contrast, others have faced more volatile growth patterns, as seen in the former Soviet Union. A fundamental question arises: to what extent does institutional reform translate into entrepreneurial dynamics, and does the development of institutions and entrepreneurship contribute to long-term economic growth in transition economies? In this paper, we utilize the GMM 3SLS estimator for panel data and simultaneous equations to investigate the relationship between institutions and entrepreneurship and the impact of entrepreneurship on economic growth in 63 provinces of Vietnam from 2012 to 2019. We aim to provide a rigorous and comprehensive analysis of the factors contributing to successful entrepreneurship and economic growth in Vietnam. The results show that various institutional indicators such as business support services, labor quality, transparency, informal charge, time costs, and proactivity have significantly positive impacts on the entrepreneurial dynamic. Remarkably, these institutional factors also indirectly affect economic growth through entrepreneurship. The findings imply that policymakers must consider and prioritize these indicators to foster a conducive environment for entrepreneurship and long-term economic growth.

Keywords

institutions entrepreneurship economic growth transition economies Vietnam

Introduction

Vietnam’s economic transition from a centrally planned economy to a market economy since 1986 has been largely characterized by unleashing entrepreneurship and private enterprise development (Q. A. Nguyen et al., 2015). Since then, Vietnam has been remarkably successful in achieving rapid economic growth. Although scholars have identified several key determinants of long-term economic growth, the specific impacts of institutional reform and entrepreneurship development on growth in developing and transition economies remain unclear (Urbano et al., 2020). The relationships among institutions, entrepreneurship, and economic growth vary based on the economic context. The environment that supports entrepreneurship development in transitional countries is significantly different from that in developed economies (McMillan & Woodruff, 2002; Smallbone & Welter, 2001). In transitional economies, key factors such as the government’s commitment to market reforms, the removal of institutional barriers, and local institutional reforms are essential for fostering entrepreneurship development (He et al., 2019; Urbano et al., 2020). While the existing entrepreneurship literature focusing on developed economies may not emphasize these factors, they are crucial to examine in the context of transition economies. Moreover, previous studies have shown that while entrepreneurship tends to promote economic growth in developed countries, it may actually hinder growth in low-income countries (Sautet, 2013; Van Stel et al., 2005). Notably, the impact of entrepreneurship on economic growth can vary depending on the stages of entrepreneurial activities (Nikolaev et al., 2018).

Although institutions play a critical role in shaping the entrepreneurial environment to promote economic growth (Acemoglu & Robinson, 2012; Bruton et al., 2010), several previous studies have primarily focused on the impact of institutions on entrepreneurship without considering how entrepreneurship itself affects economic growth (Bosma et al., 2018; Urbano et al., 2019). In research conducted by Nissan et al. (2011) and Méndez-Picazo et al. (2012) in the 2010s, model specifications were employed to separately analyze the relationships between institutions and entrepreneurship and entrepreneurship and economic growth. While this approach enhances our understanding of the interactions between institutions and entrepreneurship, it fails to account for the simultaneous effects of both on economic growth, particularly in the context of transition economies. Therefore, this study aims to address this gap in the existing literature.

Signifying the simultaneous effects will facilitate the formation of effective policy proposals for the transition process. This study addresses the need for more regional research on this interconnection in transitional economies. The findings could help formulate policy recommendations to foster entrepreneurship and economic growth in Vietnam and other transitional countries with similar socio-economic and institutional contexts.

This study focuses on Vietnam, which presents a counterintuitive case. The country is a transitional economy that has undergone institutional reforms but exhibits a lower rate of entrepreneurial activities than many developed and developing nations (Estrin & Mickiewicz, 2011). Despite this, Vietnam has experienced significant economic and social changes in recent years. Since 1986, Vietnam has been moving from a centrally planned economy to a market-oriented approach, progressing positively after the introduction of “Doi Moi,” which means reform or renovation (Q. A. Nguyen et al., 2015). The Company Law and Private Enterprise Law, enacted in 1990, marked the first steps in officially recognizing the private sector as an essential component of the economy. The Enterprise Law in 2000 created more favorable conditions for private businesses to participate in the economy, resulting in a remarkable increase in the number of new businesses over time. After the introduction of the Company Law, only 14,500 enterprises were established within 9 years. However, by the end of 2017, over 1 million private enterprises had been registered. The number of newly registered enterprises has significantly increased, reaching a peak of nearly 140,000 in 2019.

The private sector has been a key contributor to Vietnam’s economic performance in recent years. The average annual growth rate of GDP is 6.6% in the period 1987 to 2019, which is higher compared to the annual growth rate of some other transition countries. In 2016, the private sector accounted for 38.6% of GDP, and it was officially recognized as the driving force of the national economy by the National Congress XII of the Communist Party in 2017. Since then, the government has focused much attention on enhancing entrepreneurial activities. Many factors of the business environment have been significantly improved to facilitate the development of the private sector such as reducing market entry costs, increasing business support activities, and improving labor standards. However, compared to countries of the same level of economic development, the start-up ecosystem in Vietnam still has many signs of weakness with 6 out of 12 indicators of business conditions ranked below average Bosma & Kelley (2019). This paper aims to address the research question: “Is there a simultaneous effect between institutional factors, entrepreneurship, and its impact on long-term economic growth in Vietnam?.” In this study, we explore a range of institutional factors that significantly influence the dynamics of entrepreneurship and economic growth. Specifically, we focus on elements such as the availability and effectiveness of business support services, the quality of the labor force, the level of transparency within institutions, the prevalence of informal charges, the time costs associated with business operations, and the overall proactivity of leadership. By examining how these factors interact simultaneously, we aim to reveal their collective impact on fostering a conducive environment for entrepreneurship and enhancing economic growth.

The organization of the paper is as follows. Section 1 presents the motivations for the study. Section 2 provides a recent development in the entrepreneurship literature and formalizes the hypotheses. In section 3, we describe the model specifications and data used in the analysis. Section 4 presents the regression results, and Section 5 concludes the study.

Literature Review

Entrepreneurial Dynamic: Insights From New Entry and Exit Firms

Schumpeter (1934) defined entrepreneurship as the creative destruction process by: (i) introducing a new good or (ii) a new production method, (iii) opening a new market; (iv) exploiting a new source of raw materials; and (v) creating a new organization. From the viewpoint of linking entrepreneurship to economic growth, Wennekers and Thurik (1999) regard entrepreneurship as newness or new entry. “Newness” is equated with the concept of innovation in business, while “new entry” is involved in entering the market. With a broader view, Dess and Lumpkin (1996, p.136) asserted that “new entry can be accomplished by entering new or established markets with new or existing goods or services. New entry is the act of launching a new venture, either by a start-up firm, through existing firms, or via internal corporate venturing.” The entry of new firms has been used as a proxy for entrepreneurship in numerous studies, including Mueller (2007), Audretsch and Keilbach (2005), Aidis et al. (2009), Estrin and Mickiewicz (2011), Bruno et al. (2013).

After successfully entering the market, a new firm innovates by producing more efficiently or producing better goods and services. These innovative activities help to increase competition among existing firms. Thus, firm entry is not simply new production, but rather it is an element that threatens the exit of unproductive firms (Dejardin, 2011). Firm entry rate and net entry rate, which is the flow of entry and exit firms, are important features of the entrepreneurial process and therefore are considered as a good indicator of the level of entrepreneurship in a given country. Holtz-Eakin and Kao (2003) used the rate of births and rate of deaths of firms as proxied for entrepreneurship to determine whether variations in entrepreneurship affect economic growth. Dejardin (2011) measured entrepreneurship by three indicators such as stock of firm, net entry in terms of firm births and deaths, and net entry rate. Similarly, Zhou (2011) measured entrepreneurship by using net entry rate that take into account both firm formations and firm failures to examine the effects of deregulation on entrepreneurship.

The Impact of Institutions on Entrepreneurship

Business environment is a set of conditions such as social, legal, economic, political or institutional that impact on the operation of business. There is a close interaction between a business and its environment. A good business environment helps reduce business start-up costs, corrupt practices, and time costs that firms spend on non-productive activities. An efficient and proactive business environment also provide favorable services for enterprises. A transparent environment reduces the risks of the entrepreneurial process and motivates entrepreneurs to start and invest more in their businesses (Slesman et al., 2020). In this study, we use institutional factors to test whether the business environment influences firms’ entry and exit.

Institutions shape the norms, rules, and practices that guide behavior within a particular social context. In the context of entrepreneurship, institutions can either facilitate or hinder entrepreneurial activities by providing supportive or constraining environments. Formal institutions such as regulations, contracts, or procedures help to reduce transaction costs, whereas informal institutions play a key role in reducing the uncertainty of an individual’s decision-making process (North, 1990). The rate of entrepreneurial activity depends not only on the capability of individuals but also on the institutional factors that create favorable conditions or cause barriers to entrepreneurship (Fogel et al., 2009). Institutional barriers include property rights violations, administrative barriers to entering the market, lack of law enforcement, informal payments, and lack of governmental support (Baumol, 1990).

Property rights have the strongest impact on entrepreneurship according to McMillan and Woodruff (2002). It does not only help enterprises maintain their current condition but also contributes to promoting innovation and discovering and creating new resources (Harper, 2003). In transition economies, a lack of property rights or weak enforcement could limit investment, and discourage start-up firms from reinvesting their profits (Fogel et al., 2009; Johnson et al., 1999). If the ownership of the business is secured, entrepreneurial activity could be promoted. Conversely, a lack of property rights and excessive government regulations hinder entrepreneurship development (Kshetri & Dholakia, 2011).

The regulatory environment for startups may influence entrepreneurship, particularly business creation. The number of startup procedures that a firm must overcome before registering a new business is used as a measure of startup barriers. An increase in startup regulations leads to a decrease in new business creation (Djankov et al., 2000; Klapper et al., 2006). The higher the number of procedures required to process paperwork for starting a new business also lower the new business creation (Chambers & Munemo, 2019).

Property rights protection is positively related to new business start-ups (Chowdhury et al., 2015), while the quality of regulations is negatively correlated with new business entry (Braunerhjelm et al., 2015). Besides the security of property rights and business regulations, other institutional dimensions such as better legal structure, easy access to finance and credit, good infrastructure, and an educated population tend to increase entrepreneurship (Nyström, 2008). Furthermore, an efficient court system and rule of law or the belief in the court’s ability to enforce contracts affect the development of the private sector (Djankov et al., 2000; McMillan & Woodruff, 2002), especially in transition economies where the legal and institutional system underlying a market economy is still nascent.

In corrupt countries, officials are often bribed through informal payments to issue permits, facilitate entrepreneurial activities, and especially enable firms to enter the market (Dreher & Gassebner, 2013). To promote the growth of entrepreneurship, it is essential to establish control of corruption. T. T. Nguyen and van Dijk (2012) found corruption hampers the growth of the private sector across 24 provinces in Vietnam due to the low quality of provincial public governance, such as the costs of new business entry, land access, and private sector development policies. Furthermore, evidence from the study of Ghura et al. (2020) showed the moderating effect of corruption on the relationship between formal institutions and entrepreneurial activities in 14 post-communist countries.

In entrepreneurship, institutions play an important role for both start-up businesses and existing businesses because it reduces long-term uncertainty and transaction costs (Williamson, 1985). Greater fairness is shown to increase the rate of entry and decrease the rate of exit (Desai et al., 2003). In transitioning from central planning to a market economy, state-owned enterprises (SOEs) or large-size firms would receive more privileges in accessing information and finance than small-and-medium enterprises (SMEs; Hakkala & Kokko, 2007). Policy biases conduce to a skewed playing field for the private sector and create an unfair business environment, therefore preventing SMEs from entering the market and scaling businesses. A good institutional environment will create favorable conditions for individuals to confidently enter the market and expand their business activities, while a weak institution might foster unproductive or destructive entrepreneurship.

In short, institutions can influence entrepreneurial activity in transition economies through two main mechanisms. First, weak institutions can impede the establishment of new firms, leading to a lower number of market entrants. Second, institutions play a role in either supporting or undermining firm performance, which can be evaluated based on factors such as survival duration, growth, and profitability. (Estrin et al., 2005).

Taking all together based on previous studies, we propose the following hypothesis:

H1: The better the quality of institutions, the higher the net entry rate of private enterprises in a transition economy.

The Relationship Between Entrepreneurship and Economic Growth

Previous studies have demonstrated the positive effect of entrepreneurship on national or regional economic development and growth (Acs et al., 2008; Audretsch & Keilbach, 2005; Bosma et al., 2018; Mueller, 2007; Urbano & Aparicio, 2016; Valliere & Peterson, 2009). The formation of new businesses might contribute to economic growth and development by generating knowledge spillover (Audretsch & Thurik, 2001), transferring resources from low to high-productive activities, and increasing competition in the market (Klapper et al., 2010). In addition, it may be the source of generation, dissemination, and application of innovative processes and products enhancing efficiency and productivity over time (Audretsch & Fritsch, 1994; Autio & Fu, 2015). Moreover, one-third of the differences in national economic growth rate can be attributed to differences in entrepreneurial activity according to Reynolds et al. (2001).

Additionally, the effects of entrepreneurship on the economy differ between developed and developing countries. In developed countries, several studies found a positive link between entrepreneurship and growth. Zacharakis et al. (2000) revealed that one of the differences in GDP growth between 16 developed countries is explained by entrepreneurial activity. Similarly, Ács and Varga (2005) claimed that entrepreneurship generates a positive impact on technological change in European countries by stimulating knowledge spillover. In contrast, the research results from the study of Doran et al. (2018) indicated that entrepreneurial activity has a negative effect on middle/low-income economies. In a similar context, Kim et al. (2022) found no evidence of a positive relationship between overall entrepreneurship and economic growth, primarily due to the diverse nature of entrepreneurial activities between countries. Valliere and Peterson (2009) confirmed that entrepreneurship has a non-significant relationship with the GDP growth rate, based on a sample of 20 developing countries. Research by Abdinnour and Adeniji (2023) showed that there has no significant and positive effect of entrepreneurial activities on growth immediately, but overtime, has noticeable with sustained effort. Similarly, the study of Munyo and Veiga (2024) which conducted on the group of South American countries, found the positive and significant relationship between entrepreneurial activity and economic growth. Sautet (2013) proved that low-income countries often experience productive entrepreneurship but with little or no corresponding development. This suggests that the impact of entrepreneurship on economic growth differs depending on the development stage of an economy. However, that effect mainly happened in developing countries and not much in transition economies (Van Stel et al., 2005). If it occurs in transition economies, Ivanović-Djukić et al. (2018) observed that the role of entrepreneurship in economic growth is relatively smaller compared to other developed and developing economies in Europe.

In transition economies, entrepreneurship is considered an important element that encourages economic development by creating market competitiveness and limiting the market power of public enterprises (Berkowitz & Dejong, 2001). McMillan and Woodruff (2002) found a strong and enduring relationship between entrepreneurial activity and growth in Russia’s post–Soviet transition. Li et al. (2012) emphasized the significant positive effect of entrepreneurship in the transitional economy of China. Similarly, research by Tahir and Burki (2023) on transitioning BRICS economies indicated that entrepreneurship has a positive and significant effect on economic growth. In Vietnam, M.-L. Tran and Lo (2024) also found the positive relationship between entrepreneurship and regional economic performance.

Taking together, we propose the following hypothesis:

H2: A higher level of entrepreneurial activity generates a positive impact on economic growth in a transition economy.

The Nexus Between Institutions, Entrepreneurship, and Economic Growth

Several recent studies have utilized the Global Entrepreneurship Monitor (GEM) dataset to explore the relationship between institutions, entrepreneurship, and economic growth, which varies depending on a country’s level of development. Khyareh and Amini (2021) analyzed GEM data from 64 countries between 2010 and 2018 and found that governance quality positively impacts growth, depending on the country’s development stage. Similarly, Galindo-Martin et al. (2020) divided 31 countries in the GEM dataset into two groups, based on different levels of growth and development, to demonstrate that effective institutional functioning enhances both economic growth and entrepreneurship. In contrast, Boudreaux (2019) also used GEM data for a panel of 83 countries from 2002 to 2014 and discovered that entrepreneurship does not promote economic growth in developing countries.

The different impacts of entrepreneurship on economic growth can be possibly explained by the institutional context. Institutions are considered precedents of entrepreneurship by shaping entrepreneurial behavior and motivating individuals to set up new businesses based on their innovative ideas. At the same time, entrepreneurship in turn contributes to economic growth and development. According to Acemoglu and Robinson (2012) and Baumol (1990), institutional quality indirectly affects economic growth. Institutions serve as a moderating variable on more proximate causes of growth such as entrepreneurship. Sharing this view, Bjørnskov and Foss (2013; 2016) stressed that institutions may moderate and mediate the effects of entrepreneurship on economic performance. Ferreira et al. (2023) implied the important role of entrepreneurial activities to positively mediate the relationship between formal institutions and economic performance.

There are empirical studies that investigated the indirect effect of the institutional environment on economic growth through entrepreneurial activity in developed European countries (Bosma et al., 2018) and developing countries (Urbano et al., 2020). In transition economies, the unstable legal and political system may hinder entrepreneurship and therefore produce less effect on economic growth than in developed economies. A better institution could promote entrepreneurial activity, thus boosting economic growth. Following the idea of considering entrepreneurship as a conduit between institutional factors and economic performance (Urbano et al., 2019), we propose a hypothesis:

H3: Better quality of institutions positively influences entrepreneurial activity and thereby boosts economic growth in a transition economy.

Data and Methodology

In this section, we examine the relationship between institutions, entrepreneurship, and economic growth in a transition economy using simultaneous equations that include an entrepreneurship equation and a growth equation.

Following the empirical studies of Aidis et al. (2009), Bruno et al. (2013), and Autio and Fu (2015), the entrepreneurship equation incorporates key explanatory variables, namely the institutional environment, GDP growth rate, and unemployment. The general equation is as follows:

\ln EN T_{it} = β_{0} + β_{1} IN S_{it} + β_{2} X_{it} + ε_{it},

(1)

where ENT_it denotes entrepreneurship; INS_it includes a set of institutional variables, X_it denotes the vector of control variables, including the growth rate of gross regional domestic product, gGDP_it, and the unemployment rate, ln(UEMP)_it; i represents province or city, and t represents year. The data for control variables are sourced from the Statistical Yearbook of Vietnam (2019). Entrepreneurship, ENT_it, is proxied by net firm entry, which is a measure of newly registered firms minus dissolved firms in a given province for a given year. We obtain data on net firm entry from the National Business Registration Portal (2019). New firm entry and dissolved firm data have been registered with government authorities in 63 provinces/cities in Vietnam during the period 2012 to 2019.

The data on institutional variables, INS_it, is taken from the Provincial Competitiveness Index (PCI), which is the outcome of a long-standing collaboration between the Vietnam Chamber of Commerce and Industry (VCCI) and the U.S. Agency for International Development (USAID). Since 2006, VCCI and USAID have published the annual PCI report, which is based on a comprehensive survey of private firms operating and investing in 63 provinces and cities. This report assesses the ease of doing business and the effectiveness of administrative reforms implemented by local governments. The PCI includes an aggregate index scored out of a maximum of 100 points, along with 10 sub-indices, each rated on a scale of 1 to 10. Overall, all provinces have improved their aggregate index, rising from 52.50 points in 2006 to 65.18 points in 2019, as they each enacted action plans aimed at enhancing their PCI performance. The PCI has been used in a large number of studies examining institutions in Vietnam, including T. B. Tran et al. (2009), Malesky and Taussig (2009), Su et al. (2019), B. Nguyen (2021), M.-L. Tran and Lo (2024). The information about the firm’s entry and exit is published at the end of the year, while the PCI survey is conducted in the early period of each calendar year. Therefore, in this paper, we utilize 1-year-lagged PCI data and then merge it with net firm entry and GSO data.

The PCI consists of 10 sub-indexes on a scale of 1 to 10, where a higher score indicates better institutional performance. These sub-indexes include the following variables: Entry Costs (PCI1), Land Access and Tenure Security (PCI2), Transparency (PCI3), Time Costs of Regulatory Compliance (PCI4), Informal charges (PCI5), Policy Bias (PCI6), Proactivity (PCI7), Business Support Services (PCI8), Labor Policy (PCI9), and Law and Order (PCI10).

A province that demonstrates strong performance on the PCI exhibits the following characteristics: (1) low entry cost for business start-ups; (2) easy access to land and security of tenure in case the land is confiscated; (3) transparent access to business environment and business information; (4) minimal informal charges; (5) limited time that firms waste on bureaucratic compliance after registration; (6) minimal crowding out effects to private firms from policy bias; (7) proactive and creative provincial leadership in solving problems; (8) developed and high-quality business support services; (9) effective labor training policies; and (10) fair procedure for deputing resolution (Malesky et al., 2018). Since PCI sub-indices are closely related, we enter each institutional variable into the model separately to address the multicollinearity issue (Aidis et al., 2009; Desai et al., 2003). In addition, we use the composite PCI index (PCI) as an aggregate institutional variable, which is the unweighted mean of 10 sub-indices with a maximum score of 100 points.

To estimate the effect of entrepreneurship on economic growth at the provincial level, we based on the endogenous growth theory (Romer, 1990), which treats innovation and technological change endogenously, arising directly from local investment in the creation of new knowledge and human capital. That knowledge is assumed to be automatically transformed into commercial opportunities through entrepreneurial activity. It is entrepreneurship that plays an important role in transferring knowledge to society (Audretsch & Keilbach, 2004; Noseleit, 2013) and has a positive effect on national or regional economic development and growth (Audretsch & Keilbach, 2005; Méndez-Picazo et al., 2012; Urbano & Aparicio, 2016). The economic growth equation is expressed as:

\begin{matrix} gGD P_{it} = & α_{0} + α_{1} lnEN T_{i, t} + α_{2} lnIN V_{it} + α_{3} lnLabo r_{it} \\ + α_{4} lnTEC H_{it} + ε_{it}, \end{matrix}

(2)

in which, $gGD P_{it}$ is defined as the growth rate of gross regional domestic product in constant price 2010. INV_it is the ratio of investment to GDP. TECH_it is the expenditure on science and technology, Labor_it denotes the percentage of trained employees in each province. These variables are in natural logarithms.

When investigating the interconnections among institutions, entrepreneurship, and economic growth, potential endogeneity problems may arise such as reverse causality, omitted variable bias, and unobserved heterogeneity. While institutions may influence entrepreneurship and economic growth, entrepreneurial activities and economic growth can also shape institutional development. Within the provincial data model, the potential for endogeneity arises from unobserved factors that can simultaneously impact both independent variables, such as GDP growth or institutional variables, and the dependent variable and dependent variable are reversed.

We utilized aggregate data from 63 provinces and cities in Vietnam to examine the relationship between institutions, entrepreneurial dynamics, and long-term economic growth at the regional level. Using data from a single country helps avoid inconsistencies in variable definitions that can arise when comparing different countries due to varying statistical methods. Between 2012 and 2019, the number of new businesses in Vietnam increased at an impressive rate, peaking at nearly 140,000 newly registered enterprises in 2019. During this time, the private sector became a key contributor to Vietnam’s economic performance, and the government focused on enhancing entrepreneurial activities. Various aspects of the business environment significantly improved to support the development of the private sector, including reduced market entry costs, increased business support activities, and enhanced labor standards. Thus, we aim to investigate whether institutions influence entrepreneurship and its subsequent impact on economic growth in Vietnam during this period.

To address the endogeneity and estimate the two equations simultaneously, we utilize both the traditional 3SLS and GMM 3SLS estimators. However, post-estimation analysis of the 3SLS reveals the presence of heteroscedasticity and autocorrelation, indicating a poor fit of the model. To overcome these challenges, we employ the GMM 3SLS estimator, which accommodates both heteroscedasticity and autocorrelation issues while generating consistent estimates under orthogonality (Wooldridge, 2010).

Results and Discussions

Tables 1 and 2 report the descriptive statistics and correlation matrix of all variables used in this study. Table 2 reveals significant correlations between net firm entry and various institution variables (PCI), as well as the unemployment rate and GDP growth rate. Furthermore, economic growth is significantly correlated with the share of investment in GDP and the expenditure on science and technology.

Table 1.

Descriptive Statistics.

Variables	Measurement unit	Obs	Mean	Std.Dev	Min	Max	Source^*
Net firm entry (ENT)	Number of firms	504	1,240.30	3,876.97	−1784	33,195	NBRP 2012–2019
Non state firms per 1,000 inhabitants (new ENT)	Number of firms	501	5.44	5.96	1.12	44.97	GSO 2012–2019
Composite PCI (PCI)	Scale, 0–100	504	61.02	4.60	46.95	74.16	VCCI 2013–2020
Entry cost (PCI1)	Scale, 0–10	504	8.84	0.46	6.56	9.77
Land access (PCI2)	Scale, 0–10	504	6.15	0.79	4.47	8.73
Transparency (PCI3)	Scale, 0–10	504	5.70	0.56	4.05	7.21
Time cost (PCI4)	Scale, 0–10	504	6.16	1.02	2.64	8.82
Informal charge (PCI5)	Scale, 0–10	504	5.70	0.90	3.17	8.40
Policy bias (PCI6)	Scale, 0–10	504	5.79	0.83	3.52	8.45
Proactivity (PCI7)	Scale, 0–10	504	5.86	1.25	2.46	9.26
Business support services (PCI8)	Scale, 0–10	504	5.94	0.80	3.94	7.95
Labor quality (PCI9)	Scale, 0–10	504	5.24	0.80	3.36	7.34
Legal institutions (PCI10)	Scale, 0–10	504	5.59	0.74	3.42	7.82
Unemployment (UEMP)	%	501	2.00	1.04	0.14	4.92	GSO 2012–2019
GDP growth rate (gGDP)	%	504	7.90	3.85	−16.86	33.21
Investment share in GDP (INV)	%	500	47.25	19.71	11.58	198.01
Trained employee (Labor)	%	504	17.52	7.21	5.10	48.10
Government expenditure on science (TECH)	Billion VND	494	40.69	79.17	0.00	1,043

National Business Registration Portal (NBRP) https://dangkykinhdoanh.gov.vn; PCI Vietnam Chamber of Commerce and Industry (VCCI) https://pcivietnam.vn; General Statistics Office (GSO) https://www.gso.gov.vn/.

Table 2.

Correlation Matrix.

No.	Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17
1	Ln ENT	1
2	PCI	0.24*	1
3	PCI1	−0.07*	0.14*	1
4	PCI2	−0.24*	0.01	−0.19	1
5	PCI3	0.32*	0.69*	0.06	−0.12*	1
6	PCI4	0.31*	0.64*	0.01	0.13*	0.33*	1
7	PCI5	0.07	0.80*	−0.03	0.21*	0.51*	0.48*	1
8	PCI6	−0.01	0.59*	−0.10*	0.15*	0.40*	0.32*	0.61*	1
9	PCI7	0.11*	0.75*	0.22*	−0.22*	0.51*	0.33*	0.50*	0.24*	1
10	PCI8	0.45*	0.39*	0.04	−0.51*	0.28*	0.13*	0.12*	0.02	0.25*	1
11	PCI9	0.37*	0.66*	0.15*	−0.50*	0.52*	0.27*	0.36*	0.20*	0.57*	0.69*	1
12	PCI10	−0.02	0.62*	0.01	0.09*	0.36*	0.27*	0.46*	0.31*	0.43*	0.09*	0.30*	1
13	Ln UEMP	0.45*	0.25*	0.05	0.04	0.22*	0.28*	0.26*	−0.04	0.14*	0.14*	0.23*	0.14*	1
14	gGDP	0.13*	−0.02	0.06	−0.07	−0.01	−0.06	−0.04	−0.01	0.03	−0.01	−0.01	−0.01	0.05	1
15	Ln INV	−0.04	−0.17*	0.07	−0.08*	−0.20*	−0.14*	−0.13*	−0.08	−0.09*	−0.02	−0.03	−0.19*	−0.07	0.30*	1
16	Ln labor	0.57*	−0.01	−0.01	−0.43*	0.14*	−0.04	−0.14*	−0.05	0.01	0.32*	0.39*	−0.16*	0.23*	0.21	0.21*	1
17	Ln TECH	0.73*	0.20*	−0.06	−0.28*	0.30*	0.25*	0.06	0.03	0.12*	0.34*	0.31*	0.02	0.32*	0.12*	−0.04	0.61*	1

p < .05.

The GMM 3SLS results in relatively larger coefficients than the traditional 3SLS. Table 3 shows the GMM 3SLS regression results. The entrepreneurship equation shows that the composite PCI variable has a positive and statistically significant effect on entrepreneurial activity. That is, a one-point increase in the composite PCI would result in a 5.6% increase in net firm entry. Taking the mean net firm entry of a province is 1,240, this estimated coefficient translates into roughly 70 new firms for one-point improvement in the composite PCI, which ranges from 1 to 100. Is this effect very high? A closer look at Table 1 reveals that this result is reasonable. Given the standard deviation of 4.6 and mean of 61.0, 95% of the composite PCI varies in a narrow range between 51.8 and 70, which approximates a scale of 20. Therefore, a one-point change, or 5% of the adjusted scale, in institutional quality translates into a 5.6% increase in the net number of firms entering the market. Our findings are consistent with the conclusions drawn in previous studies, particularly those conducted by Fogel et al. (2009), which examine the vital role that institutions play in determining entrepreneurial activities. Our study also supports to the research results by M.-L. Tran and Lo (2024) which identified a positive relationship between local institutional quality and the rate of new firm entry throughout Vietnam. Additionally, we reference a range of literature that supports our results, reinforcing the idea that the effectiveness and structure of institutions significantly influence entrepreneurial outcomes.

Table 3.

GMM 3SLS Regression on Entrepreneurship and Growth (ENT = The Net Firm Entry).

GMM	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9	Model 10	Model 11
Entrepreneurship equation
Composite PCI	0.056*** (0.014)
Entry cost (PCI1)		−0.030 (0.178)
Land access (PCI2)			−0.252** (0.128)
Transparency (PCI3)				0.292*** (0.114)
Time cost (PCI4)					0.192*** (0.072)
Informal charge (PCI5)						0.267*** (0.078)
Policy bias (PCI6)							0.101 (0.065)
Proactivity (PCI7)								0.183*** (0.054)
Business support services (PCI8)									0.353*** (0.070)
Labor quality (PCI9)										0.320*** (0.068)
Legal institutions (PCI10)											−0.039 (0.071)
ln(UEMP)	0.488*** (0.117)	0.583*** (0.129)	0.599*** (0.125)	0.518*** (0.124)	0.498*** (0.121)	0.511*** (0.120)	0.607*** (0.128)	0.521*** (0.120)	0.539*** (0.116)	0.470*** (0.114)	0.630*** (0.126)
gGDP	0.073** (0.035)	0.067* (0.034)	0.058* (0.034)	0.068** (0.034)	0.077** (0.035)	0.074** (0.035)	0.062* (0.033)	0.065* (0.034)	0.096*** (0.035)	0.081** (0.037)	0.072**(0.035)
Constant	1.683* (0.907)	5.336*** (1.670)	6.639*** (0.875)	3.429*** (0.665)	3.859*** (0.565)	3.549*** (0.517)	4.506*** (0.448)	4.012*** (0.435)	2.755*** (0.538)	3.334*** (0.506)	5.238*** (0.397)
Growth equation
ln(ENT)	0.623*** (0.199)	0.612*** (0.190)	0.608*** (0.184)	0.613*** (0.196)	0.690*** (0.193)	0.618*** (0.199)	0.562*** (0.192)	0.623*** (0.198)	0.558*** (0.192)	0.580*** (0.193)	0.639*** (0.190)
ln(INV)	3.095*** (0.938)	3.130*** (0.877)	3.175*** (0.900)	3.063*** (0.934)	2.759*** (0.948)	3.039*** (0.931)	3.316*** (0.892)	2.988*** (0.922)	2.244*** (0.879)	3.255*** (0.917)	2.701*** (0.958)
ln(labor)	0.933 (0.695)	1.940 (0.693)	0.925 (0.688)	0.908 (0.699)	0.881 (0.712)	0.977 (0.688)	1.200 (0.640)	0.848 (0.687)	0.922 (0.682)	0.949 (0.666)	1.004 (0.718)
ln(Tech)	−0.281 (0.331)	−0.280 (0.322)	−0.284 (0.344)	−0.284 (0.340)	−0.356 (0.327)	−0.306 (0.309)	−0.360 (0.347)	−0.272 (0.337)	−0.159 (0.313)	−0.142 (0.328)	−0.441 (0.326)
Constant	−9.188** (3.633)	−9.276*** (3.208)	−9.372** (3.455)	−8.906** (3.541)	−7.889** (3.617)	−8.974** (3.560)	−10.080*** (3.425)	−8.573** (3.469)	−6.077 (3.343)	−10.139*** (3.594)	−7.441** (3.620)
Hansen test Hansen J-statistics p-value	9.350 0.10	10.722 0.06	11.305 0.05	10.318 0.07	12.648 0.03	9.736 0.08	10.428 0.06	9.756 0.08	14.505 0.01	10.533 0.06	12.686 0.03
Number of observations	419	419	419	419	419	419	419	419	419	419	419
Number of provinces	63	63	63	63	63	63	63	63	63	63	63

Note. Standard errors are in parentheses.

p < .1, **p < .05, ***p < .01.

Institutional variables such as Transparency, Time Costs, Informal Charge, Proactivity, Business Support Services, and Labor Quality have positive and statistically significant effects at the 1% level. Our findings are consistent with previous studies, including Baumol (1990), Djankov et al. (2000), McMillan and Woodruff (2002), Desai et al. (2003), Klapper et al. (2006), and Chambers and Munemo (2019). This consistency underscores the relevance of our study within the established body of knowledge. Among these indices, the business support services index has the highest impact on net firm entry: One-point improvement could translate into a 35.3% increase in the number of new firms in a province. Given the average new firm in a province is 1,240, this increase is equivalent to 436 new firms. Dong Thap province, which ranked as the second highest in the PCI 2019 report, serves as an exemplary model for providing effective business support services. The province’s leaders regularly organize events called “Café Doanh Nhân” (Coffee with Entrepreneurs) to listen to the concerns of local business owners. As a result, domestic firms in Dong Thap value and appreciate the support from the provincial government. Other enhanced business support services, such as trade promotion, access to regulatory information, business partner matchmaking, and the establishment of industrial zones or clusters (e.g., Bac Ninh, Bac Giang, and Thai Nguyen provinces in the North, as well as Binh Duong and Dong Nai provinces in the South), along with technological services (e.g., Hoa Lac High-Tech Park in Hanoi and Saigon High-Tech Park in Ho Chi Minh City), are worth investing in to promote entrepreneurship.

The labor quality index also has a substantial impact. A one-point increase in provincial services in general education, vocational training, skills development, and assistance in the placement of local labor could increase 32% net firm entry in that province. If the transparency index, which measures the access to proper planning and legal documents for running a business, improves by one point, it could result in a 29.2% increase in the net firm entry of a province. From 2012 to 2019, there are signs of improvement in information access. The quality of provincial websites was enhanced which helped firms easier to access provincial documents. The percentage of domestic firms that stated “relations are needed to have access to provincial planning documents” dropped from 69.4% in 2018 to 60 percent in 2019.

Similarly, if the informal charge index, which measures the extent of informal charges paid by firms and rents extracted by provincial officials, changes by one point, it could lead to a 26.7% increase in the number of firms operating in a province. The results are consistent with the study’s findings of T. T. Nguyen and van Dijk (2012), which shows the negative correlation between the ratio of informal payments that a firm pays over annual sales and the firm’s growth. The PCI 2019 report shows that the percentage of business operations claimed to have paid informal charges is at the lowest rate share over the last 6 years, which demonstrates a major effort of the provincial government to combat corruption. The time costs index, which is a measure of wasting time on bureaucratic compliance and inspections by local regulatory agencies, gives a rise of 19.2% in the number of new firms for its one-point change.

The proactivity of provincial leadership also plays a role in promoting entrepreneurship as demonstrated by a one-point improvement in the index, which refers to creativity and cleverness in implementing the central policies, translates into an 18.3% increase in net firm entry in that province. Leaders in the provinces that ranked top in the PCI 2019 report—Quang Ninh and Bac Ninh in the North, Da Nang in the Central region, and Dong Thap and Vinh Long in the Mekong Delta—have consistently taken proactive steps to support businesses. For instance, the leadership in Quang Ninh, a province that achieved the highest ranking in the PCI 2019 report, has established accountability at all levels and across various agencies to create a business-friendly environment.

We find that the entry costs for new firms have no impact on net firm entry in a province. This result is inconsistent with previous studies which showed that the procedure of starting a business influences entrepreneurial activity (Aparicio et al., 2016; Autio & Fu, 2015; Chambers & Munemo, 2019; Dreher & Gassebner, 2013). In the context of Vietnam, measurements of entry costs for new firms, which include information such as length of business registration in days or number of licenses and permits necessary to start operations, are already high and do not vary much among provinces as reported in Table 1. The insignificant impact is understandable. Similarly, Policy bias, which is privileged to state-owned corporations, and the Legal institution index, which is the private sector’s confidence in the effectiveness of provincial legal institutions, have no impact on entrepreneurship.

We obtained interesting results concerning land access and tenure security (PCI2). While previous studies predominantly demonstrated a positive relationship between strong property rights protection and entrepreneurial activity (Desai et al., 2003; Fogel et al., 2009), land access and tenure security index in our study has a negative and statistically significant impact on entrepreneurship. This indicator is a comprehensive measure that includes two critical dimensions of the land-related challenges faced by entrepreneurs: the ease of accessing land and the security of tenure once the land is acquired. Upon closer examination of the indicator among provinces, it becomes evident that land access and tenure in economic hubs like Ho Chi Minh City and Hanoi, and Khanh Hoa fall below the average. Furthermore, Table 2 reveals a negative relationship between land access and business support services, as well as labor quality. This suggests that economic hubs with superior labor quality, business support services, and entrepreneurial activity tend to be ranked lower on land access and tenure. The primary explanation for this phenomenon is that economic hubs face more significant challenges in terms of land availability, land access, and land ownership compared to other provinces in Vietnam. These factors explain the observed negative impact of land access and tenure on entrepreneurship in our study. The findings support previous research which suggests that institutional variables matter for entrepreneurial activities. Especially, this paper adopts a multi-dimensional approach to study institutions by using 11 indicators that provide in-deep impacts of various institutional aspects on entrepreneurship.

In the growth equation, we found a positive statistically significant impact of net entry firms on the economic growth rate, with a significance level of 1%. This finding contradicts several previous studies that have suggested a negative or non-existent relationship between entrepreneurship and economic growth in developing countries (Kim et al., 2022; Sautet, 2013; Tang & Koveos, 2004; Van Stel et al., 2005). However, this study aligns with the findings of previous studies conducted by Berkowitz and Dejong (2001) and Li et al. (2012). These studies found a strong relationship between entrepreneurship and growth and emphasized the significant role of entrepreneurial activity as a key driver of long-term economic growth in post-socialist economies. For instance, Berkowitz and Dejong (2001) reported that an additional 1.7 registered enterprises per 1,000 inhabitants generated an increase in real economic growth of 1.5% points over 1993 to 1997 and 1.0% over 1993 to 2000. Similarly, Li et al. (2012) asserted that a rise in per capita GDP growth rate by 3.2% points in 5 years or 0.6% points per annum is explained by a 3.2 increase in entrepreneurship every 5 years. Our finding is also consistent with the research of Tahir and Burki (2023) which finds evidence that entrepreneurship has positively and significantly impacted the economic growth of BRICS economies. Especially, our findings align with the results of M.-L. Tran and Lo (2024)’s study which affirms the vital role of entrepreneurial activity in enhancing regional economic performance in Vietnam.

Moreover, our finding suggests that institutions facilitate entrepreneurship activities that foster economic growth. This result aligns with Bosma et al. (2018), which indicated that enhancing each institutional component, such as the regulation of credit, labor, and business, the size of government, and the perceived skill required to start a business, by 10% results in a 1% increase in the growth rate of GDP per capita. Our results are supported by the finding of Galindo-Martin et al. (2020) in analyzing the data of 31 countries to test the existing relationships between institutions, entrepreneurship and economic growth. Similarly, they indicated that institutions play an important role in enhancing entrepreneurship and economic growth and there is a positive relationship between entrepreneurship and economic growth.

For robustness, we replace the net firm entry variable (ENT), which measures the difference between newly registered firms and dissolved firms in a given province for a given year, with a new ENT variable that specifically captures non-state enterprises. We argue that there is organizational heterogeneity in the decisions regarding firm entry and exit, particularly in transitional economies. Consequently, conducting a model test that excludes non-state enterprises has the potential to offer further insights into the robustness of the results, thereby enhancing our understanding of the phenomenon. Table 4 presents the results of the GMM 3SLS regression for the entrepreneurship equation and growth equation with the new ENT variable.

Table 4.

GMM 3SLS Regression on Entrepreneurship and Growth (ENT= the Number of Non-State Firms Per 1,000 Inhabitants).

GMM	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9	Model 10	Model 11
Entrepreneurship equation
Composite PCI	0.029*** (0.008)
Entry cost (PCI1)		−0.011 (0.095)
Land access (PCI2)			−0.239*** (0.060)
Transparency (PCI3)				0.250*** (0.061)
Time cost (PCI4)					0.088** (0.072)
Informal charge (PCI5)						0.130*** (0.041)
Policy bias (PCI6)							0.170*** (0.032)
Proactivity (PCI7)								0.073** (0.054)
Business support services (PCI8)									0.149*** (0.034)
Labor quality (PCI9)										0.165*** (0.046)
Legal institutions (PCI10)											0.041 (0.045)
ln(UEMP)	0.271*** (0.059)	0.299*** (0.063)	0.314*** (0.058)	0.272*** (0.057)	0.264*** (0.061)	0.277*** (0.060)	0.308*** (0.065)	0.280*** (0.062)	0.289** (0.061)	0.279*** (0.059)	0.278*** (0.060)
gGDP	0.028 (0.021)	0.022 (0.021)	0.024 (0.021)	0.024 (0.020)	0.031 (0.021)	0.028 (0.021)	0.022 (0.019)	0.022 (0.021)	0.047** (0.023)	0.028 (0.022)	0.027 (0.022)
Constant	−0.716 (0.540)	1.146 (0.906)	2.450*** (0.427)	−0.368 (0.387)	0.485 (0.300)	0.286 (0.298)	0.080 (0.215)	0.612** (0.257)	—0.019 (0.283)	0.134 (0.349)	0.781*** (0.300)
Growth equation
ln(ENT)	1.402** (0.584)	1.153*** (0.578)	1.313** (0.552)	1.466** (0.600)	1.413** (0.575)	0.464** (0.590)	1.512*** (0.580)	0.512*** (0.591)	1.170** (0.536)	1.211** (0.572)	1.631*** (0.574)
ln(INV)	3.244*** (0.974)	3.312*** (0.901)	2.833*** (0.964)	3.303*** (0.965)	2.887*** (0.983)	3.269*** (0.962)	3.179*** (0.945)	3.181*** (0.958)	2.183** (0.910)	3.366*** (0.961)	2.944*** (0.989)
ln(labor)	1.001 (0.760)	0.919 (0.764)	0.848 (0.726)	1.011 (0.759)	1.018 (0.769)	0.966 (0.751)	0.792 (0.732)	0.922 (0.751)	0.926 (0.718)	0.972 (0.740)	0.991 (0.766)
ln(Tech)	−0.150 (0.340)	−0.206 (0.339)	−0.166 (0.347)	−0.183 (0.352)	−0.255 (0.343)	−0.164 (0.321)	−0.181 (0.336)	−0.232 (0.356)	−0.055 (0.310)	0.040 (0.338)	−0.373 (0.333)
Constant	−8.630** (3.863)	−8.578** (3.445)	−6.446* (3.837)	−8.809** (3.768)	−6.976* (3.856)	−8.649** (3.782)	−7.829** (3.696)	−8.002** (3.733)	−4.510 (3.594)	−9.458** (3.854)	−6.977* (3.842)
Hansen test, Hansen J-statistics p-value	8.461 0.13	8.259 0.14	8.664 0.12	7.823 0.166	12.254 0.03	8.269 0.14	7.118 0.21	7.825 0.16	12.345 0.03	10.062 0.07	9.562 0.08
Number of observations	426	426	426	426	426	426	426	426	426	426	426
Number of provinces	63	63	63	63	63	63	63	63	63	63	63

Note. Standard errors are in parentheses.

p < .1, **p < .05, ***p < .01.

In general, the results obtained using the new ENT variable align closely with those from the original model. However, there are three noteworthy variations to highlight. Firstly, while the significance levels of most variables remain unchanged, the estimated coefficients of the institution variables in the new model are slightly smaller compared to the previous model. Secondly, the policy bias variable, which showed no impact on entrepreneurship in the original model, becomes positively significant in this new model. This suggests that in provinces where fewer privileges are granted to state-owned entities, we observe a higher rate of net firm entry. And thirdly, the impact of entrepreneurship on economic growth is significantly stronger in the model that excludes state enterprises.

Conclusion

In this paper, we investigate the nexus between institutions and entrepreneurship and its impact on long-term economic growth within the context of a transitional economy. We analyze panel data from 63 provinces and cities in Vietnam, covering the period from 2012 to 2019. To address the endogeneity problem, we utilize the Generalized Method of Moments (GMM) regression to simultaneously estimate a set of two equations. This study generates two main results. First, we observe a positive relationship between institutional factors and entrepreneurship in general. Specifically, we find that higher institutional quality corresponds to an increased net entry rate of private enterprises in the economy. This finding aligns with the recent studies that highlight the significant role of institutions in explaining the variations in regional entrepreneurial activities. Moreover, we find that several institutional indicators such as business support services, labor quality, transparency, informal charge, time costs, and proactivity substantially impact the net firm entry. A mere one-point improvement in any of these indicators could potentially translate into an 18% to 35% increase in the number of new firms in a province. Second, our study reveals compelling statistical evidence illustrating how institutional factors indirectly influence economic growth through entrepreneurship. Our analysis demonstrates that the dynamics of entrepreneurship can significantly enhance economic growth; however, this positive relationship only emerges when there are supportive institutional frameworks in place. This finding aligns with the perspective that well-functioning institutions serve as essential mechanisms for nurturing entrepreneurial activities. Consequently, fostering such institutions not only encourages entrepreneurship but also contributes to sustained long-term economic growth.

The major contribution of this study lies in its exploration of the simultaneous relationship between institutions, entrepreneurship, and long-term economic growth, rather than examining their separate effects. In the spirit of Aparicio et al. (2016) and Bosma et al. (2018), we develop a system of two equations, in which entrepreneurship moderates the institutions’ effect on economic growth for the data of a specific country. Our results provide empirical evidence that enriches the existing literature on the nexus of these concepts, especially within the context of a transition economy where entrepreneurial activity plays a vital role in the economic development process.

The findings of this study are important not only for academic purposes but also for policymakers. It is possible to imply that economic growth can be obtained by encouraging the appropriate institutional elements in order to increase entrepreneurship activities. The policy suggestions include increasing transparency in the accessibility to legal documents and the proactivity and creativity in policy implementation of provincial authorities. Each province should also enhance the business support services and labor quality to facilitate entrepreneurial activities. In addition, it is necessary to decrease time costs and informal charges to administrative procedures. Provinces that have made significant improvements in various indicators have seen an overall increase in their institutional levels as reflected in the PCI reports over the years. Quang Ninh province is a notable example, having improved in eight out of the 10 institutional indicators measured by the PCI. In 2012, it ranked 20th out of 63 provinces and cities with a score of 59.55 out of 100. By 2019, it had climbed to first place with a score of 73.40, achieving an average annual increase of 1.68 points during the study period.

Formal and informal institutions work together, especially in transition economies, and their interaction should be a critical aspect of the new institutional perspective proposed by Gërxhani and Cichocki (2023). This study primarily focuses on estimating the impact of formal institutions on entrepreneurship. However, it is important to recognize that informal factors may have an even greater influence on entrepreneurship than formal institutions. This is particularly true in transition economies, where formal institutions are still developing, and entrepreneurs often rely on informal networks to establish connections (Ivy & Perényi, 2020). Further research is necessary to determine the extent to which these informal factors impact entrepreneurship in transitional economies. Additionally, future studies should explore the various types of entrepreneurship and the different stages of the entrepreneurial process, particularly within the context of these economies. By examining the specific characteristics and dynamics of different types and stages of entrepreneurship, researchers can gain deeper insights into the complex relationships between institutions and entrepreneurial outcomes. This understanding would facilitate a comprehensive analysis of how institutions can effectively promote entrepreneurial activities and, in turn, enhance long-term economic growth.

Footnotes

ORCID iD

Truc Thanh Tran

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is funded by University of Economics Ho Chi Minh City, Vietnam.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Vietnam in Transition: The Nexus of Institutions,Entrepreneurship,and Economic Growth

Abstract

Keywords

Introduction

Literature Review

Entrepreneurial Dynamic: Insights From New Entry and Exit Firms

The Impact of Institutions on Entrepreneurship

The Relationship Between Entrepreneurship and Economic Growth

The Nexus Between Institutions, Entrepreneurship, and Economic Growth

Data and Methodology

Results and Discussions

Conclusion

Footnotes

ORCID iD

Funding

Declaration of Conflicting Interests

Data Availability Statement

References