




































INDIAN JOURNAL OF FINANCE AND BANKING 14(1) (2024), 1-13 

1 

 

                         FINANCE AND BANKING 
                                                             IJFB VOL 14 NO 1 (2024) P-ISSN 2574-6081  E-ISSN 2574-609X     

           Journal homepage: https://www.cribfb.com/journal/index.php/ijfb 

               Published by American Finance & Banking Society, USA 

MICROFINANCE AND WOMEN MICROENTREPRENEURS: KEY 

VARIABLES INFLUENCING SOCIO-ECONOMIC AND     

FINANCIAL SUCCESS          
  

 Gourav Roy (a)1   Popy Rani Sarkar (b)  

 

(a) Lecturer, Bangladesh Institute of Capital Market (BICM), Dhaka, Bangladesh; E-mail: gouravroy.du@gmail.com 
(b)Assistant Director, Bangladesh Export Processing Zones Authority (BEPZA), Prime Minister’s Office, Dhaka, Bangladesh; E-mail: 
popysarkar.du.mgt@gmail.com 

 

 
A R T I C L E I N F O 
 

 

Article History: 
 

Received: 14th May 2024 

Reviewed & Revised: 14th May 

to 25th July 2024 

Accepted: 30th July 2024 

Published: 15th August 2024 

 
Keywords: 

 

Bangladesh, Entrepreneurship, Financial  

Performance, Microenterprise, Microfinance,  

Socio-economic Development, Women  
Empowerment, Women Microentrepreneurs 

 
JEL Classification Codes: 

 

G21, O16, J16, L26 
 

Peer-Review Model:  

 

External peer review was done through  

double-blind method. 
 
 

  

 
A B S T R A C T 
 
Given that Bangladesh has a male to female ratio of almost 49.5:50.5, the contribution of women's 

workforce to GDP is significant, and microfinance has been instrumental in enabling women to initiate 

microenterprises since 1974. Proper investigation of how microfinance can contribute to women's socio-

economic and entrepreneurial financial success is required. This study examines whether microfinance 
impacts the socio-economic development of women microentrepreneurs and whether microfinance 

impacts the financial performance of women-led microenterprises. This primary and secondary 

database-driven mixed-methods study surveyed 273 women-led microentrepreneurs and their 

enterprises across Bangladesh using a homogenous survey questionnaire. To meet the first research 

objective, the study employs primary responses from women microentrepreneurs and uses Ordinary 

Least Squares (OLS) and Ordered Logit (Ologit) regression to analyze the mutual relationship between 

women microentrepreneurs' socio-economic development and the six explanatory variables, including 

four relevant control variables. The study has also used a paired t-test methodology to meet the second 
research objective, comparing the microenterprises’ three years' average net income before and after 

taking microfinance. The results indicate a significant impact of microfinance on the socio-economic 

development of women microentrepreneurs, with all independent variables except Q4IV and the control 

variable Q8CV demonstrating a significant relationship with the dependent variable. Additionally, the 

study confirms a statistically significant relationship between microfinance and the financial 

performance of those microenterprises. The study contributes to the field of research with a mixed-

methods statistical facility to analyze microfinance's impact on both socio-economic and financial 
performance dimensions of women microentrepreneurs using both primary and secondary data. 

 
 

© 2024 by the authors. Licensee American Finance & Banking Society, USA. This article is an open-

access article distributed under the terms and conditions of the Creative Commons Attribution (CC 

BY) license (http://creativecommons.org/licenses/by/4.0/).                           

 

INTRODUCTION 

In 1974, a project named Rural Social Services (RSS) launched the first interest-free and collateral-free microcredit. In the 

late 1970s and early 1980s, certain non-governmental organizations (NGOs) and Grameen Bank initiated microfinance 

services as a demand-driven operation, with the backing of the Government. These services were provided in conjunction 

with their social development initiatives. Microfinance allows opportunities for women to take micro loans for enabling 

access to finance in a socially inclusive way for raising contribution to national income and gross domestic product (GDP). 

In 2023, a total of BDT 2857.57 billion of microcredit has been disbursed which is 5.67% of the GDP (in current amount). 

As 90% of the clients of microfinance institutions (MFIs), registered under Microcredit Regulatory Authority (MRA), are 

women, thus the disbursement of microfinance to women is nearly 5.09% of the total GDP.  

 A study on the perspective of Pakistan was conducted with a data set from 2006 to 2018 where the study found 

that women borrowers’ percentage in microfinance significantly contribute to the financial sustainability of women 

(Maeenuddin et al., 2024). A study at Uganda suggests that enhancing and broadening micro-finance assistance to 

economically disadvantaged and susceptible women in different regions of the country by means of entrepreneurial 

education and training, facilitating access to credit and financial services, and creating market opportunities (Robert, 2024). 

The implementation of microfinance in Bangladesh has resulted in an increase in individuals' incomes, enhanced housing 

and food security, and provided economic empowerment to women, thus promoting entrepreneurship and decision-making. 

Additionally, it has bolstered social solidarity and the growth of communities by promoting economic involvement. 

                                                      
1Corresponding Author: ORCID ID: 0000-0001-9782-9103 

© 2024 by the authors. Hosting by American Finance & Banking Society. Peer review under responsibility of American Finance & Banking Society, USA.  

https://doi.org/10.46281/ijfb.v14i1.2241 
 

To cite this article: Roy, G., & Sarkar, P. R. (2024). MICROFINANCE AND WOMEN MICROENTREPRENEURS: KEY VARIABLES INFLUENCING 

SOCIO-ECONOMIC AND FINANCIAL SUCCESS. Indian Journal of Finance and Banking, 14(1), 1-13. https://doi.org/10.46281/ijfb.v14i1.2241 

https://orcid.org/0000-0001-9782-9103
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/ijfb.v14i1.2241
https://orcid.org/0009-0008-0977-5650


Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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Although facing difficulties, microfinance continues to be essential for alleviating poverty in Bangladesh (Shah, 2024). In 

Afghanistan, the effect of microfinance on women’s empowerment is less than projected; yet, there is evidence of a favorable 

benefit for some women (Hemat & Rahman, 2023). A study in the context of Bihar, India also established that microfinance 

significantly contributes to achieve financial inclusion (Fatima, 2024). 

The scope of the study is centered on primary data collected from a sample of women microentrepreneurs around 

Bangladesh. As the bigger part of microfinance (90%) is drawn by the women, the study only focuses on the women clients 

of microfinance. It includes those women clients who have utilized the microfinance in establishing an enterprise. 

Microfinance has two dimensions; one is socio-economic development and the other is financial performance of enterprises. 

Thus, the study scopes both of the dimensions by blending primary and secondary data from the same respondents. 

The study aims to find out whether microfinance is significantly impacting the socio-economic development of the 

women microentrepreneurs. Additionally, using the net income information of their enterprises, the study aims to find out 

whether microfinance significantly impacts the financial performance of those enterprises. 

The novelty of the study consists in utilizing a mixed method analytical research blending primary and secondary 

data where both the socio-economic performance and financial performance of microfinance are evaluated focusing only 

on the women microentrepreneurs. This study contributes the existing field of research by understanding the gender 

dynamics of microfinance, providing policy implications for optimizing microfinance programs for women, offering a 

robust mixed-methodological framework, and implementing a localized, contextual, and evidence-based study. 

The study approaches by reviewing exiting literatures in the given field. Review of literature involves studying the 

theories relevant to microfinance, findings of other studies, determining research gaps, and development of hypothesis. After 

that, the methodology of the study provides roadmaps to conduct the study. After that, results and discussion provide the 

statistical outputs and discussions based on the outputs. A brief finding is provided for summarizing the outputs and 

implications for microfinance society based on research aims. Finally, the study concludes by summarizing the outputs and 

providing shades of possible avenues of further studies.  

 

LITERATURE REVIEW 

Microfinance, a powerful tool for fighting against some major problems, including poverty (Kalla, 2021) and vulnerability 

(Bassem, 2012), in developing countries like Bangladesh, boosts socio-economic development (Al-Amin & Mamun, 2022), 

which is a multidimensional process through which an individual can take control over the matters concerning them for the 

socio-economic betterment of women (Sethy & Jana, 2020). Thus, it amplifies the capability of poor and marginalized 

people to improve their standards of living (Banerjee & Jackson, 2017). 

In the early 1970s, the concept of microfinance was introduced by the economist Muhammad Yunus in Bangladesh 

to encourage women involved in start-ups and entrepreneurship. The famous economist Dr. Mohammad Yunus also 

developed Grameen Bank, which is most probably the largest microcredit organization in the world (Islam et al., 2012), to 

execute his microfinance concept, especially focusing on the poor rural women who are interested in improving their living 

standards and engaging in and expanding their entrepreneurial activities. The study conducted by Akter and Jilu (2020) has 

assessed the success of the microfinance concept through Grameen Bank in Bangladesh. The strategy of self-empowerment 

through micro-finance is successfully being operated in more than 60 countries in the world and it is being observed that 

women's participation in entrepreneurial activities has increased to a greater extent all over the world. 

To make Bangladesh smart, fostering women's entrepreneurship is needed to contribute to national economic 

development. By 2041, Bangladesh is going to transition from a developing country to a middle-income country with the 

joint efforts of men and women who have worked together to implement Vision 2021 and are still working to attain the 

SDGs by 2030. It’s a good point for Bangladesh that women entrepreneurs hold large portions and are actively exploring 

new opportunities in economic participation. Not only in Bangladesh but also in the whole world, microfinance contributes 

to the economy of the country by reducing poverty, creating self-employment, and fostering women's entrepreneurship. In 

both developed and developing countries around the world, microfinance is treated as a viable and best alternative to 

conventional financial and non-financial services. During the global financial crisis of 2008, microfinance gained trust and 

reliability with profound shock-resistant roots (Alimukhamedova, 2014).  

The concept of microfinance, also called microcredit, provides women, especially those from rural areas, with 

affordable financial and non-financial services and opportunities to utilize their own skills, knowledge, and abilities to 

startup businesses, which causes women's empowerment (Nimmi & Ramachandran, 2021). Moreover, it is considered a 

world where all the people, especially marginalized and poor individuals and households, get wide access to affordable 

quality financial services and products, which do not only act as credit but also act as savings, payment services for the 

clients, leasing and micro-insurance (Khavul et al., 2013), and transfer of funds. It performs the function of banking for 

unbanked consumers and entrepreneurs who have little access to regular banks and are not able to provide proper collateral 

to take advantage of financial services (Bassem, 2012). In addition to that, microfinance provides women entrepreneurs with 

proper support and funding to financially contribute to their families (Tandon, 2016), especially in developing countries like 

Bangladesh. Nimmi and Ramachandran (2021) explained that women empowerment through small businesses is particularly 

a specific economic concept that helps women go forward and contribute to their families as well as the economy of 

Bangladesh. 

Microfinance plays a crucial role in women's empowerment through entrepreneurship. Through this, women 

entrepreneurs get financial, social, health, and educational development that ultimately develops their family empowerment. 

A study by Gupta and Meher (2016) explained that microfinance is an effective way to boost women's entrepreneurship by 

providing financial and non-financial services such as small and emergency loan facilities, scholarships, educational and 



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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training programs, medical facilities, etc. to women who are interested in entrepreneurship and small businesses. With 

financial independence through microfinance, women can grow their entrepreneurship and thus gain self-confidence and 

utilize their skills. Thus, the economic empowerment of women through microfinance makes a positive impact on their self-

esteem (Sethy & Jana, 2020) and gains respect for them. 

On the other hand, microfinance evolved as a procedure of financial inclusion for women entrepreneurs (Okesina, 

2021) who are not able to get access to conventional financial services (Chowdhury et al., 2021) such as credit facilities, 

insurance, and some other non-financial services due to perceived gaps in ownership of land and religiosity (Olohunlana et 

al., 2024), gender discrimination, lack of proper collateral, and level of informality (Banerjee et al., 2015) for fostering more 

involvement of women in entrepreneurship (Okesina, 2021). Women's participation in entrepreneurship boosts their 

financial independence, earnings, family income, savings, and also some other household resources (Rehman et al., 2015), 

and microfinance paves the way for a for a smooth and affordable future. According to a study by Bassem (2012), a large 

portion of beneficiaries of microfinance are women who are interested in involving themselves in entrepreneurship and 

other self-employed activities. This gives women self-confidence, social status, and active participation in family decision-

making, the ability to contribute to family and the economy (Degago & Aschale, 2018), and gender equality. Studies show 

that microfinance exerts a deep influence on the socio-economic status, knowledge, skill and ability (KSA) improvement, 

decision-making power, and self-dignity of women involved in self-employment. Addai (2017) shows the notable positive 

relationship between microfinance and the socio-economic development of the self-employed women group (Dame & 

Adisa, 2020), though marital status may affect the mentioned relationship, whereas age and educational level of women 

have no controlling effect. 

In Bangladesh, microfinance is provided by Grameen Bank, which is the largest microfinance bank in Bangladesh 

and is acting as a revolutionary method to eradicate poverty and foster women's entrepreneurship (Islam et al., 2012). The 

microfinance concept and Grameen Bank have contributed so much to rural development, especially women's 

entrepreneurship and empowerment, that in 2006, the Nobel Prize Committee jointly awarded Dr. Muhammad Yunus and 

Grameen Bank for their earnest efforts to reduce poverty in Bangladesh (Islam et al., 2012). Despite all the positive outcomes 

of microfinance, there are some negative outcomes of microfinance on women entrepreneurs’ ability to run their 

entrepreneurial activities. This is supported by (Dumbuya & Munu, 2024; Okesina, 2021). Such as the findings of the study 

conducted by Okesina (2021), it is a small statement that women's engagement with microfinance also has some negative 

outcomes, including increased debt, loan diversion, financial burden, less financial literacy, unjustified deductions, short 

repayment periods, etc. (Dumbuya & Munu, 2024) for women entrepreneurs. Islam et al. (2012) indicate that the high 

interest rate of microcredit sometimes becomes a huge burden for women entrepreneurs and suggest Grameen Bank rethink 

the interest rate and make a smooth way for women entrepreneurs to contribute to their families, society, and the economy 

of Bangladesh. 

Up to the authors’ latest knowledge, in Bangladesh, no research has been done on finding the impact of 

microfinance on women micro-entrepreneurs by conceptualizing a survey questionnaire and knowing directly from them 

about the effectiveness of microfinance in socio-economic development and financial performance of their microenterprises 

simultaneously. In addition to that, up to the authors’ latest knowledge, no research has been done using a mixed method 

set up in this field with updated information till June 2023. These issues have lured the researchers to conduct a study in 

this domain. 

 

Conceptual Framework   

The book, “Banker to the Poor” specifically enlightening microfinance in Bangladesh context (Yunus & Porter, 2008), a 

study by Jayasinghe and Herath (2013) formulated few variables based on what the proxies for variables can be shaped. 

Again, a Women Empowerment Index (WEI) developed in the context of India by Roy et al. (2018) influenced the inclusion 

of variables. Also, studies by Asadullah et al. (2021) and Hashemi et al. (1996) provided different angles of judgments 

regarding microcredit program’s relation to women empowerment. All these have been adjusted and conceptualized in 

Bangladesh by the authors of this study. 

Referring to Figure 1, where a theoretical framework has been generated from theories and relevant studies. 

Women’s microcredit utilization success is reflected in the entrepreneurial success of women taking microcredit. 

Entrepreneurial success is a factor of different types of capital, including financial capital (Elsafty et al., 2020). Access to 

credit encourages entrepreneurial success (Abebe & Kegne, 2023). It’s seen in the study that when financial capital is ample, 

there is a chance of entrepreneurial success. Entrepreneurial success is remarkable when such a microbusiness initiative 

employs other women (Badal, 2010). A study published in Springer focusing on the European Union showed that there 

existed a significant correlation between employment rate and entrepreneurship (Anastasiou et al., 2021). Employment leads 

to higher income and business expansion, which finally provides a better network with stakeholders and MFIs. The MFIs 

consider these successful women micro-entrepreneurs as role models, and finally, the social status of the women micro-

entrepreneurs develops. It is notably true that there should be a positive relationship between good corporate financial 

performance and entrepreneurship that is efficient and successful (Chitimiea et al., 2021). Thus, a better social status is 

blessed to these women micro-entrepreneurs, which consequentially leads to the empowerment of women. As microcredit 

allows opportunities for easy access to capital and all these direct and indirect opportunities that finally link women's 

microcredit entrepreneurship to success, the framework hints at a positive correlation between these variables and women's 

micro-entrepreneurial success. 

 



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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Figure 1. Conceptual Framework on How Microfinance Impacts Socio-economic Development and Financial Performance 

of Women Microentrepreneurs 

 

Hypotheses of the Research    

The study, as of its research objectives, wants to examine various segments of microfinance’s impacts and wants to test two 

hypotheses. Referring to table 1, the alternative hypotheses are denoted in the list with respective test strategies. 

 

Table 1. Hypotheses of the Research 

 
 

Alternative Hypotheses Description of Hypotheses Test Strategies 

H1 There exists a significant relationship between microfinance 
and the socio-economic development of women 

microentrepreneurs. 

Ordinary Least Squares (OLS), and Ordered Logit 
Regression Model. 

H2 There exists a significant relationship between microfinance 
and women-led microenterprises' financial performance. 

Paired t-test 

 

MATERIALS AND METHODS 

Data and Sample Distribution        

The data is the women clients’ information found from the Grameen Bank, Society for Social Service (SSS), and other few 

microfinance institutions (MFIs), and Microcredit Regulatory Authority (MRA). Using sample size estimation formula from 

(1), the sample size has been estimated 273. Cochran (1977) advised the sample size formula. 

 
 

Sample Size n = N * [Z2 * p * (1-p)/e2] / [N – 1 + (Z2 * p * (1-p)/e2] (1) 
 

 

Where, N = population size, e = margin of error (percentage in decimal form), z = Critical value of the normal distribution 

at the required confidence level, and p = sample proportion. Here, 1,33,64,000 is the number of women clients of 

microfinance in Bangladesh till the fiscal year 2022-23. Using z value for 90% confidence interval with 5% margin of error, 

the number of samples is found.  

Socio-economic and financial 
success of women 

microentrepreneurs

Microbusiness's financial success

Easy access to capital Job creation to the unemployed

Higher income and purchase ability
Relative freedom from domination 

in family

Better economic, legal, and political 
network

Better psychological wellbeing



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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Figure 2. Samples Distribution across Bangladesh (As of Divisions of Bangladesh) 

 

Referring to Figure 2, where the sample distribution across the locations has been provided. Figure 2represents 

stratified sampling procedure across the country considering eight divisions of Bangladesh. Basing on MFI’s presence and 

the quantity of women clients, the density of survey has been shaped.  

 

Data Collection    

Data has been collected using survey questionnaire with the women microentrepreneurs. The data questionnaire is enclosed 

in the Appendix-A, where the data has been ordinal data in nature, in a Likert scale of 0 to 4. Also, information on net 

income before taking microfinance loans and net income after taking microfinance loans has been collected for meeting the 

second aim of the research. 

 

Variables Identification, Labels and Justification     

Table 2. Variables Identification, Labels and Justification 

 
 

Variables’ Labels and Types Name of the Variables Justification 

Q1DV: Dependent Variable Economic security and 

Improvement of capital 

From a study of Hashemi et al. (1996), this has been considered proxy for 

socio-economic development of women microentrepreneurs. This variable 
represents that woman have security against economic vulnerability and 

capital enhancement history from microfinance. 

Q1IV: Independent Variable 1 Easy access to capital A study of Roy et al. (2018) considered access to resources as a key 
indicator of women’s socio-economic empowerment. 

Q2IV: Independent Variable 2 Job creation Women from their microenterprises can impact the job creations for others 

which impact the socio-economic development (Sohail, 2014). 

Q3IV: Independent Variable 3 Economic, legal, and political 

network 

A study showed that women’s socio-economic empowerment is impacted 

positively by networking (Mayoux, 1970). Microfinance enables this 

option highly to the women microentrepreneurs. 

Q4IV: Independent Variable 4 Higher income and purchase 
ability 

The ability of women in income and purchase comparing to the past 
represents benefits which impacts socio-economic development (Hashemi 

et al., 1996). 

Q5IV: Independent Variable 5 Better psychological 
wellbeing 

Asadullah et al. (2021) found that better psychological wellbeing is a 
fundamental effect of microfinance that is a social outcome of 

microfinance. 

Q6IV: Independent Variable 6 Relative freedom from 

domination in family 

The access to microfinance has a significant relationship with relative 

freedom from domination in family (Hashemi et al., 1996). 

Q7CV: Control Variable 7 Asset Size The size of the asset can have an impact on the business's growth (Kendo 

& Tchakounte, 2021). The model controls this accordingly. 

Q8CV: Control Variable 8 Location The location of the women-led enterprises may have an impact on what is 
controlled in the model (Kakooza et al., 2023). 

Q9CV: Control Variable 9 Age of the Business The age of the business represents its experience, which might have an 

impact on its growth. That’s why it’s controlled in the model (Gupta et al., 

2013). 

Q10CV: Control Variable 10 Amount of Loan Taken The amount of loan taken from the MFIs or any other government 

organization or bank may have an impact on business growth for what’s 

controlled in the model (Al-Azzam & Parmeter, 2019). 

 

Referring to Table 2, the definition of the variables is provided with proper background or insights with citations. 

As no specific theories are tested in this study, thus, variables are chosen with sincere blend of relevant literatures. 

Dhaka
16%

Chittagong
6%

Mymensingh
17%

Sylhet
6%Barisal

5%

Khulna
9%

Rajshahi
11%

Rangpur
30%

Percentage of 273 Microentrepreneurs 
Surveyed across Divisions

Dhaka Chittagong Mymensingh Sylhet

Barisal Khulna Rajshahi Rangpur



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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Regression Model   

Q1DV= α + β1Q1IV+ β2Q2IV+ β3Q3IV+ β4Q4IV+ β5Q5IV+ β6Q6IV+ β7Q7CV+ β8Q8CV+ β9Q9CV+ β10Q10CV + ε  (2) 

where,  

α The constant 

βi Slope for all the independent variables 

ε Error Terms 

 

Data Analysis Framework 

The study has used STATA (version 18) to analyze the ordinal data series, where the data analysis has been formed in the 

Figure 3. 

 

 
 

Figure 3. Data Analysis Framework 

 

The research has undergone data analysis using this methodology. The steps are described briefly below: 
 

Step 1: The Ordinal level data collected from the respondents is coded in a Likert scale of 0 to 4 (Appendix-A for more 

details). 
 

Step 2: Using STATA, a statistical analysis tool, Cronbach’s Alpha is calculated, which represents the level of reliability 

and validity of the data set. In this stage, all the independent variables and dependent variable are tested by numerous 

questions (Appendix-B) for checking individual Cronbach’s Alpha and basing on omission process, the reliability and 

validity of individual variables is determined, and finally overall Cronbach’s Alpha is found out. 
 

Step 3: Descriptive statistics is calculated to find out the minimum, maximum, mean, and standard deviation of the data set 

for understanding the basic depth and variability of the data dimension. 
 

Step 4: Ordinary Least Squares (OLS) with robust standard errors is used to regress the Q1DV against all six independent 

variables and four control variables. 
 

Step 5: The Ordered Logistic Regression Model (Ologit) with robust standard errors is used to regress the Q1DV against all 

the independent and control variables. 
 

Data Anlysis

Reliability and Validity 
Test

Cronbach's Alpha

Impact Analysis

Ordinary Least Squares 
(Robust S.E.)

Ordered Logistic 
Regression Model 

(Robust S.E.)

Test of Financial 
Performance

t-test

Correlation Analysis
Correlation Matrix with 

P Values

Test of Multicollinearity VIF Test

Summarization

Descriptive Statistics



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

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Step 6: The correlation matrix with p values is calculated to understand the variables’ interrelationship to find out the chances 

of multicollinearity. 
 

Step 7: The average net incomes of the women microentrepreneurs’ particular enterprises are calculated in two series. One 

is “average net income before getting microfinance,” and the other is “average net income after getting microfinance." The 

average of net income includes three consecutive years’ average. After that, the average before and after series are used to 

generate the Ln (Before) and Ln (After) series using the lognormal function in STATA. After that, a paired two-tailed t-test 

is conducted on the Ln (before) and Ln (After) series to find whether there are any significant differences between the means 

of the data sets. 
 

 

Step 8: The Variable Inflation Factor (VIF) Test is done to check multicollinearity. 

 

RESULTS 

Reliability and Validity Test (Cronbach’s Alpha)    

In order to find out individual Cronbach’s Alpha, several consistent questions have been designed in the survey questionnaire 

for each variable. In the test, omission methodology has been used to maximize the scale reliability. Appendix-B shows the 

final list of questions used for reaching determining every variable’s reliability and validity. 

 

Table 3. Cronbach’s Alpha Summary for Individual Variables  

 
 

Variables Overall Individual Cronbach’s Alpha 

Q1DV 0.881 

Q1IV 0.896 

Q2IV 0.903 

Q3IV 0.891 

Q4IV 0.930 

Q5IV 0.892 

Q6IV 0.888 

Q7CV 0.889 

Q8CV 0.886 

Q9CV 0.887 

Q10CV 0.887 

Overall Cronbach’s Alpha of Data Set 0.903 

 

In Table 3, the Cronbach’s Alpha is shown. Typically, a good Cronbach's Alpha value falls within the range of 

0.70 to 0.99, although this can vary depending on the research context and the specific measurement instrument used. The 

scale reliability coefficient value 0.903 presented in Table 3 indicates the high reliability and validity of the data set used in 

this study for further analysis.  

 

Descriptive Statistics   

Table 4. Summary Statistics 

 
 

Variable Observation Mean Std. Dev. Min Max 

Q1DV 273 2.655 1.392 0 4 

Q1IV 273 2.267 1.501 0 4 

Q2IV 273 2.666 1.402 0 4 

Q3IV 272 2.172 1.249 0 4 

Q4IV 273 1.908 1.517 0 4 

Q5IV 273 2.373 1.358 0 4 

Q6IV 273 2.435 1.386 0 4 

Q7CV 273 2.421 1.386 0 4 

Q8CV 273 2.487 1.393 0 4 

Q9CV 273 2.490 1.364 0 4 

Q10CV 273 2.501 1.409 0 4 

 

In Table 4, the descriptive statistics for the observation set for first research aim is shown. The table summarizes 

that there are 273 observations and the means and standard deviations are homoscedastic having no heterogenous outliers. 

The minimum and maximum in all cases are 0 and 4 respectively. 

 

Correlation Matrix with P Values    

Table 5. Correlation Matrix with P Values 

 
 

  
Q1DV Q1IV Q2IV Q3IV Q4IV Q5IV Q6IV Q7CV Q8CV Q9CV Q10CV 

Q1DV 1.0 
          

Q1IV 0.6* 1.0 
        

 
0.0 

          

Q2IV 0.5* 0.3* 1.0 
        

 
0.0 0.0 

         

Q3IV 0.7* 0.5* 0.3* 1.0 
       



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

8 

 
0.0 0.0 0.0 

        

Q4IV 0.0 0.0 0.1 0.0 1.0 
      

 
0.9 0.8 0.2 0.7 

       

Q5IV 0.6* 0.5* 0.3* 0.5* 0.1 1.0 
     

 
0.0 0.0 0.0 0.0 0.2 

      

Q6IV 0.7* 0.4* 0.4* 0.5 0.0 0.6* 1.0 
    

 
0.0 0.0 0.0 0.0 0.8 0.0 

     

Q7CV 0.7* 0.5* 0.3* 0.6* 0.0 0.5* 0.6* 1.0 
   

 
0.0 0.0 0.0 0.0 0.5 0.0 0.0 

    

Q8CV 0.7* 0.5* 0.4* 0.5* 0.0 0.5* 0.6* 0.7* 1.0 
  

 
0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 

   

Q9CV 0.7* 0.4* 0.3* 0.6* -0.1 0.5* 0.5* 0.6* 0.7* 1.0 
 

 
0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 

  

Q10CV 0.7* 0.4* 0.4* 0.5* 0.0 0.5* 0.6* 0.6* 0.6* 0.7* 1.0  
0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 0.0 0.0 

 

   Here,* denotes significance at 95% confidence interval. 

 

In Table 5, the correlation matrix with p values states that there exists a good and positive correlation between the 

independent variables and the dependent variable. Almost every independent variable provides strong explanatory evidence 

of a representing the changes in the dependent variable. 

 

Linear Probability Model (with Robust Standard Errors)     

Table 6. Summary of OLS (with Robust Standard Errors) 

 
 

Number of Observations P Value R-Squared 

273 0.000*** 0.819 

   Here, *** Stands for 99% Confidence interval 

 

In Table 6, using OLS with robust standard errors, the p value is significant at a 99% confidence interval. The OLS 

model rejects the null hypothesis by establishing a significant relationship between microfinance and the socioeconomic 

development of women microentrepreneurs. The R-Squared of 81.93% indicates that the explanatory variables can 

accurately predict changes in the dependent variables by 81.93%, providing strong evidence of the model's fitness. 
 

Table 7. Summary of Multivariate OLS Outcomes (with Robust Standard Errors) 

 
 

Variables Coefficients Robust Standard Errors t Values P Values 

Q1IV 0.085 0.034 2.43 0.016** 

Q2IV 0.079 0.032 2.41 0.017** 

Q3IV 0.202 0.049 4.08 0.000*** 

Q4IV 0.023 0.022 1.02 0.311 

Q5IV 0.070 0.042 1.66 0.098* 

Q6IV 0.193 0.048 3.99 0.000*** 

Q7CV 0.197 0.047 4.16 0.000*** 

Q8CV 0.012 0.049 0.25 0.804 

Q9CV 0.103 0.053 1.95 0.052* 

Q10CV 0.221 0.048 4.52 0.000*** 

constant -0.191 0.113 -1.68 0.093 

Here,*** Stands for 99% Confidence interval ** Stands for 95% Confidence interval * Stands for 90% Confidence interval 

 

In Table 7, the detailed outputs as per variables are listed. The results show that except for Q4IV and Q8CV, all 

the variables are significantly impacting the dependent variable. The coefficients represent a positive slope in predicting the 

dependent variable.  

 

Ordered Logistic Regression Model (with Robust Standard Errors)    

Table 8. Summary of Ologit (with Robust Standard Errors) 

 
 

Number of Observations P Value Pseudo R-Squared 

273 0.000*** 0.465 

    Here, *** Stands for 99% Confidence interval 

 

In Table 8, the Ologit model, featuring robust standard errors, demonstrates a significant p value within a 99% 

confidence interval. This rejects the null hypothesis using the Ologit model by stating that there exists a significant 

relationship between microfinance and the socioeconomic development of women microentrepreneurs. The pseudo-R-

squared shows that the explanatory variables have strong confidence in predicting the dependent variable. 
 

Table 9. Summary of Multivariate Ologit Outcomes (with Robust Standard Errors) 

 
 

Variables Coefficients Robust Standard Errors z Values P Values 

Q1IV 0.252 0.114 2.2 0.028** 



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

9 

Q2IV 0.186 0.106 1.75 0.081* 

Q3IV 0.573 0.158 3.62 0.000*** 

Q4IV 0.108 0.082 1.32 0.187 

Q5IV 0.254 0.151 1.68 0.094* 

Q6IV 0.608 0.170 3.56 0.000*** 

Q7CV 0.641 0.179 3.58 0.000*** 

Q8CV 0.022 0.175 0.13 0.896 

Q9CV 0.367 0.182 2.02 0.044** 

Q10CV 0.643 0.177 3.64 0.000*** 

 
Here,*** Stands for 99% Confidence interval ** Stands for 95% Confidence interval * Stands for 90% Confidence interval 

 

In Table 9, the results completely affirm with the outcomes of OLS in Table 7. Except for the Q4IV and Q8CV, 

all the independent and control variables are significantly impacting the dependent variable. 

 

Test of Multicollinearity (VIF Test)      

Table 10. VIF Results 

 
 

Variable VIF 1/VIF 

Q8CV 2.87 0.35 

Q9CV 2.87 0.35 

Q10CV 2.86 0.35 

Q6IV 2.53 0.40 

Q7CV 2.52 0.40 

Q5IV 2.13 0.47 

Q3IV 2.1 0.48 

Q1IV 1.75 0.57 

Q2IV 1.37 0.73 

Q4IV 1.05 0.95 

Mean VIF 2.2 
 

 

Referring to Table 10, where the test of multicollinearity using Variable Inflation Factor (VIF) is tested. The results 

show that mean VIF is 2.2 which explains that the models don’t have substantial amount of multicollinearity.  

 

The Paired t-test on Microenterprises’ Financial Performance (Net Income)      

Table 11. Paired t-test Summary Result 

 
 

Paired t-test {Ln (After) – Ln (Before)} 

P Values 0.0021*** 

t Values 3.2307 

Here, *** Stands for 99% Confidence interval 
 

With reference to Table 11, using the 3-year average net income before taking the microfinance and the 3-year 

average net income after taking the microfinance, the sets are converted into lognormal values. At a 95% confidence interval, 

the paired t-test values reject the null hypothesis, indicating a significant difference between the means of the data sets 

before and after the microfinance loans received by the women microentrepreneurs. The t values for the difference between 

the Ln (after) and Ln (before) datasets are 3.2307, indicating that microfinance had a positive impact on microenterprises' 

financial performance. 

 

DISCUSSIONS 

The study's results align with the findings of relevant studies conducted in various geospatial contexts around the world. 

Shah's (2024) study revealed that microfinance significantly reduces poverty in Bangladesh, a finding further validated by 

the study's focus on women microentrepreneurs. Robert (2024) discovered in Uganda that microfinance enables access to 

credit and financial services and creates market opportunities, which aligns with this study's findings. However, a study by 

Hemat and Rahman (2023) in Afghanistan revealed that while microfinance positively benefited women, the impact was 

not significant. Our study ensures that, from a Bangladeshi perspective, the positive impact of microfinance on women 

microentrepreneurs is significant. Gupta and Meher (2016) concluded in their study that microfinance plays a critical role 

in empowering women entrepreneurs. The study validates the findings of previous studies conducted in diverse global 

contexts. The study's analysis confirms acceptance of the first alternative hypothesis, which asserts a significant relationship 

between microfinance and the socioeconomic development of women microentrepreneurs. The study also accepts the second 

alternative hypothesis, which asserts a significant relationship between microfinance and the financial performance of 

women-led microenterprises. The study identifies five independent variables that significantly impact the dependent 

variable: easy access to capital, job creation, economic, legal, and political networks, better psychological wellbeing, and 

relative freedom from family dominance. Meanwhile, the control variables, asset size, age of business, and amount of loan 

taken, also significantly impact the dependent variable. The R-squared from OLS with robust standard errors is 81.9%, and 

the pseudo-R-squared from the Ologit regression model with robust standard errors is 46.5%. The R-squared represents 

strong explanatory confidence among the independent variables to predict the dependent variable. Once again, a paired t-



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

10 

test comparing the three-year average net income of women-led microenterprises before and after microfinance reveals that 

microfinance has a significant impact on their financial performance. Based on the alignment of findings from prior studies 

and this study, the study concludes that microfinance significantly impacts the socio-economic development of women 

microentrepreneurs in Bangladesh while also significantly enhancing their financial performance. With assurance to reject 

the null hypotheses, the study affirms that microfinance significantly and positively impacts the socio-economic 

development of women microentrepreneurs and financial performance of women-led microenterprises in Bangladesh. 

 

CONCLUSIONS 

Previous research on a similar segment of microfinance also revealed the importance of microfinance in a country's GDP 

and economic development. The study's uniqueness relied on direct responses from women microentrepreneurs and their 

enterprises' financial information to meet the research objectives. The study concentrated on root-level responses and 

secondary data-driven outcomes to explain whether microfinance in Bangladesh significantly improves the socio-economic 

development of women microentrepreneurs and the financial performance of their enterprises. The findings show a 

significant relationship between microfinance and the socioeconomic development of female microentrepreneurs. The study 

also discovered that microfinance significantly enhances the financial performance of women-led microenterprises. This 

study contributes significantly to developing ideas about the current contribution of microfinance to women’s empowerment 

in an emerging economy like Bangladesh. The study suggests significant policy implications for expanding the reach of 

microfinance throughout the country and providing technical education to clients on how to effectively use microfinance to 

establish and operate businesses. The study provides an avenue for much deeper studies involving more respondents 

countrywide and comparing microfinance’s contributions with those of other emerging economies using similar mixed-

method pathways. 

 
 
Author Contributions: Conceptualization, G.R. and P.R.S.; Methodology, G.R.; Software, G.R and P.R.S.; Validation, G.R. and P.R.S.; Formal Analysis, 

G.R.; Investigation, G.R. and P.R.S..; Resources, P.R.S.; Data Curation, G.R.; Writing – Original Draft Preparation, P.R.S. and G.R.; Writing – Review & 
Editing, G.R and P.R.S.; Visualization, G.R.; Supervision, G.R.; Project Administration, G.R. and P.R.S.; Funding Acquisition, G.R. and P.R.S. Authors 

have read and agreed to the published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study because the research does not deal with vulnerable groups 
or sensitive issues. 

Funding: The authors received no direct funding for this research.  

Acknowledgements: The views and opinions expressed in this article are mine and do not necessarily reflect the views of their institution. 
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 
due to restrictions.  

Conflicts of Interest: The authors declare no conflict of interest. 

 

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APPENDICES 

Appendix-A: Survey Questionnaire 

 
Name - 

Age of the enterprise - 

Size of the Total Assets - 

Number of Employees Working - 

Amount of loan taken - 

Location - 

Age of the owner/s - 

Types of Business - 

Net Income for three years before and after microfinance received - 

 

Survey Questionnaire (Part A) 

 
Numbers Questions Strongly 

Agree***** 

Agree**** Neutral*** Disagree** Strongly 

Disagree* 

1 Have you gained more economic security and 

become able to appreciate your capital after taking 
microfinance? 

- - - - - 

2 Do you have easy access to capital now after taking 

microfinance, comparing to when you didn’t have 
microfinance? 

- - - - - 

3 Could your microenterprise create job for your 

community? 

- - - - - 

4 Could you get better access to economic, legal, and 
political network after taking microfinance? 

- - - - - 

5 Utilizing the loan, could generate higher income and 

get ability to more purchase? 

- - - - - 

6 Are you now at a better psychological wellbeing 
after taking microfinance? 

- - - - - 

7 Do you think that you can manage a relative better 

freedom from domination your family now after 

taking microfinance? 

- - - - - 

Here, ***** represents 4, **** represents 3, *** represents 2, ** represents 1, * represents 0 

 

Survey Questionnaire (Part-B) 

 

Numbers Control Variables Codes 

4 3 2 1 0 

8 Size of Total Assets 7 lacs to 10 lacs 5 lacs to below 7 

lacs 

3 lacs to below 5 

lacs 

1 lac to below 

3 lacs 

Less than 1 lacs 

9 Location of the 
enterprise 

Metropolitan City Upazilla Thana Village 

10 Age of the enterprise Above 10 years 5 years to below 

10 years 

3 years to below 5 

years 

6 months to 3 

years 

1 month to below 6 

months 

11 Amount of Loan 
Taken 

5 lacs to 10 lacs 3 lacs to below 5 
lacs 

1 lac to below 3 
lacs 

50 thousand 1 
lac 

Below 50 thousand 

 

 

Appendix-B (Likert Scale 0 to 4) Supporting Questions after Omission Methodology   

   
 

Main Questions Sl. No. Supporting Questions/Statements 

Have you gained more 

economic security and 

become able to appreciate 

your capital after taking 

microfinance? 

1 Has your income achieved greater stability since you obtained microfinance? 

2 Have you experienced any growth in your savings or assets since engaging in microfinance? 

3 Your enterprise experienced an increase in size, revenue, or customer base as a result of obtaining 

microfinance. 

4 You obtained additional assets (such as equipment, inventory, or property) for your business or personal use 

subsequent to receiving microfinance. 

5 Your ability to handle your finances and make financial choices improved as a result of obtaining 

microfinance. 



Roy & Sarkar, Indian Journal of Finance and Banking 14(1) (2024), 1-13 

 

13 

Do you have easy access to 

capital now after taking 

microfinance, comparing 

to when you didn’t have 

microfinance? 

1 You can obtain further financing or loans, in comparison to the period prior to your acquisition of 

microfinance. 

2 You received offers or successfully acquired fresh credit or loans from other financial institutions subsequent 

to obtaining microfinance. 

3 Has the capital for your business activities increased since obtaining microfinance, in comparison to when 

you did not have microfinance? 

Could your 

microenterprise create 

job for your community? 

1 You strongly advocate for the necessity of recruiting extra personnel for your microenterprise following the 

acquisition of microfinance. 

2 You are convinced that your microenterprise has made a significant contribution to the creation of job 

possibilities within your local community. 

3 As your microenterprise expands, you intend to recruit additional employees or workers. 

4 You had difficulties in recruiting personnel or expanding your labor force. 

Could you get better 

access to economic, legal, 

and political network 

after taking 

microfinance? 

1 Since obtaining microfinance, your access to economic networks and commercial options has significantly 
improved. 

2 Since obtaining microfinance, you now have enhanced access to legal support and information. 

3 Since receiving microfinance, you have gained enhanced access to political networks and community power. 

Utilizing the loan, could 

generate higher income 

and get ability to more 

purchase? 

1 By utilizing the loan, you have been able to create a greater revenue than previously. 

2 Since obtaining the loan, I have been able to acquire a greater quantity of goods or services to meet the 

demands of my business or personal requirements. 

3 The financing has facilitated your investment in my firm, resulting in expansion and increased profitability. 

Are you now at a better 

psychological wellbeing 

after taking 

microfinance? 

1 Acquiring microfinance has alleviated your financial distress and concerns. 

2 Accessing microfinance has bolstered your confidence and elevated your self-esteem. 

3 The microfinance you received has significantly enhanced your overall quality of life. 

4 Microfinance has enhanced your sense of financial security and stability. 

Do you think that you can 

manage a relative better 

freedom from domination 

your family now after 

taking microfinance? 

1 Acquiring microfinance has enhanced your autonomy in managing your finances, reducing your reliance on 

my family. 

2 You now possess greater autonomy to make independent decisions without any interference from your 

family. 

3 Microfinance has resulted in a reduction of familial control or intervention in your financial and economic 

affairs. 

4 Since undertaking microfinance, your capacity to negotiate and assert my preferences within my family has 

significantly enhanced. 

 

 
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