INTRODUCTION
The Overview
Since gaining recognition as an economically independent unit in 1998, the number of household businesses in Vietnam has surged The Ministry of Planning and Investment reports that there are over 1.5 million household businesses in the country, providing jobs for more than 3 million workers and contributing approximately 9% to the total social production capacity.
As of October 1, 2016, Vietnam had 4.91 million individual firms employing over 8.2 million workers, marking a significant increase since 1999 Household businesses in Vietnam benefit from simple incorporation processes and tax payment methods, contributing positively to the economy by creating job opportunities and enhancing product diversity Their widespread presence across the country positions these entrepreneurs as vital distribution channels that support trade balance and stimulate local economic development Additionally, household businesses serve as a catalyst for entrepreneurship and market growth, representing a promising area for the establishment of micro, small, and medium enterprises (CIEM, 2017).
Household-scaled businesses often encounter significant limitations in their operational capacity, technology utilization, and management knowledge These challenges can result in reduced labor productivity and overall business efficiency.
This region faces significant challenges in accessing official loans, primarily relying on retained profits and informal credits from friends and family (Pham Van Hong, 2016) Household businesses struggle to secure funding from credit organizations due to an inability to provide adequate collateral or reasonable business plans The Civil Code of 2015 mandates that borrowers must be legal entities, leading to amendments in the State Bank's regulations under Circular No 39/2016 As of March 15, 1977, entities like household businesses and cooperative groups without legal status are ineligible for loans To qualify for borrowing, household businesses must either transform into formal enterprises or have the household head take individual responsibility for debt repayment, resulting in higher interest rates similar to consumer loans.
Microfinance institutions serve as a vital funding source for household businesses by offering small loans, savings services, and non-financial support such as risk management and business guidance In Vietnam, the microfinance landscape comprises three official organizations, approximately 70 semi-formal programs across 23 provinces, and various credit systems aimed primarily at low-income individuals and social welfare beneficiaries Consequently, access to credit for household businesses remains limited Research indicates that microfinance significantly alleviates poverty and enhances living standards, with studies highlighting its positive effects on the revenues of low- and middle-income families However, a comprehensive analysis of microfinance's impact on household businesses is lacking, underscoring the urgent need for a research project focused on "Microfinance and the Development of Household Businesses in Vietnam."
Review of literature
In Vietnam, the definition of household businesses is clarified in the Decree 78/2015 / ND-
In Vietnam, a household business is defined as one owned by individuals or a group of Vietnamese citizens aged 18 and above, who possess full civil capacity, and operates in a single location with fewer than ten employees, taking full responsibility for its assets This model mirrors sole proprietorships found in countries like England, France, Australia, and India, where the owner also serves as the manager and operator, with no distinction between personal and business property rights However, unlike these countries, Vietnamese household businesses can have multiple owners, allowing for a collaborative approach while maintaining small-scale operations that often reflect family characteristics and the potential to hire additional labor.
In Vietnam, household businesses are often categorized as "microbusinesses" or "micro-enterprises," highlighting the significance of microfinance in supporting these small-sized businesses Research indicates that a critical barrier to the growth of micro, small, and medium-sized enterprises (MSMEs) is the lack of access to capital and financial resources (Owualah, 1999; Carpenter, 2001; Anyawwu, 2003; Lawson, 2007) Access to financial services is essential for these businesses, as it provides additional resources for enhancing production capacity and overall productivity (Watson and Everett, 1999) However, many micro-enterprises rely on informal funding sources, such as family and friends, which often fall short of meeting their operational needs (Bhasin and Alepaku, 2001) Furthermore, small businesses face challenges in securing financing from formal institutions due to stringent borrowing requirements, leading to reduced profitability (Khandker et al., 2013).
Microfinance was established to provide low-income individuals with access to essential financial services, such as credit, savings, and insurance, aiming to enhance their incomes and living conditions Numerous empirical studies have demonstrated its effectiveness in alleviating poverty and improving living standards in developing countries While low-income individuals remain the primary focus of microfinance institutions (MFIs), many organizations are now targeting small and micro business owners for sustainable development These business owners can become loyal clients, successfully lifting themselves out of poverty and expanding their enterprises Additionally, new clients may seek financial support to grow their businesses with reduced risks Microfinance serves as a vital resource for small-scale businesses, facilitating capital mobilization and offering non-financial services, including business consulting and training in financial management and entrepreneurial skills.
Empirical research indicates varied impacts of microfinance on small and micro businesses A study by Rahmat et al (2006) in Indonesia, utilizing the ANCOVA model, found that microfinance enhances sales and business scope, although it primarily focused on regional factors Similarly, Xitian Wang (2013) highlighted microfinance's role in boosting sales and profits for household businesses in China Karlan and Valdivia (2006) demonstrated that combining microcredit with business training significantly benefits both lenders and borrowers, resulting in increased revenues and faster loan repayments Conversely, Babajide (2012) employed Pooled OLS regression analysis on a survey of 502 microfinance businesses in Nigeria, concluding that microfinance loans had no impact on business development, recommending improved lending and repayment terms Consistent findings emerged from Olugbenga and Mashigo (2017) in South Africa In India, the government initiated a cooperative loan program linking banks and microfinance institutions, offering higher lending limits The World Bank assessed this initiative, revealing enhancements in labor productivity, production facilities, working capital management, employment opportunities, and overall business confidence among owners.
- To systematize theoretical matters in credit stemming from microfinance institutions (MFIs) and the development of household businesses
- To assess the impact of microcredit on the development of household businesses in Vietnam
- To make recommendations to improve the effectiveness of microcredit for household businesses in Vietnam
4 The researched subjects and fields
The delimitation
- Research stage are aimed from 2013 to 2017.
The disposition
Apart from the introduction, conclusion and reference, the structure of the topic is divided into 4 chapters:
- Basic theory of Credit from Microfinance Institutions and Development of Household businesses
- Methodology of the research „Microfinance Institutions on the Development of Household businesses in Vietnam‟
- Empirical Finding and Analysis of the research „Microfinance Institutions on the Development of Household businesses in Vietnam‟
- Recommendations for improving the effectiveness of credit from microfinance institutions for the development of household businesses in Vietnam.
THEORITICAL FRAMEWORK
Overview of household business and household business development
In Vietnam, the concept of household business is clarified in Article 66 of the Government's Decree No 78/2015 / ND-CP guiding the business registration procedures of Enterprise Law
In 2014, Vietnamese businesses, whether owned by individuals or families, were required to register at a single location, employ fewer than ten staff members, and hold full responsibility for their business operations This regulation specifically applies to Vietnamese citizens over the age of 18 with full civil capacity.
Household businesses with ten or more employees must adhere to specific regulations for registration, with the owner being the sole beneficiary of profits and responsible for all financial obligations to the state If the business is owned by a household or a group, a representative must be appointed for registration purposes, who will act on behalf of the household but is not individually liable for other members Profits and risks will be allocated among members based on their contributions, efforts, and agreements.
In terms of size of labor, household businesses in Vietnam may be classified as
"microbusiness" / "micro-enterprise", meaning the micro-sized type of enterprises, which is divided on the basis of labor size or sales revenue
2.2 Characteristics and role of household business
2.2.1 Characteristics of production and business activities of household businesses
In terms of production activities, household businesses usually have the following characteristics
Household businesses typically operate within a limited scope, targeting a small local market for their products and services Globally, sole-owner businesses tend to employ fewer workers due to their small-scale nature In Vietnam, this characteristic is influenced by legal restrictions, which permit household businesses to register at only one location and employ a maximum of 10 employees.
Household businesses typically feature a straightforward management structure where the owner also serves as the worker and manager This arrangement facilitates quick decision-making; however, its effectiveness relies on the owner's management skills, market awareness, and experience Additionally, the lack of specialization means that employees often juggle multiple roles, contributing to the overall simplicity of the business Consequently, the skill level of labor in household enterprises tends to be lower compared to larger entrepreneurial ventures, reflecting the more straightforward nature of these operations.
Household businesses offer flexibility and adaptability to market changes due to their small-scale operations and low entry costs However, the head householder's approach to capturing market opportunities can often be spontaneous, lacking a clear business strategy or orientation, which may result in unmet market demand.
Household businesses often face challenges due to low technology application, resulting in a reliance on manual labor and outdated production machinery This situation contributes to decreased labor productivity and hampers their ability to meet the demands of various market segments.
2.2.2 The role of household businesses in the economy
Household businesses are a prevalent economic sector globally, poised to generate significant employment opportunities and contribute to GDP and economic growth This dynamic sector showcases great potential through its diverse range of products and services, fulfilling societal needs and acting as a supportive satellite for broader economic activities.
Household businesses play a vital role in the economic restructuring of rural areas by generating jobs and reducing poverty through diverse industrial fields They attract a significant labor force, produce a variety of goods and services for both consumption and export, and enhance state budget revenues These enterprises contribute to a more dynamic and adaptable economy by tapping into the latent resources of the local population Furthermore, household businesses have the potential to revitalize traditional trades by leveraging management expertise and production techniques passed down through generations, thereby preserving and advancing the ethnic cultural products of the region.
2.3 Factors affecting the development of household businesses
The development of micro, small, and medium-sized businesses is significantly influenced by the entrepreneurial capacity and perspective of the business owner This capacity shapes their choice of management strategies and methods Previous studies indicate that various characteristics of the owner play a crucial role in shaping their entrepreneurial attitude and capabilities.
Research indicates that banks often impose stricter lending conditions on women seeking collateral for business loans, which hinders their borrowing capacity and business growth (Riding & Swift, 1990) Furthermore, women are generally more focused on family responsibilities, leading to less motivation for economic development and business expansion (Brush, 1992).
A study conducted in 1994 revealed that having a female owner for a registered business did not significantly contribute to its expansion, yet it did not adversely impact the business's sustainability.
Younger entrepreneurs exhibit greater motivation and a willingness to take risks in order to grow their businesses, driven by a strong need to increase their income for family support However, they face challenges such as limited financial resources, networking opportunities, and business experience compared to their older counterparts Empirical research highlights the significant impact of age on entrepreneurial development (Boswell, 1973; Davidsson, 1991).
The educational level of a household head significantly influences their business success, encompassing essential attributes such as knowledge, skills, motivation, self-confidence, problem-solving abilities, commitment, and self-discipline Individuals with higher education are better equipped to navigate business challenges and seize opportunities, which positively impacts the growth of their enterprises Research by Cooper et al (1992, 1994) indicates a strong correlation between an entrepreneur's educational background and their performance, as well as the sustainability and expansion of their business Additionally, the willingness to embrace risks can enhance their capacity to mobilize and access necessary resources for business development (Gundry and Welsch, 1997).
Research indicates that a household's business experience significantly influences growth rates Birch (1987) found that established small-scale businesses typically experience faster growth compared to newly formed ones Conversely, Evans (1986) revealed that for businesses with fewer than 25 employees, growth rates tend to decline over time, while those with more than 25 employees show the opposite trend.
The legal status of a business significantly influences its development, as highlighted by Dietmar et al (1998) Different legal structures determine taxation responsibilities, capital-raising capabilities, and employer accountability Additionally, certain business types, particularly small and medium-sized enterprises, may benefit from government support, tax incentives, and loans.
The impact of credit from microfinance institutions on the development of household
Research indicates that insufficient business capital and challenges in obtaining financing are significant barriers to the growth of micro, small, and medium enterprises.
Access to financial services is crucial for micro firms to enhance their capacity and productivity (Owualah, 1999; Carpenter, 2001; Anyawwu, 2003; Lawson, 2007; Watson and Everett, 1999) These businesses often rely on unofficial sources like family and friends for working capital, which frequently fall short of their needs (Bhasin and Alepaku, 2001) The challenges in accessing formal finance hinder small businesses from meeting bank borrowing criteria, ultimately impacting their sales and profitability (Khandker et al., 2013).
Microfinance was established to provide low-income individuals with access to essential financial services such as credit, savings, insurance, and remittances, along with various non-financial services This initiative aims to enhance their income and improve their overall living conditions.
Microfinance has proven effective in alleviating poverty and enhancing living standards in developing countries, as evidenced by numerous empirical studies While low-income individuals remain the primary focus of microfinance institutions (MFIs), there is a growing trend towards supporting small and micro business owners for sustainable development These business clients often become long-term, loyal customers who have successfully moved beyond the poverty line and scaled their operations Additionally, new clients can access the necessary capital for their ventures, leading to increased income and reduced risk.
Microfinance serves as a vital resource for small-scale businesses seeking to secure capital, while also offering essential non-financial services such as business consulting and training in financial management and entrepreneurial skills for grassroots entrepreneurs.
Microfinance institutions (MFIs) play a crucial role in enhancing household businesses by offering micro-credit that provides essential working capital and investment for improving production capacity This includes funding for technology and production means Furthermore, MFIs also offer training in business skills and financial management for household heads, which enhances human resource capital, ultimately resulting in increased sales, profits, and productivity.
International experience to improve the efficiency of microcredit for household business development
4.1 The successful practice of microcredit for household businesses development in Malaysia
In Malaysia, the success of poverty reduction is intricately tied to the effectiveness of microfinance, particularly through microcredit initiatives This led to the establishment of Amanah Ikhtiar Malaysia (AIM) in 1987, inspired by the Grameen Bank model, which emphasizes extensive credit distribution to enhance the incomes of the impoverished AIM categorizes individuals into three groups based on income levels: low-income earners (earning $670/month), the poor (earning below $269/month), and those in extreme poverty (earning below $150/month) The program focuses on assisting individuals facing significant challenges, enabling them to start their own businesses and gradually rise above poverty.
The AIM model provides micro credits at various levels, starting with interest-free loans that require weekly repayments to help households develop business plans in livestock or farming Upon full repayment of the initial loan, borrowers become eligible for higher-value credits, which come with increased interest rates The highest-level loans can range from RM5,000 to RM100, facilitating further business growth.
This innovative approach addresses key challenges in micro-credit by fostering group dynamics among individuals with similar circumstances, encouraging shared responsibilities and benefits It enhances self-monitoring and evaluation for credit officers while promoting commitment among members, which intensifies participation and motivates peer support The implementation of a weekly monitoring system and tiered credit packages enables microfinance institutions to effectively resolve customer issues, support income and business development, and reduce the risk of negative debts.
Table 1: AIM Micro Credit Products
The initial loan offered to customers featured minimal interest rates, approximately 0%, serving as an introductory package designed to provide experience and support prior to accessing subsequent loan options.
'I-Srikandi' This loan is issued after the first loan The value of the loan will be determined based on the success of the first "I-Mesra"
Short-term loans Flexible repayments can be made in person, on a weekly, monthly or one-off basis
A special support package for those who do not reach the expected level of success for various reasons such as failure of business projects, natural disasters, or health problems
The model's outcomes are highly positive, evaluated based on three key criteria: access to finance for household businesses, the financial sustainability of loans, and additional impacts on customers Research by Nawai & Bashir (2006) indicates that AIM has successfully provided micro-credit through 69 branches and nearly 4,000 facilities across the nation.
RM 1.02 billion for nearly 150,000 customers, Credit growth rates over the past 10 years has reached a staggering 150 times (from RM 890,000 in 1990 to RM 150,000,000 in 2003) Compulsory savings, along with the solid development of financial capabilities and business capabilities, have been proven as effective on the target of maintaining sustainably the project, with the increasing rate of 73.6 % of customer's income compared to the starting point
Analysing of the success of AIM has helped to draw important lessons for the development of microfinance to grow household businesses in Vietnam:
- Firstly, the classification and assessment of demographic characteristics is very important, based on the characteristics of micro credit customers who are prone to behave by regional and cultural criterium
Understanding the social sector is crucial for the microfinance industry, as elements like education, healthcare, clean water access, electricity provision, and infrastructure significantly impact the ability to alleviate poverty for individual households.
Implementing a weekly loan monitoring system is crucial for microfinance institutions This approach, combined with a structured hierarchy of credit packages, helps address customer challenges, enhances income opportunities, and boosts business efficiency Additionally, it plays a vital role in reducing the risk of bad debts.
Microfinance requires careful regulation and restructuring of loan terms to enhance the financial skills of individual households Additionally, microfinance institutions need substantial support from the government through effective public policies to ensure sustainable growth The accessibility of microcredit plays a significant role in boosting a country's overall GDP growth rate.
METHODOLOGY OF THE RESEARCH
Data collection
The empirical research utilized primary data sources gathered through survey questionnaires distributed across three provinces in Vietnam: Bac Giang, Vinh Phuc, and Phu Yen, as well as Binh Thuan, Giang Thuan, Binh Duong, and Ho Chi Minh City.
Between 2013 and 2017, a comprehensive survey was conducted in Ho Chi Minh and selected provinces to analyze microcredit usage among individual household businesses across diverse regions with varying characteristics and development levels The research included both questionnaires and in-depth interviews with households in specific communes and wards of two Northern provinces, aiming to gather essential data on microfinance activities and to understand the perspectives and aspirations of household businesses regarding micro-loans.
The total vote count reached 320, with 40 votes allocated per province across two districts Out of the recorded 235 votes, 171 were deemed valid and utilized in the empirical model The questionnaire was structured around key themes to gather relevant data.
This article provides essential background information on household heads and their businesses, focusing on key indicators such as gender, age, and education level of the household head It also examines various business lines, the size of the labor force, and important financial metrics including turnover and profits, as well as the material facilities utilized by the household.
- Micro credit information: Include figures on the maintenance level of household businesses with microfinance, size of loan, term of loan
- Poll: Include questions on the level of household business on microfinance, credit procedures, loan amounts and expected interest rates
Table 2: Characteristics of the sample
1 Sex of the household head
2 Education level of household head
Not graduated from primary school 15
Research variables
The model test investigates the impact of microcredit on the growth of individual household businesses, focusing on key indicators such as business profits and labor productivity (Williams et al., 2016; Babajide).
Productivity = Turnover (by year) / number of employees in the household in the year
The study focuses on the profit and labor productivity of household businesses as the dependent variable The primary explanatory variable is microcredit, quantified as the amount of household borrowing in millions of Vietnam Dong.
To effectively assess the impact of microfinance on household business development, it is essential to control for various influencing factors, such as the human resources of the household, including the age, gender, and education level of the household head (La Porte & Schleifer, 2014) Additionally, industry-specific factors, including labor size, business lines, facilities, and operational areas, must be considered (Nabar & Yan, 2016) The article also highlights regional variables that reflect external conditions affecting business skills training for household heads, specifically examining their participation in training programs offered by microfinance organizations.
Based on the analysis above, we present two models as follows:
Profit = * microcredit + * training + * age + * sex + * education + * scale + * career + * infrastructure + * region + ( * region1 +
Performance = * microcredit + * training + * age + * sex + * education + * career + * infrastructure + * region + ( * region1 + * region_
Table 3: Description variable and control variable in the model
Continuous variable: VND million/year +
Dummy variable: 1 = Getting involved in business skills training courses organized by MFIs
3 Ages of the head householder Continuous variable +
4 Sex off the head householder Dummy variable: 1 = Male; 2 = Female -
5 Education level of the head householder
1= Illiterate 2= Not graduated from primary school 3= Primary school Graduator
4= Secondary school Graduator 5= High School Graduator
6 Working scale Continuous variable: person +
7 Main Professionals- Dummy variable: 1 = Agriculture
Dummy variable: Total points of the following factors:
+ Roof house / floor /concrete house: 1 + Temporary house: 2
- Electricity: grid electricity: 1; Electric explosion machine: 2
- Machinery, means of production, fixed assets:
Use three dummy variables: northern, central, southern (each variable in turn receives values 0 and 1, which are combined in pairs to indicate the presence of each domain)
Central = 0 Northern ( Bac Giang, Vinh Phuc)
Central (Phu Yen, Dac Nong, Binh Thuan, Giang Thuan)
Central = 0 Southern (Binh Duong, Ho Chi Minh)
Data Analasys
The study analyzed data from 171 microfinance clients, specifically household business owners, covering the years 2013 to 2017 This data is presented in a structured table format, showcasing the balance sheets of the customers over the specified time series.
3.1 Basic estimates with table data
Table data plays a crucial role in research across microeconomics and macroeconomics, allowing for the analysis of household and business units as well as broader geographical regions It encompasses two main types: cross-sectional data, which captures variable values for sample units at a single point in time, and time series data, which observes variables over time Combining these data types enhances the analysis of economic relationships, particularly in examining variations following events and differences among study groups There are two primary structures of table data: balanced sheets and unbalanced tables, with the latter potentially limiting estimation accuracy Our research focuses on balanced data from households that have borrowed microfinance loans over time, leveraging the advantages of panel data These include increased information and variability, reduced variable multipliers, and enhanced observational degrees of freedom, leading to robust, unbiased estimates Moreover, the heterogeneous characteristics of different households can be effectively accounted for in estimation techniques, making panel data analysis more effective than solely relying on cross-sectional or time series data.
We assume that the observation sample includes N(number) household(s), in T(number) year(s), so the table data will include N x T observations The general regression equation is written as:
Where: Y: Vector expressing sets of dependent variables
X: Vector expressing sets of independent variables Z: The vector of variables does not change over time, representing the characteristics of each household businesses i: household business index I (i = 1, N) t: the indicator shows observations by time (t = 1, T) : error
The basic estimation methods for regression with the table data are: Pooled regression model, Fixed effect model (FEM) and Random effect model (REM)
The pooled regression model, which utilizes ordinary least squares (OLS) estimation, treats table data as a uniform set of observations, independent of year or country This approach assumes that households share similar characteristics, leading to a simplified general equation.
However, strong assumptions of OLS are often difficult to meet in practice
The Fixed Effects Model (FEM) analyzes the impact of fixed factors by utilizing dummy variables, similar to Ordinary Least Squares (OLS) regression This model can be structured based on household characteristics, time periods, or both, but it does reduce the degrees of freedom, particularly when a large number of dummy variables are included The FEM equation effectively captures the relationships among these fixed factors.
In there, αi represents the difference in logistic regression for each year or household businesses
The Random Effect Model (REM) accounts for the unique differences among households that influence overall patterns By incorporating variations in specific household business conditions within the random errors, the model effectively captures these distinctions.
Where ui is the difference in y- intercep, ui and εit are random quantities
The selection of one of the three logistic regression models is determined by the variability observed within each household and its correlation with the independent variable in the model.
- To compare the pooled regression model and FEM: after estimating with FEM, we use the F test to test the hypotheses: H0: α1 = α2 = α3 = = αN = α
If the result refutes H0, FEM should be chosen
To compare between FEM and REM, we used the Hausman test (Hausman, 1978) for the FEM and REM estimations with the hypotheses: H0: Cov (xit, ui) = 0
If the result is not negative in H0, it means that the REM and FEM estimates are stable, but only REM is effective
To compare the pooled regression model and REM: after estimating REM, test hypotheses here is that: H0: = 0
In case of the rejection of H0, the REM estimate is more effective
After selecting the most suitable model of the three models, the topic continues to test assumptions about autocorrelation and changes in variance
3.3 Self-correlation testing and changeable variance
While data tables offer significant advantages, they also introduce challenges during the estimation process due to varying observations from different household businesses, which can lead to changing variance Additionally, time series data may encounter autocorrelation issues To identify these problems, appropriate tests were conducted using Stata software, with hypotheses set for no changed variances and no first-order correlations If these hypotheses are rejected, it indicates the presence of variance changes and self-correlation within the model To address these issues, FGLS regression is applied to the data panel, following a methodology similar to that of Ai Enman, Chinn, and Ito (2010).
In classical linear regression, a key assumption is that the error terms have constant variance and are uncorrelated, indicating no autocorrelation When these assumptions are violated, the variability in autocovariance and self-dependence can lead to unbiased regression coefficients estimated by the least squares method, but they may no longer be the most efficient.
The GFT (Generalized Least Squares) method addresses its limitations by assuming a fully defined model, where the variance of errors differs across target groups while remaining constant within each object range.
GLS provides consistent and asymptotic estimates while enabling the correction of autocorrelation and variance changes in regression models using tabular data.
EMPIRICAL FINDINGS AND ANALYSIS
Pearson correlation matrix
The correlation coefficient (r) is a key statistical measure that evaluates the relationship between two variables, x and y Ranging from -1 to 1, a correlation coefficient of 0 indicates no relationship between the variables, while values close to -1 or 1 signify a strong correlation A negative correlation coefficient suggests an inverse relationship between the variables.
In statistical analysis, a negative correlation indicates that as one variable (x) increases, the other variable (y) decreases, and conversely, when x decreases, y increases Conversely, a positive correlation suggests that when x increases, y also increases, and when x decreases, y decreases as well.
The research team employed the Pearson correlation coefficient to assess the linear relationships among the independent variables in their model A strong correlation, indicated by a coefficient close to 1 or -1, would signal potential issues with multi-collinearity in regression analysis However, the correlation matrix analysis revealed no pairs of independent variables exhibiting strong correlations, suggesting a lower likelihood of multi-collinearity within the model This indicates that the independence of the variables is preserved.
Microcredit Trainning Age Sex Education Scale Career Infrastructure Region North Central
Central 0.1736 -0.5208 -0.0809 -0.1319 0.0119 -0.1130 0.2568 0.0971 -0.1084 -0.5041 1.0000 with the dependent variable „profit‟ and the model (2) with dependent variable
„productivity‟ to choose between FEM regression and REM
Table 6: Hausman test results with model (1)
Table 7: Hausman test results with model (2) infrastructure scale infrastructure
The test results indicate a p-value of less than 0.05, demonstrating that the Fixed Effects Model (FEM) outperforms the Random Effects Model (REM) Additionally, the Wald test was employed to assess the variance across entities within the REM framework.
Table 8: Results of the variance test
However, the results of the Wald test showed that p-value F value of less than 0.05 indicates the presence of autocorrelation in the model As shown in Table 2.9, model (1) exhibits autocorrelation, whereas model (2) does not.
Table 9: Self-correlation test results
The author employs the GLS regression method to achieve asymptotic estimation, effectively addressing autocorrelation and variance issues present in regression models utilizing panel data.
4 Model results by GLS regression
The study analyzed 11 explanatory variables in model (1), finding nine with significant coefficients ranging from 1-10% In contrast, model (2) revealed only seven variables with significant coefficients Notably, the regression coefficient for the microfinance variable (microcredit) was 0.584, which was statistically significant at the 1% level, aligning with the authors' expectations This indicates that an increase of 1 million in microfinance loans would result in a profit increase of 0.58 million per year for household businesses.
In model (2), each million VND of microloans correlates with an increase of 0.74 million VND in annual labor productivity for households, indicating a positive effect of microfinance on business outcomes However, the low value of current microcredit, primarily under VND 30 million, suggests limitations in its impact The survey revealed that while microcredit significantly contributes to working capital for household businesses, it does not substantially assist in acquiring fixed assets or advanced technology Most households relied on personal funds or loans from family and friends, often using land or homes as collateral, to invest in fixed assets rather than utilizing microfinance for such purposes.
The article introduces the "training" variable to examine how Microfinance Organizations (MFOs) deliver business production skills training to their clients, which impacts performance However, the findings from both models indicate no statistically significant effect on the profitability and labor productivity of household businesses.
Table 10: Results of the analysis of the effect of microcredit on the profitability of household businesses
Number of observations= 736 Number of groups = 168 Prob>chi 2 = 0.00
Table 11: Results of the analysis of the effect of microcredit on labor productivity of household business
Number of observations = 736 Number of groups = 168 Prob>chi 2 = 0.00
In the analysis of household head variables, model (1) reveals that the age of the household head positively influences business profit, with a regression coefficient of 0.88, indicating that each additional year in age correlates with an increase of 0.88 million VND in annual profit at a significance level of 1% However, model (2 shows that age does not significantly impact household productivity Additionally, the gender of the household head affects profitability, with male heads generating an average of 7.9 million VND more per year than their female counterparts, although gender does not significantly influence household labor productivity at the 10% level.
The regression analysis revealed that the industry variables had significant coefficients of -24.5 and -63.73, indicating that non-agricultural household businesses are more effective in utilizing microfinance loans compared to agricultural households Specifically, non-agricultural households achieve an annual profit exceeding 24.5 million VND, with labor productivity surpassing 63.73 million VND per year In contrast, the facility variables did not demonstrate any statistically significant effects on the dependent variables.
A significant regional variation was observed in model (1) with a regression coefficient of -12.01, indicating that urban households are expected to generate over VND 12.01 million annually from microfinance compared to their rural counterparts However, this variable lacks statistical significance in model (2), and there is no notable difference in household labor productivity between urban and rural areas.
The regression coefficients for regional dummy variables indicate that the North has a coefficient of -35.58 and the central region has a coefficient of -41.93, both significant at the 5% level These values were derived from a regression model where the dependent variable is "profit," highlighting the impact of regional differences on profitability in the surveyed domains.
Model results by GLS regression
The study analyzed 11 explanatory variables and found that nine exhibited significant coefficients between 1-10% in model (1), while model (2) revealed that only seven variables were statistically significant Notably, the regression coefficient for the microfinance variable (microcredit) was 0.584, which is statistically significant at the 1% level and aligns with the authors' expectations This indicates that for every 1 million increase in microfinance loans, household business profits are projected to rise by 0.58 million annually.
In model (2), each million VND of micro loans increases household labor productivity by 0.74 million VND annually, indicating a positive impact of microfinance on household business performance However, the low value of microcredit, primarily under VND 30 million, limits its effectiveness The survey revealed that microcredit mainly provides working capital for household businesses, rather than facilitating the purchase of fixed assets or advanced technology Most households relied on personal funds or loans from family and friends to invest in fixed assets, with few utilizing microfinance for this purpose.
The article introduces the "training" variable to examine how Microfinance Institutions (MFOs) offer business production skills training to customers, which impacts their performance However, the findings from both models indicate that there is no statistically significant effect on the profitability or labor productivity of household businesses.
Table 10: Results of the analysis of the effect of microcredit on the profitability of household businesses
Number of observations= 736 Number of groups = 168 Prob>chi 2 = 0.00
Table 11: Results of the analysis of the effect of microcredit on labor productivity of household business
Number of observations = 736 Number of groups = 168 Prob>chi 2 = 0.00
In the analysis of household head variables, model (1) revealed a significant regression coefficient of 0.88 for age, indicating that for each additional year in age, household business profits increase by 0.88 million VND annually However, model (2 showed that age did not significantly impact household productivity Additionally, the gender of the household head had a notable effect on business profitability at the 10% level, with male heads generating an average of 7.9 million VND more per year compared to female heads, although gender did not significantly influence household labor productivity.
The regression analysis revealed that the industry variables had significant coefficients of -24.5 and -63.73, aligning with the author's expectations This indicates that household businesses in the non-agricultural sector benefit more from microfinance loans compared to agricultural households, with non-agricultural households achieving an annual profit exceeding 24.5 million VND and demonstrating higher labor productivity of over 63.73 million VND per year Conversely, the facility variables did not exhibit statistically significant effects on the dependent variables.
In model (1), regional variation showed a statistically significant impact at the 5% level, with a regression coefficient of -12.01, indicating that urban households are expected to generate over VND 12.01 million more annually than rural households when accessing microfinance However, in model (2), this variable lost its statistical significance Additionally, there is no notable difference in household labor productivity between urban and rural areas.
In the regression analysis, the coefficients for regional dummy variables indicate that the North region has a coefficient of -35.58, while the Central region shows a coefficient of -41.93, both significant at the 5% level When evaluating the "private block" for the surveyed domains using profit as the dependent variable, the results reveal these notable regional disparities.
The analysis reveals that microcredit significantly enhances the performance of household businesses across different regions, with southern household businesses demonstrating the highest effectiveness, followed by those in the northern region, while central household businesses show the least performance.
Household businesses in the North of Vietnam, on average, borrowed microfinance to achieve an annual profit of VND 35.58 million, while those in the Central region reported a profitability rate of less than VND 41.93 million per year This trend aligns with the varying levels of economic development across the surveyed provinces and cities Notably, Ho Chi Minh City and Binh Duong in the South exhibit higher development levels compared to the regions surveyed in the North and Central areas of Vietnam.
RECOMMENDATIONS
Recommended to the Government
To begin with, we must continue to study, supplement and improve the legal framework to support the development of microcredit for household businesses
In June 2017, the Prime Minister signed Decision No 20/2017/QD-TTg, which established regulations for microfinance programs and projects conducted by political and socio-political organizations, as well as non-governmental organizations, effective from August 1, 2017 This decision aims to enhance the legal framework for microfinance in Vietnam, promoting the diversification of organizations and expanding microfinance products It introduces various fundraising methods, including compulsory and voluntary savings deposits from clients, while limiting voluntary savings to 30% of total allocated funds and capping loans to individuals at 50 million VND Additionally, the decision emphasizes the autonomy and accountability of lending practices, alongside regulations regarding the capacity of microfinance clients, ensuring effective loan utilization.
The regression study in Chapter 2 reveals that an increase of 1 million VND in microfinance leads to a profit rise of 0.58 million VND per year and boosts household labor productivity by 0.74 million VND annually This indicates that microfinance loans positively influence the business performance and productivity of household enterprises; however, the impact is limited This limitation can be attributed to the relatively low value of microcredit loans, which primarily serve to supplement working capital rather than enabling household businesses to invest in essential fixed assets and production machinery.
Most surveyed households initially relied on their own savings or funds from family and friends, as well as mortgaging land or property, to secure bank loans for investing in fixed assets Additionally, only a small number of households utilized microfinance loans to further enhance their production and business facilities.
To stimulate household economic development, the government should implement a microfinance initiative that offers tailored loan programs for household businesses, addressing their capital needs This program must include diverse quotas that cater to various client demographics, such as household type, region, gender, and age of the household head.
The State must implement a comprehensive mechanism and policy to support individual household businesses, as current incentives primarily benefit catering enterprises Despite existing frameworks for private economic development, the lack of targeted support for household businesses hampers their growth Additionally, many local management bodies face limitations, including insufficient professionalism among officials, which further complicates the operational challenges faced by individual household businesses.
Recommendations for microfinance institutions
To create an effective loan model for microfinance institutions (MFIs) in Vietnam, it is essential to tailor approaches to the socio-cultural characteristics of each locality While many MFIs have successfully adopted global microfinance models, some have faced challenges and failures Therefore, it is crucial for MFIs to conduct thorough market research and understand the cultural and social dynamics of their specific regions A one-size-fits-all lending model is not viable; instead, loan strategies must be customized to meet the unique needs of customers in different areas.
Large-scale microfinance institutions (MFIs) face challenges in aligning their lending models with diverse local cultures across various regions The presence of multiple loan models can complicate management and operational procedures Therefore, ongoing research is essential to refine lending models, ensuring they develop core processes and basic standards effectively The successful implementation of these models must consider the unique socio-cultural characteristics of each locality.
To enhance borrowers' willingness to repay microcredit loans, it is crucial to strengthen incentive measures, particularly given the lack of collateral in these loans Microfinance institutions (MFIs) in Vietnam have already implemented strategies like group loans and gradual loan increases to encourage repayment However, market pressures from competing credit organizations and financial companies have made it more challenging for borrowers to access capital, even at high interest rates This situation may lead to a decline in borrowers' sense of responsibility regarding capital use and repayment To ensure safety and improve lending effectiveness, MFIs should offer meaningful incentives, such as increased interest rates and larger loan amounts for clients with strong credit histories The design of these dynamic incentives must be market-driven and sufficiently attractive to capture borrowers' attention.
To enhance the effectiveness of microfinance institutions (MFIs), it is crucial to strengthen the role of savings alongside lending activities Savings serve as collateral, increasing borrowers' repayment willingness Despite various voluntary and compulsory savings initiatives by Vietnamese multiformal organizations, the average savings per customer remains low, limiting their potential as valuable loan assets Therefore, it is essential to improve the quality and efficiency of savings activities in tandem with lending Additionally, diversifying and tailoring savings products to meet the specific needs of different customer segments based on locality, industry, and cash flow is vital Making savings products attractive will help consumers view saving as a beneficial practice rather than merely a prerequisite for accessing microfinance loans.
To support household businesses, it is essential to simplify loan procedures, making it easier for them to access financing Loan policies should be tailored to the unique needs of this sector, allowing for flexible borrowing periods By doing so, new household businesses can obtain micro-capital to enhance production, adopt innovative technologies, and improve operational efficiency.
Implementing a weekly loan monitoring system and creating structured credit packages are essential for microfinance institutions to effectively address customer challenges This approach not only promotes customer support and income growth but also enhances business efficiency while minimizing the risk of bad debts.
Micro-credit should be regulated and restructured with reasonable loan terms to help individual households enhance their loan management skills Additionally, microfinance institutions require substantial support from the government through appropriate public policies to ensure sustainable growth Furthermore, the availability of micro-credit significantly contributes to a country's overall GDP growth.
The advancement of databases and expertise in microcredit has significantly contributed to the growth of household businesses through microloans It is essential to enhance the processes of information storage and effectiveness measurement, involving not only banks but also their suppliers for comprehensive assessment Furthermore, clarifying various service levels will provide a holistic understanding of loan effectiveness Lastly, implementing flexible lending policies that accommodate diverse customer reviews and mortgage documentation can alleviate legal burdens and reduce administrative costs for non-registered business forms.
To enhance the effectiveness of household businesses, it is essential to prioritize social communication, ensuring they comprehend the significance of training and the necessary training content requirements.
A study involving 171 household businesses across eight provinces in North, Central, and South regions reveals that microfinance institutions (MFIs) offer skill training and business management courses to enhance loan utilization and improve production efficiency However, the impact on profitability and labor productivity remains minimal, largely due to the low participation rates in training programs This limited engagement is attributed to misconceptions about the value of training and the inadequacy of MFI training content and methods in meeting the specific needs of household businesses.
Recommended for household businesses
In the context of economic integration, small-scale household businesses in Vietnam face significant challenges in competition due to their lack of linkages To enhance their competitiveness, it is crucial to foster connections between individual household businesses, professional associations, and the broader market Furthermore, the government should provide adequate support to these businesses, facilitating their transition to larger-scale operations and ensuring access to ample financial resources.
To enhance the performance of individual household businesses, it is crucial to shift traditional mindsets and quickly adopt improved financial management skills and tools Professional financial practices enable better investment decisions, risk assessment, and the development of effective business and marketing strategies, facilitating market expansion Additionally, it is essential to address financial policy barriers, implement measures for capital raising, and modernize financial management methods to optimize the use of resources Urgent improvements in economic efficiency are necessary for all household businesses in this sector.
According to AIM's model, micro credits are structured in tiers, starting with interest-free loans that require weekly repayments to help households develop business plans, such as livestock or farming Upon full repayment, borrowers can access higher-value credits at increased interest rates, with top-tier loans ranging from RM5,000 to RM100, equivalent to approximately VND30 to 60 million.
This innovative approach addresses key challenges in micro-credit by fostering a cohesive community model where individuals share responsibilities and benefits It enhances the support for credit officers through self-monitoring and evaluation, promoting active participation among group members Weekly monitoring mechanisms, combined with tailored credit packages, enable microfinance institutions (MFIs) to effectively address customer inquiries and challenges This strategy not only aids in income and business development but also minimizes the risk of bad debts.
To enhance the absorption capacity of household businesses in Vietnam, it is crucial to establish effective coordination among the four key sectors: the State, scientists, enterprises, and farmers Currently, the development of these businesses is characterized by spontaneity and a lack of flexibility, leading to inefficiencies and regional disparities By fostering collaboration and creating value chains in agriculture, all parties can benefit Additionally, developing specialized economic zones tailored to the unique potentials of each region will promote a more specialized and effective agricultural sector.
In today's rapidly evolving economic landscape, enhancing profit and productivity is crucial for every household, particularly for those operating businesses To thrive and expand, household businesses must focus on improving productivity and efficiency, enabling them to invest in and engage with both domestic and international supply chains.
The development of household businesses in Vietnam is significantly influenced by various factors, with microcredit being a key element It not only addresses the financial needs of these businesses but also transforms the mindset of household heads, enhancing their business production and financial management skills This leads to improved investment decisions, better risk assessment, and the formulation of effective business and marketing strategies, ultimately enabling successful access to financial models tailored for individual household enterprises.
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