Tóm tắt: Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam

Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.Tiếp cận vốn và tăng trưởng của các doanh nghiệp nhỏ và vừa Việt Nam.

INTRODUCTION

REASONS FOR CHOOSING THE TOPIC

Small and medium-sized enterprises (SMEs) are crucial to global economies, particularly in developing nations, where they constitute approximately 90% of all businesses and generate over 50% of employment worldwide According to the World Bank (2021), SMEs contribute up to 40% of GDP and are responsible for creating 7 out of 10 jobs in emerging markets In OECD countries, SMEs represent about 99% of enterprises and account for nearly 60% of GDP (OECD, 2019) Over the past two decades, SMEs have been the primary source of job creation globally (Mateev and Anastasov, 2010).

Vietnamese SMEs share common traits with global SMEs and are crucial to the national economy, representing 96% of all companies, employing 47% of the workforce, and contributing 36% to the country's added value They account for 88% of export enterprises and approximately half of the total export volume (OECD, 2021) According to the Ministry of Planning and Investment (MKHDT, 2022), on average during this period

From 2016 to 2020, small and medium-sized enterprises (SMEs) represented 97.2% of all businesses in the country, employing 38.8% of the workforce and contributing 31% of total capital, with net revenues of 6,351 trillion VND, accounting for 27.6% of overall enterprise revenue Despite their significant economic impact, SMEs face substantial challenges, with the International Finance Corporation (IFC) reporting that 40% of formal SMEs in developing nations have an unmet financial need of $5.2 trillion annually Moreover, SMEs provide over half of formal employment in these countries but often struggle to secure the financial resources necessary for growth and job creation, a concern echoed by organizations such as the OECD and ADB.

Access to finance remains a significant barrier for the survival and growth of small and medium enterprises (SMEs) globally, as highlighted by Mueller and Zimmermann (2008) The 2021 Competitiveness Survey of Vietnamese Localities revealed that 47% of surveyed businesses struggled to secure capital, with notable workforce reductions among domestic private (33%) and foreign direct investment (FDI) enterprises (18%) The ongoing economic crisis exacerbated by the Covid-19 pandemic further complicates access to loans, necessitating proactive measures from both capital suppliers and demanders While management agencies are urged to facilitate better capital access, it is essential to assess whether businesses are prepared to utilize available funds effectively Vietnamese SMEs are recognized for their creativity and responsiveness, yet they typically exhibit limited investment in research and development, often opting for minor modifications to existing products to cater to low-income consumers This research aims to explore the relationship between capital access and the growth of Vietnamese SMEs, providing valuable insights for policy implications and enterprise development.

RESEARCH OBJECTIVES

This study aims to analyze how access to capital and environmental factors influence the growth of small and medium-sized enterprises (SMEs) in Vietnam By understanding these dynamics, the research seeks to propose effective policies that enhance capital accessibility and improve environmental conditions to foster SME growth.

(1) Research the impact of access to capital on the growth of SMEs in Vietnam

(2) Research the impact of environmental factors on the growth of SMEs in Vietnam

(3) Policy comments related to capital access and environmental factors in the growth of Vietnamese SMEs.

RESEARCH QUESTION

To achieve the goal, the topic needs to answer the following questions:

(1) Does access to capital impact the growth of SMEs in Vietnam? What is the trend and level of impact?

(2) How do environmental factors impact the growth of SMEs in Vietnam?

(3) What suggestions are needed for policies related to capital access and environmental factors in the growth of SMEs in Vietnam?

OBJECT AND SCOPE OF THE STUDY

Research the impact of capital access and environmental factors on the growth of SMEs in Vietnam

Enterprise growth indicators are essential for understanding business development, drawing on theories from Coase (1937), Penrose (2009), Gouillart and Kelly (1995), Freel and Robson (2004), and Delmar (1997) This research focuses on three key indicators: labor growth, revenue growth, and enterprise asset growth, which collectively provide a comprehensive framework for evaluating enterprise performance and growth potential.

The thesis examines the influence of capital access on enterprise growth by analyzing the effects of equity and debt within a research model It draws on Levine's (1997) successive definitions of capital access, as well as insights from Beck and Demirguc-Kunt (2008) regarding financial services Additionally, it incorporates the World Bank's (2008) theories on capital utilization and Merton's (1995) criteria for capital quantity, providing a comprehensive understanding of how access to capital impacts business development.

The research on SME units is based on Decree No 39/2018/ND-CP, utilizing data compiled from the General Statistics Office's annual reports and business activity summaries spanning from 2005 to 2022 Additional data sources include contributions from the Central Institute for Economic Management Research (CIEM), the Institute of Labor Sciences and Social Affairs (ILSSA), the United Nations University World Development Economics Research Institute (UNU-WIDER), and the University of Copenhagen's Department of Economics (DOE), all of which coordinated the investigation and research efforts.

RESEARCH METHODS

The project uses a combination of qualitative and quantitative methods, including:

The qualitative method employs analysis and synthesis techniques grounded in scientific theory and prior experimental research It utilizes descriptive statistical techniques to examine the current state of the phenomenon and the characteristics of the research variables.

The research employs a quantitative method aimed at ensuring the reliability and sustainability of results through econometric models grounded in theory and prior research Utilizing Bayesian quantitative techniques, specifically Markov Chain Monte Carlo (MCMC) methods along with Gibbs and Metropolis-Hastings sampling, the study investigates the effects of equity, debt, and environmental factors on the growth of SMEs in Vietnam.

NEW CONTRIBUTIONS OF THE THESIS

Previous studies have often included only one or two growth scales and have inadequately demonstrated the statistical significance of their findings, highlighting a theoretical gap in the research The use of varying measurement scales can yield different results, and studies with diverse data and scopes lack consistent standards for comparison (Delmar, 1997) This article aims to address this gap by examining the impact of capital access—both equity and debt—on three distinct growth scales, thereby providing a more comprehensive analysis and clearer correlations between variables based on a unified comparison framework.

The thesis employs a Bayesian approach featuring three growth scales and two impact capital components, offering a novel perspective compared to traditional frequency research methods This Bayesian technique delivers direct probability results regarding hypothesized effects, making it resilient to issues like small sample sizes, insufficient observations, or violations of research assumptions that often challenge frequentist methods.

Access to capital significantly influences the growth of SMEs in Vietnam Specifically, equity capital positively contributes to asset growth, while debt financing enhances labor growth and revenue generation.

This article analyzes the significant influence of equity and debt on the growth of Vietnamese SMEs, utilizing a comprehensive data set and robust analytical methods to reveal current trends and impacts.

(2) Added evidence of empirical results on the impact of accessible capital sources such as equity and debt on the growth of Vietnamese SMEs

(3) Research results are collated and compared with world cases and are a necessary reference source for related governance and management policymaking

Equity positively influences asset growth, providing a solid foundation for businesses to plan capital creation and scale operations effectively Additionally, the positive correlation between debt and labor as well as revenue growth instills confidence in commercial banks and credit institutions, encouraging them to increase lending to businesses This insight serves as motivation for companies to strategically allocate capital and leverage loan resources for their production and operational activities Furthermore, these research findings can guide authorities in facilitating easier access to capital for businesses.

The findings indicate that larger enterprises positively influence labor, revenue, and asset growth, while older enterprises tend to have a negative impact on these areas This insight allows businesses to proactively develop strategies and optimize their processes, serving as a foundation for authorities to create tailored support roadmaps.

The outcomes of education and training levels, along with export factors and industry influences, play a crucial role in guiding businesses to allocate resources effectively Additionally, these insights assist authorities in formulating strategic plans for immediate, overarching, and future development initiatives.

CONTENT LAYOUT OF THE THESIS

Chapter 5: Conclusion and policy suggestions

Chapter 1 introduces the research objectives and the urgency of the topic The introduced contents include the subject, scope of research, data sources, research questions, and research methods The scientific and practical contributions to the topic have also been stated

In addition, Chapter 1 also outlines the content layout of the topic, including five chapters.

THEORETICAL OVERVIEW

ECONOMIC GROWTH

Economic growth refers to the increase in total output within an economy over two distinct periods Robert Solow (1957) identified three key drivers of economic growth: investment, labor force, and technological advancements Mankiw and colleagues (1992) expanded upon Solow's model by incorporating human capital into the Cobb-Douglas production function, highlighting its significance in enhancing economic productivity.

Y(t): total quantity of final goods produced at time t

At time t, K(t), L(t), and A(t) denote total capital, labor force, and technology, respectively, with A(t) encompassing the effects of production and market organization on production factors Additionally, H(t) signifies the human capital factor This model, empirically researched by Mankiw and his colleagues, significantly contributes to the understanding of economic growth theory.

BUSINESS GROWTH

Based on research documents on enterprise growth, there are currently three theories, including:

2.2.1 Growth theory is based on the boundary theory of the firm

Coase (1937) posited that a company's growth is directly linked to the volume of transactions it engages in He introduced the concept of "transaction costs" to elucidate the factors influencing the formation and size of businesses, concluding that as transaction costs rise, the scale of the business tends to increase This expansion, in turn, leads to further increases in transaction costs.

2.2.2 Growth theory is based on the life cycle

Organizational life cycle models, as outlined by various scholars including Adizes (1989) and Churchill and Lewis (1983), identify four key stages: emergence, growth, maturity, and decline These stages represent the typical progression of an organization throughout its existence, highlighting the dynamic changes it undergoes over time.

2.2.3 Growth theory is based on gene combinations

The enterprise can be likened to a biological organism, with its influencing factors akin to genes and chromosomes According to Gouillart and Kelly (1995), enterprise transformation involves the organizational redesign of these 'genes' at varying speeds across four key dimensions: restructuring, which alters perspectives and concepts; scaling, which addresses the size of the enterprise; regeneration, which modifies the structure and operating environment; and innovation, which focuses on developing individuals with new skills, capabilities, and goals.

According to Penrose (1959), company size should be assessed by total resources, including personnel Numerous authors, such as Delmar (1997) and Gilbert et al (2006), support this view, identifying growth indicators like market share, assets, profits, employment, and sales These enterprise growth theories suggest that growth indicators are interconnected with human factors, production outcomes, and asset management Furthermore, the classification criteria for SMEs in Vietnam, as outlined in Decree No 39/2018/ND-CP, also consider labor force, total revenue, and total capital Therefore, incorporating all three growth indicators in the research model is a sound approach.

ACCESS TO CAPITAL

2.3.1 Definition of access to capital

Access to capital is a crucial aspect of economics and corporate governance, though it lacks a universal definition, as interpretations vary among authors based on their research focus and methodologies Levine (1997) describes capital access as the ability of individuals and businesses to utilize financial intermediation services for securing external capital to invest in profitable ventures Beck and Demirguc-Kunt (2008) emphasize that access to capital encompasses the extent to which financial services, such as credit, savings, insurance, and payment options, are available to individuals and businesses The World Bank (2008) defines widespread access to financial services as the absence of barriers preventing their use Consequently, capital access involves not only the quantity of capital but also the availability, affordability, and appropriateness of financial products tailored to meet diverse needs Despite varying perspectives, fundamental elements such as the nature of capital, the concept of access, and influencing factors are essential for defining access to capital.

Capital has been a fundamental concept in socio-economic life since ancient times, existing in both resource funds and goods storage Lewin and Cachanosky (2021) argue that capital should be viewed as the value of all produced goods under a firm's control, rather than solely the value of legally owned assets They emphasize that capital is crucial to growth theory within the neoclassical production function, as capital accumulation is essential for economic growth alongside other production factors.

Access to capital is crucial for businesses and individuals, allowing them to utilize financial services without barriers Capital sources can be classified in various ways, primarily into fixed and working capital based on their role in production Additionally, capital can be categorized as equity, contributed by investors and generated profits, or debt, which includes bank credit, trade credit, bonds, and funds from various organizations According to Hwang et al (2019), capital sources may be internal or external and can be public or private For small and medium-sized enterprises (SMEs), especially during the startup phase, reliance on internal capital sources such as retained profits and personal savings is common due to challenges like information ambiguity, lack of transaction history, and high failure risk.

External sources of capital include financial support from family and friends (Abouzeedan, 2003); commercial credit; joint venture capital; and angel financiers (He & Baker,

In 2007, external formal sources, including banks, financial institutions, and stock markets, play a crucial role in financing small and medium-sized enterprises (SMEs) However, the COVID-19 pandemic significantly affected the socio-economic landscape, leading to a slow growth in lending to SMEs globally, as reported by the OECD in 2020.

Influencing factors significantly affect an individual or business's access to capital, stemming from both the supply side, represented by financial institutions, and the demand side, encompassing businesses and individuals On the supply side, key elements include the macroeconomic environment, state policies, the characteristics of financial institutions, and the conditions surrounding guarantees Ultimately, enterprises rely on these organizations to make informed decisions regarding loan approvals.

The demand for capital is significantly influenced by businesses' effective utilization of accessible funds, which in turn enhances their production and business outcomes Successful performance builds trust and credibility, facilitating easier access to financing from financial institutions Additionally, businesses can leverage strategic capital usage to optimize their production and operations, as illustrated by the trade-off theory and the Pecking Order theory in finance.

Access to capital is a crucial aspect of financial intermediaries, evaluated through criteria such as quantity, type, cost, conditions, time, and capital risk (Merton, 1995) While capital serves as a common measure of access, it may not accurately represent a firm's true capital supply and demand due to factors like asymmetric information and market imperfections Various studies have assessed access to capital differently; for instance, Ayyagari et al (2011) focused on the fraction of fixed assets financed by banks in developing countries, while Fairlie and Robb (2020) examined startup capital invested by U.S entrepreneurs The World Bank (2008) emphasizes the distinction between the right to access financial services and their actual use, noting that some individuals may have access but choose not to utilize financial products, often influenced by cultural or religious factors Consequently, access to capital can be assessed by the amount of capital utilized by businesses, prompting the question of which capital sources are most commonly used and their distinct characteristics.

Capital, as defined by economists and synthesized by Trivedi & Bhattacharya (2018) and Lewin & Cachanosky (2021), can be categorized into two primary components: equity and debt Diamond (1984) argues that debt serves as the principal source of external finance due to its association with profit-sharing mechanisms and its cost-effectiveness in monitoring project implementation The World Bank (2008) notes that external debt financing from banks is prevalent among companies of all sizes Research by Harvie et al (2013) across 10 ASEAN countries indicates that SMEs primarily rely on internal sources, such as loans from friends or personal savings, to establish and operate new businesses, with external financing sought mainly for working capital, machinery, and growth Additionally, Rand et al (2015) highlight that small businesses often prefer using retained profits for investments, a trend reflected in a 2015 survey of 1,275 Vietnamese firms, which revealed that 39.7% of capital originated from retained profits, 47.2% from official loans, and 13.1% from unofficial loans.

In examining the operations of SMEs globally and in Vietnam, it is evident that equity capital and loan capital (debt) are crucial for the establishment, survival, and growth of enterprises The capital sources of SMEs are most effectively categorized into these two components: equity and debt Other classifications tend to lack clarity and completeness The influence of capital access on business growth is significantly illustrated through the roles of equity and debt within the research model.

Equity includes capital contributed by investors, profits generated in production and business processes, funds, and assets

Debt includes capital from bank credit, capital from trade credit, capital from bond issuance, capital from business partners, capital from government funds, and capital from international organizations.

IMPACT OF ACCESS TO CAPITAL ON ENTERPRISE GROWTH

Economic growth theory, encompassing classical, neoclassical, and modern economics, emphasizes the importance of capital in driving business expansion Coase (1937) noted that the addition of "transaction costs" contributes to the scaling of businesses The OECD (2019) highlights that providing SMEs with access to appropriately sized financial resources is crucial for their development and growth Cassar (2006) supports this by stating that finance is an essential resource for new business projects and a catalyst for growth Research by Robb et al (2010) indicates that as businesses grow, their debt levels increase Ayyagari et al (2005), Beck and Demirguc-Kunt (2006), and Klapper et al (2006) all assert that inadequate access to formal financing severely restricts SME operations, development, and the establishment of new enterprises, ultimately hindering productivity and growth.

In Vietnam, investment capital plays a crucial role in unlocking human and natural resources It is essential for expanding production scales, enhancing the economy's production capacity, and driving national economic restructuring.

IMPACT OF ENVIRONMENTAL FACTORS ON ENTERPRISE GROWTH11

Mankiw et al (1992) enhanced Robert Solow's growth function by incorporating a human capital component, while Gouillart and Kelly (1995) emphasized that enterprise growth is influenced by the enterprise's characteristics, size, organization, and operating environment Storey (1994) identified three key factors in enterprise growth: enterprise characteristics (such as scale, age, location, and industry), entrepreneur characteristics (including age, education, and gender), and enterprise strategy (focusing on exports, new product development, and competitive approaches) Machado (2016) synthesized findings from 16 journals, highlighting critical factors affecting SME growth, which include the entrepreneur's age, gender, education, experience, the nature of exports, state policies, and the business's market environment Therefore, it is essential to consider various environmental factors impacting business growth, including access to capital, enterprise size, establishment time, entrepreneur demographics, business lines, and export activities.

RELATED EXPERIMENTAL STUDIES

Table 2.1 Results of impact trends of equity and liability

The author did previous research Labor growth Revenue growth Asset growth

Honjo and Harada (2006); Rahaman (2011); Haynes and Brown (2009); Ha et al (2023)

Honjo and Harada (2006); Mateev and Anastasov (2010)

Serrasqueiro et al (2018); Ha et al (2022); Watson and Wilson (2002); Honjo and Harada (2006); Mateev and Anastasov (2010)

Mateev and Anastasov (2010); Gereben et al

Serrasqueiro et al (2018); Honjo and Harada (2006); Ha et al (2022); Watson and Wilson (2002); Mateev and Anastasov (2010); Pham et al

DISCUSSING SCIENCE GAPS

Through a brief review of previous related empirical studies, we can see a number of issues, as follows:

1 In terms of dependent variables, studies do not consistently use enterprise growth scales, as well as the period and scope of the research The impact direction and growth scale used in the studies had different or conflicting results Including more than two measurement scales in the model and establishing an autocorrelation matrix will be convenient for explaining the reasonableness of the relationships through experimental results Only a few authors, such as Heshmati (2001), Honjo, and Harada (2006), included in the research model all three scales: labor growth, revenue, and assets However, these studies use the frequency method, which has disadvantages such as small samples and a lack of observations, and the research results will be unstable SME data is often collected incompletely or lacks consistency (OECD, 2020; World

Heshmati, Honjo, and Harada (2008) utilized three distinct growth scales in their research, revealing varying outcomes among the scales However, they did not adequately clarify the rationale behind the observed trends in these results.

2 Regarding the explanatory variable of access to capital, there are studies that only use one of the two components, equity or debt, in absolute numbers or in relative numbers to reflect capital growth Using different indicators will lead to different results (Delmar, 1997; Heshmati, 2001; Honjo and Harada, 2006) Thus, adding new research is necessary (Delmar, 1997)

3 Most previous studies used frequency research methods In particular, the research by Ha and colleagues (2022, 2023) uses the Bayesian method but only includes total asset growth and labor growth in the research scale model.

Utilizing the Bayesian method to incorporate all three growth scales in the model effectively assesses the impact of capital access on business growth This approach enhances the reliability and validity of experimental outcomes by enabling a direct, probabilistic evaluation of hypothesized effects Notably, Bayesian estimates remain unaffected by issues such as sampling design, endogeneity, autocorrelation, and heteroskedasticity Furthermore, the clarity of Bayesian results facilitates communication among researchers and practitioners, making it a valuable tool in the analysis of business growth trends.

This thesis explores the influence of capital access on the growth of SMEs in Vietnam, integrating theories of economic and enterprise growth with insights from prior empirical studies The author identifies gaps in existing research and introduces a novel approach tailored to the unique characteristics of Vietnamese SMEs To enhance the reliability and sustainability of the findings, a combination of descriptive statistical methods and Bayesian estimation is employed in the analysis.

RESEARCH METHODS

ESTABLISH HYPOTHESES AND RESEARCH MODEL

This article explores the relationship between access to capital and the growth of small and medium-sized enterprises (SMEs) in Vietnam, drawing on theories of enterprise growth, capital access measurement, and the characteristics of SMEs globally and in Vietnam It evaluates the current operational status of Vietnamese SMEs and incorporates findings from previous empirical studies to propose hypotheses regarding the influence of capital access on their growth trajectory.

H1: Debt has a positive impact on labor growth

H2: Debt has a positive impact on revenue growth

H3: Debt has a negative impact on asset growth

H4: Equity has a positive impact on asset growth

H5: Equity capital has a negative impact on labor growth

H6: Equity has a negative impact on revenue growth

Based on the theoretical basis and inheritance of related empirical research mentioned above, the project includes the following variables for 3 models: labor growth, revenue growth, and total asset growth

The growth rate of full-time labor, denoted as lngLT, serves as a key indicator of enterprise growth This metric is calculated using the natural logarithm to compare the total full-time labor force between year t and the previous year, t-1 Specifically, lngLT reflects the difference in the natural logarithm values of the full-time labor force from one year to the next, providing insights into the company's labor dynamics and overall growth trajectory.

The growth rate of an enterprise is represented by the total revenue growth, calculated using the natural logarithm (lngTR) This value reflects the difference in the natural logarithm of total revenue between year t and the previous year, t-1.

The growth of an enterprise is measured by the growth rate of total assets, represented as lngTA, which is calculated using the natural logarithm This value reflects the difference in the natural logarithm of total assets between the current year (t) and the previous year (t-1).

To focus on the main solution, which is to consider the impact of capital on business growth, the topic divides the explanatory variables into two groups:

Is a group of capital variables that impact business growth, including:

- Total equity at the end of the year, calculated according to Natural Logarithm, symbol (lnEq)

- Total liabilities at the end of the year (representing non-enterprise loan capital) are calculated according to the natural logarithm, symbol (lnLi).

- Growth rate of total assets, symbol lngTA The lngTA variable represents firm size

- Growth rate of the enterprise's full-time workforce, symbol lngTL The variable lngTL represents firm size

- Number of years of establishment (age) of the enterprise (firm age), symbol lnFA

- Export factor, symbol (Ex): is a binary variable, with value equal to 1 if the enterprise exports, equal to 0 if the enterprise does not export

- Gender of the businessman, symbol Ge: is a binary variable, with value equal to 1 if he is male, equal to 0 if he is female

The education and training level of an entrepreneur is categorized into a binary variable system Edu1 indicates completion of university or postgraduate education, Edu2 signifies attendance at a college or vocational school, and Edu3 represents training in an occupation without a formal degree If none of these educational qualifications are met, then Edu1, Edu2, and Edu3 are all set to zero, reflecting a lack of occupational training.

- Production and business industry: Selected industries associated with binary variables to include in the model are based on a survey data set including a total of 20 industries Among the

In the analyzed dataset, the distribution of enterprises across 20 industries is uneven, leading to significant variations in their numbers To streamline the model and minimize the inclusion of excessive binary variables, only industries with 50 or more operating enterprises annually were selected This resulted in the creation of six binary variables representing distinct industry groups, while the remaining enterprises were categorized into Group 7 The binary variables are defined as follows: Sec1=1 for the paper industry, Sec2=1 for the garment industry, Sec3=1 for the food and beverage industry, Sec4=1 for the manufactured metal products industry, Sec5=1 for the wood industry, and Sec6=1 for the furniture, jewelry, musical equipment, watches, toys, and medical equipment sectors All other sectors are represented by Sec1 = Sec2 = Sec3 = Sec4 = Sec5 = Sec6 = 0.

This article explores the mathematical model proposed by Evans (1987), Honjo and Harada (2006), Mateev and Anastasov (2010), and Ha et al (2022, 2023), focusing on the theoretical foundations and real-world conditions of small and medium-sized enterprises (SMEs).

The project enhances three research models based on foreign scientific theories by Evans (1987), Honjo and Harada (2006), and Mateev and Anastasov (2010) by incorporating explanatory variables such as equity and debt, a labor growth scale, and utilizing Bayesian estimation methods Additionally, the model tailored for Vietnamese SMEs, as researched by Ha and colleagues (2022, 2023), introduces a revenue growth scale The resulting mathematical model is proposed for further analysis.

𝑌 𝑡 : The value at time t of the growth variable

𝑌 𝑡−1 : Value at time t-1 of the growth variable

Xt: Group of explanatory variables

Zt: Group of quantitative control variables

Dt: Group of qualitative control variables

Labor growth model: lngTLit = 𝛽 1 + 𝛽 2 lnEqit + 𝛽 3 lnLiit +𝛽 4 lngTAit +𝛽 5 lnFAit + 𝛽 6 Geni + 𝛽 7 Exi + 𝛽 8 Edu1i +

𝛽 9 Edu2i + 𝛽 10 Edu3i + 𝛽 11 Sec1i + 𝛽 12 Sec2i + 𝛽 13 Sec3i + 𝛽 14 Sec4i +𝛽 15 Sec5i +𝛽 16 Sec6i + 𝜀 𝑖

Revenue growth model: lngTRit = 𝛽 1 + 𝛽 2 lnEqit + 𝛽 3 lnLiit + 𝛽 4 lngTAit + 𝛽 5 lngTLit +𝛽 6 lnFAit + 𝛽 7 Geni + 𝛽 8 Exi +

𝛽 9 Edu1i + 𝛽 10 Edu2i + 𝛽 11 Edu3i + 𝛽 12 Sec1i + 𝛽 13 Sec2i + 𝛽 14 Sec3i + 𝛽 15 Sec4i +𝛽 16 Sec5i

Asset growth model: lngTAit = 𝛽 1 + 𝛽 2 lnEqit + 𝛽 3 lnLiit +𝛽 4 lngTLit +𝛽 5 lnFAit + 𝛽 6 Geni + 𝛽 7 Exi + 𝛽 8 Edu1i + 𝛽 9 Edu2i

+ 𝛽 10 Edu3i + 𝛽 11 Sec1i + 𝛽 12 Sec2i + 𝛽 13 Sec3i + 𝛽 14 Sec4i +𝛽 15 Sec5i +𝛽 16 Sec6i + 𝜀 𝑖

DATA

The article utilizes data gathered by the General Statistics Office, along with annual reports on enterprise activities from 2005 to 2022, and collaborates with various institutions including CIEM, ILSSA, UNU-WIDER, and the Department of Economics at the University of Copenhagen The investigation encompasses a sample of 2,512 to 2,821 SMEs across 20 industries within the processing and manufacturing sectors.

10 provinces and cities in Vietnam

Based on the national economic planning tasks in each 5-year period, the period from

The period from 2005 to 2015 is ideal for analyzing the growth of Vietnamese SMEs, allowing for a meaningful comparison with both the domestic and global economic landscapes This timeframe is particularly relevant as the subsequent years from 2015 to 2020 were significantly impacted by COVID-19, which disrupted survey data across various countries and regions worldwide.

Stata 17.0 software was used to match the ID codes of businesses over the years with 2,073 matching observations.

RESEARCH METHODS

This article employs statistical metrics, alongside a combination of charts and data tables, to analyze and synthesize the current landscape of Vietnamese SMEs It focuses on the characteristics of variables within a quantitative model, offering insights into the state of small and medium-sized enterprises in Vietnam.

The project uses the Bayesian method with the Markov Chain Monte Carlo (MCMC) technique, selecting Gibbs and Metropolis-Hastings samples due to the advantages that this method brings

1 White Paper for Vietnamese Enterprises in 2022 Part 2: Some main indicators of operating enterprises with production and business results 2016–2020, Statistics Publishing House; Current status of enterprises through survey results in 2005,

2006, and 2007, Statistics Publishing House, Hanoi 2008; Current status of enterprises through survey results in 2006, 2007,

The Statistics Publishing House in Hanoi has released several significant reports on the status of Vietnamese enterprises over the years Key publications include surveys from 2007 to 2009, a detailed analysis of SMEs from 2006 to 2011, and a report on production and business results in 2009 Additionally, the house documented the evolution of Vietnamese enterprises during the first 15 years of the century (2004–2014) and provided insights into the socio-economic dynamics of Vietnam in two five-year periods: 2011–2015 and 2016–2020.

SME data often presents challenges due to its incomplete nature, variability across countries, and fragmentation from multiple sources, complicating measurement efforts (World Bank, 2008; OECD, 2020) In Vietnam, the completeness and consistency of SME data are particularly limited compared to developed nations Utilizing frequency methods such as OLS, FEM, REM, and GMM can lead to common errors like assumption violations, multicollinearity, and endogeneity, exacerbated by small data samples with numerous missing values In contrast, the Bayesian method offers advantages as it remains unaffected by sampling design issues, endogenous phenomena, autocorrelation, and heteroscedasticity, ensuring more reliable estimates (Godambe, 1966; Basu, 1969; Scott and Smith, 1973; Gelman, 2009; Hassan and Blandón, 2019).

Bayesian analysis relies on posterior distributions to make inferences, focusing on the probabilities of population parameters (θ) given the observed data (D), represented as P(θ|D) This process integrates observed data with prior knowledge through Bayes' rule, allowing for a comprehensive understanding of the parameters in light of new evidence.

In Bayesian statistics, P(θ) denotes the prior probability, reflecting the expected likelihood of θ prior to data collection The term P(D|θ), known as likelihood, quantifies the probability of observing specific data given the prior θ The posterior probability, represented as P(θ|D), integrates both the likelihood and the prior Additionally, P(D) serves as the marginal likelihood, acting as a normalizing constant that ensures the posterior density is appropriately scaled.

The project utilizes Sata 17.0 software to estimate model parameters through the Bayesian method, which requires prior information about the variables involved Following the approach of Block et al (2011), the author selects a priori information for normally distributed parameters using various simulations Model testing encompasses several methods, including convergence tests, MCSE criteria diagnostics, Trace and Autocorrelation charts, Histogram and Kernel density plots, Cumulative sum plots, Gelman-Rubin diagnostics, simulation model comparisons, Bayesian sensitivity analysis, and posterior probability checks.

Chapter 3 introduces the research process, establishes models, and introduces and explains variables based on the theoretical basis analyzed in Chapter 2 Research hypotheses are proposed based on theory, empirical research, and Vietnam's economic context The contents of the research method presented include descriptive statistical methods, Bayesian estimation methods, analytical techniques, model tests, an introduction, and an analysis of data sources.

RESEARCH RESULTS

RESEARCH RESULTS AND DISCUSSION OF RESEARCH RESULTS

This project will conduct an analysis using five simulations of a priori information derived from normal distribution and inverse gamma distribution, focusing on three key scales: labor growth, revenue growth, and asset growth, as outlined in Chapter 3.

Prior distributions lngTL, lngTR, lngTA~ 𝑵(𝝁, 𝝈 𝟐 )

The variables lngTL (natural logarithm of labor growth rate), lngTR (natural logarithm of revenue growth rate), and lngTA (natural logarithm of asset growth rate) are normally distributed, characterized by a mean (μ) and variance (σ²) This indicates that each of these growth rates follows a predictable pattern, facilitating analysis and interpretation in economic studies.

𝛽 𝑖 are regression coefficients in research models, reflecting the impact of variables on business growth

𝜎 2 ~𝐼𝑛𝑣𝑔𝑎𝑚𝑚𝑎(0.01, 0.01): 𝜎 2 has the form of an inverse gamma distribution

Bayesian model and coefficient testing will be utilized to identify the most suitable simulation based on Log BF, Log (ML), and DIC criteria The project will assess the validity of Bayesian inference through convergence diagnostics, including autocorrelation, normal distribution, stability, and Max Gelman-Rubin Rc tests To enhance robustness and reliability, normal distribution priors will be fine-tuned to a range of -0.5 to 0.5, with increments of 0.1 for all parameters, forming the foundation for conclusions.

Bayesian estimation results based on the above selection procedure are presented in Tables 4.2, 4.3, and 4.4

Table 4.2: Bayesian simulation results of labor growth model lngTL

Mean Std Dev MCSE Median Equal-tailed

[95% Cred Interval] lnEq -.019893 0062293 000036 -.0198603 -.0321947 -.0077492 lnLi 0097885 0049992 000029 0097551 0000017 0196299 lngTA 0364819 0088226 000051 0365312 0189782 0535417 lnFA -.0271732 013181 000076 -.0272199 -.0531002 -.0011748

Source: Results estimated by Sata 17.0 from SME research data set

Table 4.3: Bayesian simulation results of revenue growth model lngTR

Mean Std Dev MCSE Median Equal-tailed

[95% Cred Interval] lnEq -.0055923 0093639 000054 -.0056136 -.0241137 0127845 lnLi 0064567 0074276 000043 0064697 -.0081316 0210934 lngTA 0036626 0130145 000076 0036584 -.0220226 0291699 lngTL 2456505 0223712 00013 2457209 201976 2893388 lnFA -.0534372 0207145 00012 -.0535429 -.0942476 -.0128681

Source: Author's calculations from SME research data set

Table 4.4: Bayesian simulation results of asset growth model lngTA

Mean Std Dev MCSE Median Equal-tailed

[95% Cred Interval] lnEq 1645891 0101728 000059 1646403 1444968 184426 lnLi -.036896 0083791 000048 -.0369493 -.0533023 -.0204146 lngTL 1028573 0248715 000144 1028507 053681 1512624 lnFA -.0897988 022076 000127 -.0898559 -.1331687 -.046379

Source: Author's calculations from SME research data set

The estimated parameters in Tables 4.2, 4.3, and 4.4 show that the Gelman-Rubin Rc value is 1 According to Gelman and Rubin (1992) and Brooks and Gelman (1998), a diagnostic

Rc value greater than 1.2 for any model parameter is considered non-converging In practice, Rc

< 1.1 is often used to conclude convergence Therefore, Max Gelman-Rubin Rc values < 1.1 indicate that MCMC convergence is acceptable for Bayesian analysis

Bayesian estimation results are simulated using the MCMC chain, with visual tests conducted to assess the convergence of variables lngTL, lngTR, and lngTA, ensuring the robustness of the estimates Diagnostic graphs will evaluate autocorrelation, normal distribution, and stability of the variables As outlined in Chapter 3, the trace chart illustrates the sequential calculated values of parameters, demonstrating that the MCMC series is stationary and meets convergence conditions Autocorrelation plots indicate a low level of autocorrelation, with fluctuations within a limit of 0.02, aligning with the distribution simulation density (StataCorp., 2021) Histogram plots reveal a uniform shape in frequency estimates and posterior distribution density, confirming the stability of Bayesian inference Additionally, the kernel density estimate plot shows three nearly coinciding curves, indicating effective convergence and combination of the series.

In conclusion, the convergence diagnostic charts for labor growth, revenue growth, and asset growth models indicate successful MCMC convergence for lngTL, lngTR, and lngTA, as supported by fundamental theoretical standards (StataCorp., 2021).

The author conducted a Bayesian sensitivity analysis to evaluate how variable effects influence the conclusions drawn from test results Findings indicate that adjusting all normal distribution a priori parameters to mean values ranging from -0.5 to 0.5, with an interval of 0.1, yields mean posterior values, MCSE, and intervals that demonstrate no significant difference in reliability Consequently, it can be concluded that the Bayesian inference results are valid and the estimated model exhibits stability.

To achieve reliable Bayesian conclusions, the project employs posterior probability to assess the dependability of research hypotheses after parameter estimation using the dataset and prior information Bayesian estimation utilizes the probability of direction (pd) to identify the positive or negative trajectory of a variable with an associated probability value The outcomes of the posterior probability calculations for the three models are presented in Tables 4.5, 4.6, and 4.7.

Table 4.5: Posterior probability of labor growth model

Source: Author's calculations from SME research data set

Table 4.6: Posterior probability of revenue growth model

Source: Author's calculations from SME research data set

Table 4.7: Posterior probability of asset growth model

Source: Author's calculations from SME research data set

To draw a definitive conclusion regarding the impact of a variable, the author selects a posterior probability level significantly distant from the median, opting for a threshold of 70% or higher as recommended by Gelman and colleagues (2021) As illustrated in Table 4.5, the variable Gene does not exhibit a strong directional impact.

The analysis reveals that the posterior probability stands at 63.79%, with Ex at 53.18%, Edu1 at 67.58%, Sec1 at 47.69%, Sec3 at 61.08%, and Sec6 at 57.45% According to Table 4.6, when a probability threshold of 70% is applied to assess the impact of variables, lngTA (58.60%), Gene (49.77%), and Sec1 (66.52%) do not demonstrate a clear directional impact Table 4.7 indicates that equity positively influences asset growth with a high probability of 97.50%, whereas debt negatively affects asset growth, also with a probability of 97.5% The findings are further compared to research expectations in Table 4.8.

Table 4.8: Comparison of research results with research expectations

H1 H1: Liability positively impacts labor growth + +

H2 H2: Liability positively impacts revenue growth + +

H3 H3: Liability negatively impacts asset growth - -

H4 H4: Equity positively impacts asset growth + +

H5 H5: Equity negatively impacts labor growth - -

H6 H6: Equity negatively impacts revenue growth - -

Source: Based on Bayesian estimation results of SME research data set

DISCUSS RESEARCH RESULTS

4.2.1 The impact of capital access on business growth

Research consistently supports the hypothesis that liability positively influences labor growth, aligning with findings from various studies, including those by Rahaman (2011), Ullah and Wei (2017), Brown et al (2017), Gereben et al (2019), Amamou et al (2020), IFC (2021), Heshmati (2001), Becchetti and Trovato (2002), as well as more recent research by Le (2022) and Ha et al (2023) focused on Vietnamese SMEs.

* Liability positively impacts revenue growth: The result is in line with hypothesis H2, supported by the views of Heshmati (2001), Honjo and Harada (2006), Mateev and Anastasov

In line with findings from Le (2022) and Pham et al (2020) regarding Vietnamese SMEs, this study reinforces the perspective of Combs et al (2005), Delmar (1997), Delmar et al (2003), and Rauch & Rijskik (2011) that there is a significant correlation between labor growth and economic revenue growth.

Liability adversely affects asset growth, aligning with hypothesis H3 and corroborated by global researchers like Heshmati (2001) and Serrasqueiro et al (2018) Additionally, Ha et al (2022) found similar conclusions in their study of Vietnamese SMEs.

Equity plays a significant role in enhancing asset growth, aligning with hypothesis H4 and supporting findings from previous studies by Watson and Wilson (2002), Serrasqueiro et al (2018), and Ha et al (2022) focused on Vietnamese SMEs.

* Equity negatively impacts labor growth: The research results are consistent with hypothesis

According to Rahman (2011), as enterprises gain greater access to bank credit, the influence of internal finance on their growth diminishes This shift indicates that while bank credit positively affects labor growth, the relationship between equity capital and labor growth is inversely correlated Consequently, an increase in liabilities, such as bank credit, supports labor growth, whereas equity capital negatively impacts it, aligning with the theoretical framework of hypothesis H1.

* Equity negatively impacts revenue growth: The results are in accordance with hypothesis

H6 The results are consistent in impact relationships when compared to the cases mentioned above

4.2.2 The impact of environmental factors on enterprise growth

* Enterprise size has a positive impact on labor growth, revenue, and assets

Research indicates that the size of an enterprise significantly influences its growth, with larger SMEs benefiting from increased internal resources and improved access to external resources (Abdulsaleh & Worthington, 2013; Federico et al., 2012) In Vietnam, studies show that business size positively affects revenue growth (Pham et al., 2020; Pham et al., 2017; Nham, 2012), labor growth (Pham et al., 2017; Ha et al., 2023), and asset growth (Pham et al., 2020; Ha et al., 2023).

* Firm age has a negative impact on growth on all three scales, supporting the views of Evans

Research indicates that young companies experience faster growth compared to their older counterparts, as supported by Coad et al (2011) This finding aligns with Ha et al (2022), which highlights the negative impact of enterprise age on labor and asset growth among Vietnamese SMEs.

(2020) and Le (2022) also found that business age negatively impacts revenue growth; Pham and colleagues (2020) found that age has a negative impact on asset growth

According to Brenner & Schimker (2015), the export factor negatively influences revenue and asset growth, indicating that a higher export proportion does not necessarily correlate with sustained growth This finding aligns with the studies conducted by Ha and colleagues (2022, 2023) on Vietnamese SMEs, which also suggest that exports adversely affect both asset and labor growth.

Entrepreneurs in Vietnam with higher educational qualifications, such as university and postgraduate degrees, tend to have a negative impact on the revenue and asset growth of small and medium-sized enterprises (SMEs) In contrast, those with vocational training but no formal degree positively influence these growth metrics This finding aligns with Becker's (1964) and Shepherd & Wiklund's (2006) perspectives, as well as Ha et al.'s (2022) research on Vietnamese SMEs Additionally, it supports Le and Nguyen's (2009) assertion that older entrepreneurs, despite lacking high educational attainment, often possess valuable experience in traditional occupations and enjoy better access to credit.

The six industries analyzed, including paper, clothing, food and drink, fabricated metal products, wood, furniture, jewelry, musical equipment, watches, toys, and medical equipment, have all negatively impacted total revenue and asset growth This decline can be attributed to the prevalence of traditional practices among Vietnamese SMEs, where many owners are senior artisans with limited formal education In contrast, younger entrepreneurs, despite possessing advanced degrees, often lack practical experience, making the findings relevant to the current economic landscape.

Chapter 4 presents the current situation of Vietnamese SMEs in the period 2005–2022 Empirical research results show that liability has a positive impact on labor growth and revenue growth, and equity has a positive impact on asset growth In addition, the project also discovered that factors such as size, age of the enterprise, level of education and training, and industry factors have an impact on enterprise growth.

CONCLUSION AND POLICY SUGGESTIONS

CONCLUSION

This study aims to analyze the influence of capital access and environmental factors on the growth of SMEs in Vietnam, offering policy recommendations to enhance these areas Utilizing descriptive statistics alongside Bayesian quantitative methods, including Markov Chain Monte Carlo (MCMC) techniques, Gibbs sampling, and Metropolis-Hastings, the research examines the current landscape of Vietnamese SMEs and the critical factors impacting their growth from 2005 to 2022.

Chapter 4 presents the level and impact trends of the variables through point estimate values and interval estimates assessed with posterior probabilities The analysis reveals the significant impact results of the variables under investigation.

5.1.1 The impact of capital access on the growth of SMEs in Vietnam

Research findings indicate that access to capital significantly influences the growth of SMEs in Vietnam, highlighting two key components: access to equity capital and access to liabilities.

(1) Impact of Liability: Liability has a positive impact on labor growth and revenue growth and a negative impact on asset growth

(2) Impact of Equity: Equity has a positive impact on asset growth and a negative impact on labor growth and revenue growth

5.1.2 The impact of environmental factors on the growth of SMEs in Vietnam

While the gender variable's influence on business growth remains ambiguous, other factors demonstrate a clear trend and significant impact, as evidenced by testing and the reliability of posterior probability.

(1) Enterprise size has a positive impact on labor growth, revenue growth, and asset growth

(2) Enterprise age has a negative impact on labor growth, revenue growth, and asset growth

Entrepreneurs with university and postgraduate degrees, as well as those from colleges and vocational schools, tend to hinder revenue and asset growth In contrast, entrepreneurs who have undergone vocational training without holding a degree positively influence labor and asset growth.

(4) Exporting enterprises have a negative impact on revenue growth and asset growth

(5) Paper industry; sewing clothes; food and drink; fabricated metal products; wood; Furniture, jewelry, musical equipment, watches, toys, and medical equipment have a negative impact on labor growth and asset growth

This research enhances the existing literature on capital access and business growth, specifically for SMEs in developing countries like Vietnam It addresses previous calls for further investigation into SME growth and serves as a valuable reference for organizations focused on the development of SMEs in emerging markets Additionally, the findings provide a scientific and practical foundation for proposing policies aimed at improving capital access and fostering SME growth.

POLICY COMMENTS

With the results achieved and conclusions drawn from Section 5.1, some comments on the policy of the topic are as follows:

The positive correlation between liability and labor and revenue growth indicates that SMEs effectively utilize loan capital, contributing to the expansion of both the labor and commodity markets This observation aligns with global trends discussed in previous chapters However, when liability negatively affects asset growth, it may reflect a shift in the roles of equity and liability over time From an individual business perspective, such negative impacts can stem from the inefficient use of liabilities As noted by Serrasqueiro et al (2018), SMEs' reliance on liability financing necessitates the repayment of principal and interest, which diminishes cash flow This reduction in cash flow complicates the ability to meet creditor obligations and limits internal financing, ultimately hindering corporate investment activities.

In summary, based on the research results, businesses can promote access to capital by simultaneously adding equity and liability sources to accelerate business growth

To enhance growth, enterprises must not only increase access to capital but also leverage their position and scale when seeking external resources It's crucial to focus on the timing and progression of accessing these capital sources Additionally, businesses should prioritize training, research and development, and the adoption of new technologies Improving production processes and methods is essential, especially in the export sector, where companies can source local materials to replace imports, enhance export expertise, seek suitable partners, reduce costs, and engage with agencies through management functions and associations to capitalize on economies of scale.

5.2.2 For the banking system and credit institutions

Capital is a crucial factor for the production and business operations of enterprises, with commercial banks and credit institutions serving as vital providers Fehder and Hochberg (2014) highlight that these capital providers not only impact individual companies but also create systemic effects within the ecosystem The positive correlation between loan capital usage and growth in labor and revenue indicates the need for banks to implement practical support programs for businesses To enhance access to loans, capital providers must address existing challenges by establishing clearer information portals and facilitating direct communication with enterprises for policy consultation Developing clear standards for assessing creditworthiness and timely appraisals is essential Additionally, collaboration with credit guarantee funds can boost lending capacity While liability may negatively impact asset growth, this can be attributed to high costs and risks associated with borrowing, particularly for Vietnamese SMEs facing asymmetric information Consequently, commercial banks should simplify lending procedures, reduce transaction times, and lower interest rates to foster investment growth and mitigate the reliance on unofficial loan sources Regulations regarding loan terms and conditions must be made more convenient for businesses.

The size of an enterprise significantly influences its operational scales, highlighting its crucial role in business success Enterprises must fulfill specific conditions to effectively utilize financial leverage in their production and business activities As noted by Oakey (1984), liabilities are essential for enterprise growth, aligning with the trade-off theory of capital structure, which emphasizes leveraging tax shields for optimal benefits Consequently, commercial banks and credit institutions should enhance their support for growth-oriented enterprises, particularly those in the growth phase.

Commercial banks and credit institutions should focus on supporting enterprises in the export sector, as they face high operating costs Additionally, it is crucial to provide assistance to businesses within traditional manufacturing industries to foster their growth and sustainability.

Vietnamese SMEs, like their global counterparts, face significant challenges in accessing loans due to insufficient information about their operations and performance, often incurring high costs in the process Research indicates that loans positively influence the growth of these enterprises, highlighting the need for supportive measures To foster this growth, authorities should implement timely and consistent policies, including state budget regulations for interest rate support Additionally, enhancing information sources about enterprise performance and standardizing evaluation and credit rating processes can improve access to capital and lower borrowing costs Creating favorable conditions for the Bank for Social Policies to execute credit programs is essential, alongside strengthening partnerships with international financial institutions to provide further incentives for the development of Vietnamese SMEs.

Research indicates that larger enterprises in Vietnam positively influence overall growth, attracting more workers and achieving higher profit margins The transition from small to large enterprises is crucial for enhancing the labor market and national goods and services However, certain sectors like garments, metal products, and wood face challenges that hinder growth, necessitating support for improved production methods and technology adoption Additionally, exporting enterprises encounter difficulties related to imports and elevated operating costs To foster growth, the government should implement policies that favor key industries, promote environmentally sustainable practices, assist small enterprises with operations and export experiences, encourage domestic production of alternative raw materials, and facilitate connections with foreign businesses.

Research indicates that the educational and training qualifications of entrepreneurs negatively affect enterprise growth, likely due to a disconnect between education outcomes and practical job market needs in Vietnam To foster the growth of Vietnamese SMEs, it is essential to enhance operational skills training in schools, establish effective practical experiment centers, and strengthen connections between educational institutions and businesses This approach will provide students with valuable hands-on experience in real production and enterprise environments Additionally, promoting healthy competition in education and improving training quality control are crucial for achieving better alignment between education and industry demands.

LIMITATIONS OF THE THESIS

The topic has contributed; however, there are limitations

Obtaining a comprehensive dataset on small and medium-sized enterprises (SMEs) is challenging both globally and in Vietnam due to a lack of standardization, which hinders consistent data variation over time (World Bank, 2008) The dynamic nature of the business environment, with thousands of new enterprises established and dissolved each year, complicates data collection A larger research sample would facilitate more effective analysis and evaluation of the variables impacting SMEs.

A larger sample size and comprehensive data can mitigate the issue of missing observations, allowing for the inclusion of additional main explanatory and control variables in the model In terms of explanatory variables, capital access can be enhanced by incorporating criteria such as type, cost, conditions, time, and risk, as suggested by capital access theory (Merton, 1995) Furthermore, the model can integrate more dummy variables related to industry factors to better capture the effects across various manufacturing sectors Additionally, a more nuanced analysis of company size can provide insights into the growth characteristics of enterprises based on their scale.

Therefore, the proposed topic should be supplemented with the stated limitations for future research.

Chapter 5 presented a summary of the research results for the topic from Chapter 4, after estimating the parameters and testing the model Based on this basis, the author has also proposed some suggestions and solutions to support small and medium-sized enterprises in developing

This article contributes to the research on the growth of small and medium-sized enterprises (SMEs), particularly through empirical evidence gathered in Vietnam Despite its valuable insights, the study acknowledges certain limitations discussed in Chapter 5 and offers suggestions for future research directions.

Decree No 39/2018/ND-CP, dated March 11, 2018

Ha, V D., Nguyen, V T, & Dang, T T N (2022), The Impact of Capital on Growth of Small and

Medium Enterprises: Evidence from Vietnam, Journal of Asian Finance, Economics and Business, 9(1), 0353–0362

Ha, V D., Nguyen, V T, & Dang, T T N (2023) The impact of accessible capital on labor growth of small and medium enterprises in Vietnam International Journal of Advanced and Applied

Le, N T T (2022) The Effect of Exports on Growth of Small and Medium-Sized Enterprises: Evidence from Vietnamese Manufacturing Firms Journal of Asian Finance, Economics and Business,

Ministry of Planning and Investment (MKH&I) (2022) Vietnam Business White Book 2022 Statistics

Nghị định số 39/2018/NĐ-CP, ngày 11/03/2018

Nguyen, T H., Khuu, T Q., & Nguyen, N D L (2018) Determinants of Firm Growth: Evidence from

Vietnamese Small and Medium Sized Manufacturing Enterprises Journal of Economics and

Nham, P T (2012) Gender, innovation and the growth of small medium enterprises: An empirical analysis of Vietnam’s manufacturing firms VNU Journal of Science, Economics and Business, 28(2), 87-102

Pham, H D., Runst, P., & Bizer, K (2017) Networks and Firm Performance: A Case Study of

Vietnamese Small and Medium Enterprises ifh Working Paper, 8 (2017), Volkswirtschaftliches Institut fỹr Mittelstand und Handwerk an der Universitọt Gửttingen (ifh), Gửttingen http://hdl.handle.net/10419/191850

Pham, H N., Kalyebar, B., & Islam, S M N (2020) Ownership Structure, Capital Structure and Firm

Growth: Empirical Evidence and Sustainable Growth Implications International Journal of Business and Economics, 19(3), 221-235

Rand, J., Brandt, K., Sharma, S., & Trifkovic, N (2015), Characteristics of the Vietnamese business environment: evidence from a SME survey in 2015, The Central Institute for Economic

The collaboration between CIEM, ILSSA, UNU-WIDER, and the University of Copenhagen's Department of Economics aims to enhance labor science and social affairs through innovative research and development initiatives.

Trinh, L Q, & Doan, H T T (2018) Internationalization and the growth of Vietnamese micro, small, and medium sized enterprises: Evidence from panel quantile regressions Journal of Asian Economics, 55, 71-83

Vietnam Chamber of Commerce and Industry (VCCI) (2021) Vietnam's Provincial Competitiveness

Index: Assessing the Quality of Economic Governance to Promote Business Development (PCI

2021) Hanoi: Vietnam Chamber of Commerce and Industry

Abouzeedan, A (2003) Financing Swedish Small and Medium-Sized Enterprises (SMEs): Methods,

Problems and Impact ERSA 2003 Congress

Achtenhagen, L., Naldi, L., & Melin, L (2010) Business growth: do practitioners and scholar really talk about the same thing? Entrepreneurship Theory and Practice, 34(3), 289-316

ADB (2014) ADB – OECD Study on Enhancing Financial Accessibility for SMEs: Lesson from Recent

Crises, Mandaluyong City, Philippines: Asian Development Bank

Adizes, I (1989) Corporate lifecycles: How and why corporations grow and die and what to do about it Englewood Cliffs, NJ: Prentice Hall

Amamou, R., Gereben, A., & Wolski, M (2020) Making a difference: Assessing the impact of the EIB's funding to SMEs EIB Working Paper

Ardishvili, A., Cardozo, S., Harmon, S., & Vadakath, S (1998) Towards a Theory of New Venture

Growth Paper presented at the1998 Babson Entrepreneurship Research Conference, Ghent,

Asian Development Bank (ADB) (2021) Asia Small and Medium-Sized Enterprise Monitor 2021

Volume I-Country and Regional Reviews Asian Development Bank (ADB)

Ayyagari, M., Demirguc-Kunt, A., & Maksimovic, V (2011) Firm Innovation in Emerging Markets:

The Role of Finance, Governance, and Competition Journal of Financial and Quantitative

Ayyagari, M., Beck, T & Demirgỹỗ-Kunt, A (2007) Small and medium enterprises across the globe

Ayyagari, M., Demirguc-Kunt, A., & Maksimovic, V (2005) How Important are Financing

Constraints? The Role of Finance in the Business Environment World Bank Mimeo

Basu, D (1969) Role of the sufficiency and likelihood principles in sample survey theory

Batt, R (2002) Managing customer services: human resource practices, quit rates, and sales growth

Becchetti, L., & Trovato, G (2002) The determinants of growth for small and medium sized firms: the role of the availability of external finance Small Business Economics,19(4), 291-306

Beck, T., & Demirguc-Kunt, A (2006) Small and medium-size enterprises: access to finance as a growth constraint Journal of Banking and Finance, 30(11), 2931-2943

Beck, T., Demirguc-Kunt, A (2008) Access to finance: An unfinished agenda World Bank Econ

Beck, T., Demirguc-Kunt, A (2008) Access to finance: An unfinished agenda World Bank Econ

Becker, G.S (1964) Human capital New York: Columbia University Press

Berger, A.N., & Udell, G.F (1998) The economics of small business finance: The roles of private equity and debt markets in the financial growth cycle Journal of Banking and Finance, 22(6-8): 613-

Berger, J O., & Pericchi, L R (1996) The intrinsic Bayes factor for model selection and prediction

Journal of the American Statistical Association, 91, 109–122 https://doi.org/10.2307/2291387 Berger, J O (2006) Bayes factors In Encyclopedia of Statistical Sciences, edited by Kotz, S., C B

Read, N Balakrishnan, and B Vidakovic Wiley http://onlinelibrary.wiley.com/doi/10.1002/0471667196.ess0985.pub2/abstract

Besag, J., & D Higdon, D (1999) Bayesian analysis for agricultural field experiments Journal of the

Royal Statistical Society, Series B 61, 691–746 https://doi.org/10.1111/1467-9868.00201

Block, J H., Jaskiewicz, P., & Miller, D (2011) Ownership versus management effects on performance in family and founder companies: A Bayesian reconciliation Journal of Family Business Strategy, 2(4), 232–245

Braun, E (2017) The theory of capital as a theory of capitalism Journal of Institutional Economics,

In "Principles of Corporate Finance," Brealey and Myers (2003) provide foundational insights into financial principles, emphasizing the importance of corporate financial strategies Brennan and Subrahmanyam (1996) explore market microstructure and its impact on asset pricing, particularly focusing on how illiquidity affects stock returns Additionally, Brenner and Schimke (2015) examine the growth development paths of smaller firms, highlighting the unique challenges and strategies that influence their financial trajectories.

Businesses Journal of Small Business Management, 53(2), 539–557

Brigham E.F., Ehrhardt M.C., (2008) Financial Management: Theory and Practice, Twelfth Edition,

Brook, S P., & Gelman, A (1998) General Methods for Monitoring Convergence of Iterative

Simulations Journal of Computational and Graphical Statistics, 7(4), 434-455

Brown, J D., & Earle, J S (2017) Finance and Growth at the Firm Level: Evidence from SBA Loans

Browne, W J (2017), MCMC Estimation in MlwiN Version 3.01, Centre for Multilevel Modelling

Cassar, G (2004) The financing of business start-ups Journal of Business Venturing, 19(2), 261-283 Cassar, G (2006) Entrepreneur opportunity cost and intended venture growth Journal of Business

Cekrezi, A (2013) A literature review of the trade−off theory of capital structure Iliria International

Chittenden, F., Hall, G C., & Hutchinson, P J (1996) Small Firm Growth, Access to Capital Markets and Financial Structure: Review of Issues and an Empirical Investigation Small Business

Churchill, N C., & Lewis, V L (1983) The five stages of small business growth Harvard Business

Clark, J., B (1890) The Distribution of Wealth - A Theory of Wages, Interest and Profits London:

Cliff, J E (1998) Does one size fit all? Exploring the relationship between attitudes towards growth, gender, and business size Journal of Business Venturing, 13(6), 523–542

Coase, R H (1937) The Nature of the Firm Economica, 4(16), 386 – 405

Cohen, A.J., & Harcourt, G.C (2003) Whatever happened to the Cambridge capital theory controversies? Preliminaries: Joan Robinson’s complaints Journal of Economic Perspectives, 17(1), 199– 214

Cohen J (1994) The earth is round (p < 0.05) American Psychologist, 49, 997–1003

Cole, R., Cumming, D., and Li, D (2016) Do banks or VCs spur small firm growth? Journal of

International Financial Markets, Institutions and Money, 41: 60-72

Combs, J G., Crook, T R., & Shook, C L (2005) The Dimensionality of Organizational Performance and its Implications for Strategic Management Research Research Methodology in Strategy and

Davidsson, P., Kirchhoff, B., Hatemi-J, A & Gustavsson, H (2002) Empirical analysis of growth factors using Swedish data Journal of Small Business Management, 40(4), 332-349

De Wet J.Hv.H (2006) Determining the Optimal Capital Structure: A Practical Contemporary

DeAngelo H., Masulis R., (1980), “Optimal Capital Structure under Corporate and Personal Taxation”,

Delmar, F (1997) Measuring growth: methodological considerations and empirical results, in

Donckels, R and Miettinen, A (Eds), Entrepreneurship and SME Research: On Its Way to the

Next Millennium, (199-216), Aldershot, England: Ashgate

Delmar, F., Davidsson, P., & Gartner, W (2003) Arriving at the high-growth firm Journal of Business

Dey, D K., S K Ghosh, and B K Mallick (2000) Generalized Linear Models: A Bayesian

Dey, D D., Muller, P., & Sinha, D (1998) Practical Nonparametric and Semiparametric Bayesian

Diamond, D.W (1989) Financial intermediation and delegated monitoring The Review of Economic

Domar, E (1946) Capital Expansion, Rate of Growth and Employment conometrica, 14, 137 - 147 Easley, D., & O’Hara, M (2004) Information and the cost of capital Journal of Finance, 59(4), 1553-

Elston, J & Audretsch, D (2011) Financing the entrepreneurial decision: an empirical approach using experimental data on risk attitudes Small Business Economics, 36, 209-222

Evans, D.S (1987) The relationship between firm size, age and growth: Estimates of 100 manufacturing companies The Journal of Industrial Economics, 35(4), 567-581

Fazzari S M., Hubbard, R G & Petersen, B C (1988) Financing constraints and corporate investment

Brookings Papers of Economic Activity, (1), 141-195

Federico, J., Rabetino, R & Kantis, H (2012) Comparing young SMEs’ growth determinants across regions Journal of Small Business and Enterprise Development, 19(4), 575-588

Fehder, D & Hochberg, Y (2014) Accelerators and the regional supply of venture capital investment

Fisher, F.M (2005) Aggregate production functions – a pervasive but unpersuasive fairytale Eastern

Fisher, I (1930) The Theory of Interests New York: Macmillan

Flamholtz, E G (1986) Managing the Transition from an Entrepreneurship to a Professionally

Managed Firm San Francisco: Jossey-Bass

Flegal, J M, Haran, M., & Jones, G L (2008) Markov Chain Monte Carlo: Can We Trust the Third

Freel, M S., & Robson, P J A (2004) Small firm innovation, growth and erformance: Evidence from

Scotland and Northern England International Small Business Journal, 22 (6), 561-575

Frid, C., Wyman, D., & Coffet, B (2016) Effects of wealth inequality on entrepreneurship Small

Gelman, A (2009) Bayes, Jeffreys, prior distributions and the philosophy of statistics Statistical

Gelman, A., Carlin, J B Stern, H S Dunson, D B Vehtari, A & Rubin, D B (2014) Bayesian Data

Analysis (3 rd ed) Boca Raton, FL: Chapman & Hall/CRC

Gelman, A., & Rubin, D B (1992) Inference form Iterative Simulation Using Multiple Sequences

Geman, S., & Geman, D (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721–741 https://doi.org/10.1109/TPAMI.1984.4767596

Gereben, A., Rop, A., Petricek, M., & Winkler, A (2019) Do IFIs make a difference? The impact of

EIB lending support for SMEs in Central and Eastern Europe during the global financial crisis

Gibrat, R (1931), Les inégalités économiques, Paris, Librairie du Recueil Sirey

Gigerenzer, G (2004) Mindless statistics The Journal of Socio-Economics, 33(5), 587-606

Gilbert, B.A., McDougall, P.P., & Audretsch, D.B (2006) New venture growth: a review and extension

Gill, J (2015) Bayesian Methods: A Social and Behavioral Sciences Approach Boca Raton, FL:

Godambe, V P (1966) A new approach to sampling from finite populations: I Journal of the Royal Statistical Society B, 28, 310–319

Gonzales, E., Hommes, M & Mirmulstein, M L (2014) MSME Country Indicators: Towards a better understanding of Micro, Small and Medium Enterprises, IFC

Gouillart, F J., & Kelly, J N (1995), Transforming the Organization, McGraw Hill, New York

Hahn, E D (2014) Bayesian Methods for Management and Business: Pragmatic Solutions for Real

Problems Hoboken, NJ: John Wiley & Sons

Hall, B H (1987) The Relationship between Firm Size and Firm Growth in the US Manufacturing

Sector Journal of Industrial Economics, 35(4), 583-606

Hanks, S H., C J Watson, E Jansen, & G N Chandler (1993) Tightening the life-cycle construct: A study of growth stage configurations in high-technology organizations Entrepreneurship Theory and Practice,18(2), 5–29

Hart, P E., & Prais, S J (1956) The Analysis of Business Concentration: A Statistical Approach

Journal of the Royal Statistical Society, 119(2), 150-191

Harvie, C., Narjoko, D., & Oum, S (2013), Small and Medium Enterprises’ Access to

Finance: Evidence from Selected Asian Economies, ERIA Discussion Paper Series, ERIA-DP- 2013-23

Hassan, A R., & Blandón, S M (2019) Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects Econometric Reviews, 38(3), 301–318

Haynes, G W., & Brown, J R (2009) How Strong is the Link between Internal Finance & Small Firm

Growth? Evidence from Survey of Small Business Finances Finance Publication, 7, 69-92

He, W., & Baker, H K (2007) Small Business Financing: Survey Evidence in West Texas The Journal of Entrepreneurial Finance and Business Ventures, 12(1), 27

Heshmati, A (2001) On the growth of micro and small firms: evidence from Sweden Small Business

Hodgson, G.M (2014) What is capital? Economists and sociologists have changed its meaning: should it be changed back? Cambridge Journal of Economics, 38(5), 1063– 1086 https:// doi.org/

Honjo, Y., & Harada, N (2006) SME policy, financial structure and firm growth: Evidence from Japan

Hubbard, R (2004) Alphabet soup: Blurring the distinctions between p’s and alpha’s in psychological research Theory and Psychology, 14(3), 295-327

Hubbard, R (2015) Corrupt Research: The Case for Reconceptualizing Empirical Management and

Social Science Thousand Oaks, CA: SAGE Publications

Huyghebaert, N., & Gucht, L M V D (2007) The Determinants of Financial Structure: New Insights from Business Start-Ups European Financial Management, 13(1), 101-133

Hwang, V., Desai, S., & Baird, R (2019), Access to Capital for Entrepreneurs: Removing Barriers,

Ewing Marion Kauffman Foundation: Kansas City

Hymer, S., & Pashigian, P (1962) Firm Size and Rate of Growth Journal of Political Economy, 70(6),

International Finance Corporation (IFC) (2010) The SME Banking Kwoledge Guide: IFC Advisory

Services/Access to Finance, International Finance Corporation (IFC), Second Editiion,

International Finance Corporation (IFC) (2017) SME Financial Gap: Assessment of The Shortfalls and

Opportunities in Financing Micro, Small and Medium Enterprises in Emerging Markets

International Finance Corporation (IFC) (2021) Small Business, Big Growth: How investing in SMEs creates jobs International Finance Corporation Washington, D.C

International Moneytary Fund (IMF) (2022) World Economic Outlook: War Sets Back the Global

Kass, R E., & Raftery, A E (1995) Bayes factors Journal of the American Statistical Association,

Klapper, L., Laeven, L., & Rajan, R (2006) Entry Regulation as a Barrier to ntrepreneurship Journal of Financial Economics, 82(3), 591– 629

Krugman, P (1994) The Myth of East Asian Miracle Foreign Affairs, 73(6), 28-44

Kruschke, J K (2015) Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2 nd ed)

Levie, J., & Lichtenstein, B B (2010) A terminal assessment of stages theory: Introducing a dynamic states approach to entrepreneurship Entrepreneurship Theory and Practice, 34(2), 317–350 Levine, R (2004) Finance and growth: Theory and evidence NBER Working Paper, 10766

Levine, R (1997) Financial Development and Economic Growth: Views and Agenda Journal of

Lewin, P., Cachanosky, N (2021) Capital and Finance – Theory and History Routledge, Oxon –

Love, I (2018) Entrepreneurial access to finance in the United States Working paper

Lucas, D., & McDonald, R.L (1990) Equity issues and stock price dynamics Journal of Finance,

Machado, H P V (2016) Growth of small businesses: a literature review and perspectives of studies

Mankiw, N G., Romer, D., & Weil, D N (1992) A Contribution to The Empirics of Economic

Growth The Quarterly Journal of Economics, 407 – 437

Mansfield, E (1962) Entry, Gibrat's Law, Innovation, and the Growth of Firms American Economic

Marris, R (1964) The Economic Theory of Managerial Capitalism London: MacMillan

Marshall, Alfred (1890) Principles of Economics London: Macmillan

Mateev, M., & Anastasov, Y (2010) Determinants of small and medium size fast growing enterprises in central and eastern Europe: a panel data analysis Financial Theory and Practice, 34(3), 269-

McElreath, R (2020) Statistical Rethinking: A Bayesian Course with Examples in R and Stan

Boca Raton, FL: CRC Press

McShane, B B., Gal, D., Gelman, A., Robert, C., & Tackett, J L (2019) Abandon statistical significance The American Statistician, 73(sup1), 235-245

Merton, R.C (1995) A functional perspective of financial intermediation Financial Management,

Mill, J., S (1848) Principles of Political Economy with Some of their Applications to Social

Philosophy, vol 1 & 2 (1 ed.), London: John W Parker

Ministry of Planning and Investment (MPI) (2021) The White Book on Vietnamese Businesses 2021

Mises, L von (1949) Human action (1996) Irvington- on- Hudson: The Foundation for Economic

Modigliani, F., & Miller, M H (1963) Corporate income taxes and the Cost of Capital: A correction

Mueller, E., & Zimmermann, V (2008) The importance of equity finance for R&D activity – Are There

Differences Between Young and Old Compaies? Forthcoming: Small Business Economics, 06-

14, Centre for European Economic Research

Myers, S C (1984) The Capital Structure Puzzle The Journal of Finance, 39(3), 575-591

Myers, S C., (2001) Capital structure Journal of Economic Perspectives, 15(2):81-102

Myers, S C., & Majluf, N S (1984) Corporate Financing and Investment Decisions When Firms Have

Information That Investors Do Not Have, 13(2), 187-221

Oakey, R., P (1984) Finance and Innovation in British Small Independent Firms The International

OECD (2005) OECD SME and Entrepreneurship Outlook 2005 OECD Publishing, Paris

OECD (2006) The SME Financing Gap, Theory and Evidence Paris: OECD

OECD (2019) SME and Entrepreneurship Outlook 2019 OECD Publishing, Paris

OECD (2020) Financing SMEs and Entrepreneurs: An OECD Scoreboard Special edition: The impact of COVID-19, OECD SME and Entrepreneurship Papers

OECD (2021) OECD SME and entrepreneurship outlook 2021 Organization for Economic Co- operation and Development, Paris, France https://doi.org/10.1787/97a5bbfe-en

O'Hagan, A., Buck, C E., Daneshkhah, A., Eiser, J R., Garthwaite, P H., Jenkinson, D J., &

Rakow, T (2006) Uncertain Judgements: Eliciting Experts' Probabilities Hoboken, NJ: John Wiley & Sons

Oliveira, B., & Fortunato, A (2006) Firm growth and liquidity constraints: a dynamic analysis Small

Penrose, E (2009), The Theory of the Growth of the Firm Oxford University Press, New York

Pole, A., West, M., & J Harrison, J (1994) Applied Bayesian Forecasting and Time Series Analysis

Boca Raton, FL: Chapman and Hall

Rafiki, A., 2019 Determinants of SME growth: an empirical study in Saudi Arabia International

Rahaman, M M (2011) Access to Financing and Firm Growth Journal of Banking & Finance, 35(3),

The article discusses the critical influence of human capital on the sustainability and success of newly established businesses, as highlighted in the research by Rauch and Rijskik (2011) It also references the Kauffman Firm Survey, which provides insights into entrepreneurial trends and outcomes from 2004 to 2008, as summarized by Robb et al (2010) Additionally, the work by Fairlie, Robb, and Robinson (2020) examines significant racial disparities in access to capital for minority-owned startups, revealing that black entrepreneurs often face more challenges in securing funding compared to their white counterparts, which impacts their business growth and sustainability.

Rubin, D B (1976), Inference and missing data Biometrika, 63, 581–592

Sahlman, W A., Stevenson, H H., Roberts, M J., & Bhid´e, A (1999) The Entrepreneurial Venture

Boston, MA: Harvard Business School Press, 2nd edition

Schwab, A., Abrahamson, E., Starbuck, W H., & Fidler, F (2011) Researchers should make thoughtful assessments instead of null-hypothesis significance tests Organization Science, 22(4), 1105-1120

Scott, A J., and Smith, T M F (1973) Survey design, symmetry, and posterior distributions

Journal of the Royal Statistical Society B, 35, 570–60

Scott, M & R Bruce (1987) Five stages of growth in small business Long Range Planning, 20(3), 45–

Serrasqueiro, Z., Leitão, J., & Smallbone, D (2018) Small- and medium-sized enterprises (SME) growth and financing sources: Before and after the financial crisis Journal Of Management &

Shepherd, D.A & Wiklund, J (2006) Success and failures at the research on business failures and learning from it Foundations and Trends in Entrepreneurship, 2(5), 1–35

Smith, A (1776) An Inquiry into the Nature and Causes of the Wealth of Nations London, UK Solow, R., M (1957) Technical Change and the Aggregate Production Function The Review of

StataCorp (2021) Stata: Release 17 Statistical Software College Station, TX: StataCorp LLC

Stiglitz, J (1985) Credit markets and capital control Journal of Money, Credit and Banking, 17(2), 133-

Stiglitz, J.E., & Weiss, A (1981) Credit rationing in markets with imperfect information American

Stockhammer, E (2004) Financialisation and the slowdown of accumulation

Storey D J (1994) Understanding the Small Business Sector London: Routledge

Thompson, S K (2012) Sampling (3 rd ed.) John Wiley & Sons, Inc., Hoboken, New Jersey

Timmons, J A & Spinelli, S (2003) New Venture Creation: Entrepreneurship for the 21st Century (6 th ed.) Boston: McGraw-Hill

Toft, N., Innocent, G T., Gettinby, G., & Reid, S W J (2007) Assessing the convergence of Markov

Chain Monte Carlo methods: An example from evaluation of diagnostic tests in bsence of a gold standard Preventive Veterinary Medicine, 79, 244–256

Trivedi, S R., & Bhattacharya, S (2018) Financial Economy – Evolutions at the Edge of Crise

Routledge, Taylor & Francis Group, London and New York

Ullah, B., and Z Wei (2017) Bank Financing and Firm Growth: Evidence from Transition Economies

Watson, T & N Wilson (2002) Small and Medium Size Enterprise Financing: A Note on Some of the

Empirical Implications of a Pecking Order Journal of Business Finance & Accounting, 29(3-4), 557-578

Wolpert, R L., & K Ickstadt, K (1998) Poisson/gamma random field models for spatial statistics

Biometrika, 85, 251–267 https://doi.org/10.1093/biomet/85.2.251

World Bank (2021) Small and Medium Enterprises (SMEs) https://www.worldbank.org/en/topic/smefinance, [20/9/2021]

World Bank Group (2019) World Bank Group Support for Small and Medium Enterprises: A

Synthesis of Evaluative Findings The world Bank, Washington, D C

World Bank (2008) Finance for All? Policies and Pitfalls in Expanding Access The world Bank,

Wu, J., Song, J., & Zeng, C (2008) An Empirical Evidence of Small Business Financing in China

Yoshino, N & Taghizadeh – Hesary, F (2015) Analysis of Credit Ratings for Small and Medium-Sized

Enterprises: Evidence from Asia Asian Development Review, 32(2), 18–37

Young, A (1992) A Tale of Two Cities: Factor Accumulation and Technical Change in Hong Kong and Singapore In O J Blanchard and S Fischer (eds.), NBER Studies in Macroeconomics Annual, 7, 13-64

Zhang, Z., Scott, J., M., Lau, M., C., K., & Parnell, J., A (2022) A Multi-Level Perspective on Firm

Growth: An Empirical Study of SMEs Journal of Managerial, 34(2), 173-193