The impact of financial literacy on financial inclusionin vietnam

Many studies have been advanced towards the financial literacy and financial inclusion discourse due to the global financial crisis, with an increased emphasis on the role of financial l

THE STATE BANK OF VIET NAM MINISTRY OF EDUCATION AND

TRAINING

BANKING UNIVERSITY HO CHI MINH CITY

-

GRADUATION THESIS PHAN ANH KHOA THE IMPACT OF FINANCIAL LITERACY ON FINANCIAL

INCLUSION IN VIET NAM

Supervisor: Assoc Prof PhD HA THI THIEU DAO

Ho Chi Minh 2021 COMMITMENT`

This thesis is the author's study The research results are honest in that there

is no previously published content or other content done by someone else except fully cited citations in the thesis

Ho Chi Minh City, 29/09/2021

Khoa

Phan Anh Khoa

ABSTRACT

This thesis explores the impact of financial literacy and financial technology

on financial inclusion in the university in Viet Nam It employs a sample of 567 respondents sampled across the 3 regions of Viet Nam from June 2021 to August

2021 Logistic regression was used to analyse of impact of financial literacy on financial inclusion The following empirical findings emanate from this thesis: financial literacy positively and significantly affect financial inclusion The thesis discovers that financial literacy has a significant impact on financial inclusion through owning a bank account Finally, it shows that financial literacy and Fintech has a significant impact on financial inclusion Overall, the findings of the study provide policymakers in Vietnam with recommendations

ACKNOWLEDGEMENT

I would like to thank my teacher Ha Thi Thieu Dao, Assoc Prof, Ph.D., for supporting me to complete the project successfully

I would like to express my gratitude to all my friends who have supported me

to share my survey in student groups

This research would not have been possible without their support

ABSTRACT 3

ACKNOWLEDGEMENT 4

Chapter 1: INTRODUCTION 1

1.1 Problem Statement 1

1.2 Objectives 3

1.2.1 Overall objective 3

1.2.2 Specific objectives 3

1.3 Research questions 3

1.4 Objectives and scope 3

1.5 Research methodology 3

1.5.1 Data 3

1.5.2 Regression method 4

Chapter 2: RESEARCH LITERATURE REVIEW 6

2.1 Financial inclusion 6

2.1.1 Definition 6

2.1.2 Financial inclusion measurement 7

2.2 Financial literacy 8

2.2.1 Definition 8

2.2.2 Financial literacy measurement 10

2.3 Determinants of financial inclusion 11

2.3.1 Financial literacy and financial inclusion 11

2.3.2 Control variables 12

2.4 Summary 19

CHAPTER 3: RESEARCH METHODOLOGY 20

3.1 Research Data 20

3.2 Regression method 20

3.2.1 Binary logistic model 20

3.2.2 Model specification 22

3.3 Testing 25

3.3.1 Omnibus Tests 25

3.3.2 Hosmer and Lemeshow Test 26

3.4 Summary 26

CHAPTER 4: RESULT OF STUDY AND DISCUSSIONS 27

4.1 Descriptive statistics 27

4.1.1 Demographic statistics 27

4.1.2 Financial Inclusion Statistics 29

4.1.3 Financial literacy statistics 30

4.2 Regression results and discussions 31

4.3 Summary 37

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS 38

5.1 Conclusions 38

5.2 Recommendations 38

5.3 Limitation and research future 40

REFERENCE 41

APPENDICES 51

LIST OF TABLES

Table 2.1 Conceptual definitions of financial literacy 9

Table 2.2 Summary of previous research on financial inclusion 16

Table 3.1 Summary of variable in the research 23

Table 4.1 Demographic statitics 28

Table 4.2 Percentage of owning an account 30

Table 4.3 Score of financial literacy 31

Table 4.4 Result of regression of financial inclusion 33

Table 4.5 Probability of owning an account 36

Chapter 1: INTRODUCTION

1.1 Problem Statement

In the development of industry 4.0, one of the most vital factors determining the development and growth of the national financial system in the current integration context is financial inclusion Financial inclusion offers many benefits for individuals and businesses to access financial services affordably and conveniently Financial inclusion also helps them have a good view of savings, investment, ability to create assets, and improve quality of life For a developing country like Viet Nam, financial inclusion is increasingly becoming a vital pillar

of the country's development

Besides that, financial literacy plays an important role in furthering financial inclusion (Grohmann, FKlühs & Menkhoff, 2018) Financial literacy contributes

to the improvement of social life, economic development and social well-being

To catch up with Industry 4.0's development, many countries have developed and implemented national programs and strategies to improve financial literacy and financial education In this way, financial literacy becomes one of the essential skills for all members of society However, the impact of financial literacy of financial inclusion can be reversed by objective factors Babych, Grigolia & Keshelava (2018) demonstrate that low income levels, lower financial behavior may be in part responsible for low levels of financial inclusion and thus, indirectly, lead to lower levels of financial literacy Several studies in developing countries have also confirmed that better financial literacy is positively associated with participation in financial markets, the use of formal sources of borrowing (Klapper et al., 2017)

Despite the benefits of financial literacy, financial illiteracy exists worldwide The full benefits of financial inclusion are difficult to realize because of this phenomenon (Akakpo, 2020) Although financial literacy is an important tool,

economic and social barriers to access may need to be overcome before financial literacy can be effective (Lyons, Chang, & Scherpf, 2006) Many studies have been advanced towards the financial literacy and financial inclusion discourse due to the global financial crisis, with an increased emphasis on the role

of financial literacy in increasing access to, and use of, financial services (Xu & Zia 2012) For instance, Menon (2019) suggested that financial inclusion must be accompanied by financial literacy in order to achieve the best results Grohmann, Klühs & Menkhoff (2018) emphasized that proving the stylized fact that higher financial literacy is systematically linked to better financial inclusion at the national level

Recently, there has been limited research that pulls on finance theory to research whether Fintech can help financial inclusion and the way this might ultimately shed light on the intractable problem of lack of financial literacy However, World Bank support in 2011, 2014 and 2017 provided evidence on the connection between Fintech and financial inclusion

However, financial inclusion in Vietnam continues to be limited According

to World Bank’s Global Findex (2017), in Viet Nam, only 31% of people have accounts, which is higher than Cambodia (22%) and Lao (29%) and this figure is

a warning to the government About 69% of adults in Vietnam are non-banked and therefore dependent on money to buy or sell goods and services.That means that out of Vietnam's 97 million citizens, there are approximately 50 million people, aged 15 and over, relying on cash (World Bank, 2018) The number of deposit accounts with commercial banks in Viet Nam per 1000 adults is approximately 1194,86, which is only higher than Lao (672,47) and Cambodia (376,39) Furthermore, while financial inclusion has improved significantly in other Asian economies, progress in Vietnam appears to be slow Some recent studies have been conducted on how financial literacy can help improve financial inclusion in economies that are progressing slowly (Babajide, Adegboye &

Omankhanlen, 2015; Sethi & Acharya, 2018; Sharma, 2016) This search complements the blanks.

Thereby it can be seen that the impact of financial literacy and financial inclusion plays an important role Lack of financial literacy will lead to ineffective financial decisions What is the impact of financial literacy on financial inclusion in Vietnam? This research will add a certificate about the effect of financial literacy and financial inclusion That is also why we chose the topic “financial literacy and financial inclusion”

1.2 Objectives

1.2.1 Overall objective

The main focus of this study is to determine the impact of financial literacy

on financial inclusion and increasing positive influences to financial inclusion

1.2.2 Specific objectives

－ Examining financial literacy impacts on financial inclusion

－ Exploring level of impact of financial literacy on financial inclusion

1.3 Research questions

After identifying the research objectives as outline above, a few research question is issued

－ Does financial literacy affect financial inclusion?

－ What is the impact level of financial literacy on financial inclusion ?

1.4 Objectives and scope

－ Objectives: The research survey the students from the universities

－ Scope: The research chooses 3 regions in Viet Nam: Ho Chi Minh, Vinh Long and Lai Chau

1.5 Research methodology

1.5.1 Data

The data collect by online survey Data collected about 567 students completed the questionnaire and were selected for analysis The study selected

three random regions to represent: the highlands (Lai Chau), the downtown (Ho Chi Minh city), and the plains (Vinh Long) based on the bank's distribution density

1.5.2 Regression method

This research employs quantitative regression techniques The study employs logistic regression approach and uses the software SPSS This estimate measures causality from the outcome variables of financial literacy and financial inclusion

It is the objective of the study to establish how financial literacy and financial inclusion

Increasing student spending needs to make it easier for them to access financial inclusion

1.7 Research structure

The research is divided into five sections The first chapter provides an overview of the research topic The second chapter is dedicated to a literature review The review concentrates on empirical and theoretical research in the areas

of financial inclusion, financial literacy In chapter three, the study's methodology

is presented in detail It encompasses the research design, population, data collection, model specification, dependent and independent variable selection,

and data analysis mode The study's results and discussions are presented in Chapter 4 It provides an interpretation of the findings and backs them up with research on financial inclusion, financial literacy The study's conclusion is presented in chapter five This chapter also includes recommendations and limitations

Chapter 2: RESEARCH LITERATURE REVIEW

2.1 Financial inclusion

2.1.1 Definition

Financial inclusion has been a much-researched topic in recent years A series of studies have examined the important role of financial inclusion Financial inclusion is the process of regulated mainstream institutional players providing appropriate financial products and services to all sections of society in general, and vulnerable groups such as weaker sections and low-income groups

in particular, at an affordable cost fairly and transparently (Chakrabarty, 2011) Sarma & Pais (2011) illustrated that financial inclusion is a process that assures that all members of an economy have easy access to, and use of, the official financial system Financial inclusion outreach can be characterized generically

as the process of providing all members of society with a range of necessary financial services at a reasonable cost, at the appropriate location, form, and time, and without discrimination (Aduda & Kalunda, 2012) Despite the different definitions, financial inclusion is believed to be individuals' access to relevant financial products and services (Hayton & alt, 2007) Financial inclusion is an indispensable sector of economic growth and poverty reduction (World Bank, 2018) Multilateral organizations have repeatedly emphasized the benefits of universal access to financial services and emphasized the global committed to expanding financial inclusion as a means of economic and social improvement around the world (World Bank, 2018) Besides that, Kirana & Havidz (2020) concluded that better financial knowledge, behavior, perceived usefulness, and ease of use may promote financial inclusion and are more reachable since the poor can access and use financial products and services as well as improve their quality of life and welfare of society Moreover, financial inclusion adding value

to small and medium enterprises (Demirgüç-Kunt, Honohan & Beck, 2008)

2.1.2 Financial inclusion measurement

Financial inclusion has been studied in countries around the world Fungaova & Weill (2014 ) examined financial inclusion in China using data from the 2011 World Bank Global Findex database through using financial services such as formal account, formal credit, access to formal education,… Zins & Weill (2016) used the World Bank's Global Index database to discover that in Africa, being a man, who is wealthier, more educated, and older, favors financial inclusion, with education and income having a better influence Besides that, Léon & Zins (2020) also used datasets from World Bank Global Findex; and the World Bank's Business Survey to measure financial inclusion Almost all of the studies use data from the World Bank's Global Findex database, which takes advantage of the standardized questionnaire used to collect indicators from all countries, makes it easy to compare metrics or aggregate data across the countries

Researchers, governments, and policymakers are concerned about how to evaluate financial inclusion While the causes and consequences of financial inclusion are still being investigated around the world There is no consensus on how it should be defined and quantified As previously stated, most studies continue to define “financial inclusion” in terms of formal bank account availability, usage, and quality (Lyons & Kass-Hanna,2021) According to Allen, Demirguc-Kunt, Klapper, and Martinez Peria (2016), financial inclusion is measured using a variety of indicators such as "owner account", "owner bank card”, "savings" and so on The study focuses on the indicator “owner an account” due to previous research (Lusardi, Schneider, & Tufano, 2011; Demirgüç-Kunt

et al, 2015; Grohmann, Klühs & Menkhoff, 2018; Lyons, Grable & Joo, 2018; World Bank, 2017; …) “Owner an account” is the most important indicator They identify those who have a formal bank account where they could potentially save Individuals who are "financially inclusion" in the mainstream financial system are referred to as "financially inclusion” However, just because you have

a formal account doesn't mean you'll use it According to World Bank (2017), having a bank account is a crucial first step toward financial inclusion

2.2 Financial literacy

2.2.1 Definition

Atkinson & Messy (2012) has defined financial literacy as “a combination of awareness, knowledge, skill, attitude, and behavior necessary to make sound financial decisions and ultimately achieve individual well-being”.Financial literacy has occupied a prominent place on the policy agenda of many countries (OCED/2015) Lusardi (2019) found that financial literacy affects everything from daily to long-term financial decisions, and this has implications for both individuals and society Low levels of financial literacy across countries correlate with inefficient financial planning and spending, as well as expensive debt and debt management Moreover, financial literacy beyond understanding, covering aspects of financial behavior and attitudes (OCED/2020)

Financial literacy can be defined in various ways, depending on the perspective of the individual and the researcher In the simplest definition, Atkinson & Messy (2012) has defined financial literacy as “a combination of awareness, knowledge, skill, attitude and behavior necessary to make sound financial decisions and ultimately achieve individual well-being” In details, it is the “knowledge of basic financial concepts, such as the working of interest compounding, the difference between nominal and real values, and the basics of risk diversification” (Lusardi, 2008) In some practical views, financial literacy

is defined: “The ability to make informed judgments and to take effective decisions regarding the use and management of money ” ANZ Bank (2008) and Gowri (2015) seem to have a more comprehensive understanding about financial literacy In general, financial literacy is a broad term, and research on it focuses

on analyzing financial literacy outcomes, assessing levels among various population cohorts, factors impacting financial literacy, and the impact of

financial education on enhancing financial literacy (Goyal & Kumar, 2020) In short, financial literacy is synthesis of an individual's perceptions, attitudes, and skills toward financial matters.

Table 2.1 Conceptual definitions of financial literacy

PACFL (2008) The ability to use knowledge and skills

for the effective management of financial resources for long-term financial well-being

well as the application of that knowledge

Lusardi and Mitchell (2011) The knowledge of basic financial

concepts and ability to do simple calculations

financial concepts and risks, and the skills, motivation and confidence to apply such knowledge and understanding to make effective decisions across a range of financial contexts, to improve the financial well-being of individuals and society, and to enable participation in economic life

Sahadeo (2018) Financial literacy is a combination of

the awareness, knowledge, abilities, attitudes, and habits needed to make sound financial decisions and, ultimately, to achieve individual financial well-being

Santini (2019) The constructs of financial literacy as

financial attitude, financial knowledge, and financial behavior Swiecka (2020) Financial literacy as the knowledge

and understanding of financial concepts and risks

Source: The author synthesized

2.2.2 Financial literacy measurement

The development of financial literacy led to many studies and a variety of questions being formed Klapper, Lusardi & Van Oudheusden (2015) choose the definition of a financial literate as someone who correctly answers three out of four questions assessing financial knowledge on four simple concepts (knowledge of interest rate, interest compounding, inflation, and risk diversification) In the United Arab Emirates, Al-Tamimi & Kalli (2009) measured the financial literacy of UAE investors using 18 exam-type true-or-false questions covering the main aspects of investment management Studies also extend the measurement to a variety of factors, Brown, Henchoz & Spycher (2018) measured financial literacy by surveying and comparing secondary-school students along the German–French language border within Switzerland, Gunawan & et al (2021) explored financial literacy have paid attention to issues related to gender with a particular focus on women, Lusardi, Mitchell & Curto (2010) also paid attention to financial literacy with an emphasis on the youth and

their determinant Financial literacy studies have suggested that financial services professionals should take advantage of the many benefits presented by financial education (Akakpo, 2020)

Financial literacy score proposed in Klapper et.al (2015), which is used there

is a dummy variable, given “1” if the question is answered correctly and the other responses are given value "0" The mean percentages of correct scores were divided into three categories, as suggested by the literature (Chen & Volpe, 1998): (a) over 80%, representing a relatively high level of knowledge; (b) 60% to 79%, representing a medium level of knowledge; and (c) below 60%, representing a low level of knowledge

The research followed Klapper et.al (2015) and Ergün (2018), that means the research divided student in two group Students who scored higher than the average were classified as more financial literacy Students below the median score were classified as less financial literacy In this study, financial literacy was assumed to be positively related to financial inclusion However, the person who answers all questions correctly cannot be considered financial professionals The financial literacy questions cover the following topics: interest rates, interest compounding, inflation, and risk diversification

2.3 Determinants of financial inclusion

2.3.1 Financial literacy and financial inclusion

Most studies have found that financial literacy has played an important role

in creating financial inclusion (Trianto, Barus & Sabiu 2021; Grohmann & Menkhoff 2020; Lyons & Kass-Hanna 2019; Bongomin, Munene, Ntayi & Malinga 2018; ) Financial Inclusion is a lofty ideal but financial Literacy is the first step towards achieving Financial Inclusion (Ramakrishnan, 2012) Financial literacy impact on financial inclusion through many factors: saving behavior (Morgan & Long 2020), income (Adetunji & David‐West 2019), financial education (Ramakrishnan 2012), financial tenology (Morgan & Trinh 2019), In

addition, the World Bank also has many studies exploring the impact of financial literacy on financial inclusion detail as: The World Bank Global Financial Development Report on Financial Inclusion (2014) states that financial literacy has statistical and economic implications on financial behavior However, these studies ignore the role of social capital as a critical factor in mediating between financial literacy and financial inclusion, especially Fintech A large number of research have been published to the link between financial literacy and financial inclusion Financial inclusion is seen as a critical tool for promoting inclusive growth and reducing poverty (Morgan & Long, 2020) Bongomin, Munene & Yourougou (2020) found that financial intermediaries help people become more financially literate, which leads to greater financial inclusion.They also found that financial inclusion is improved as a result of increased financial literacy According to Grohmann et al (2018), financial literacy has a beneficial effect on financial services, which is a good influence on people of all income levels and subgroups within countries with different features According to the World Bank (2008), financial literacy aids in improving financial service efficiency and quality Moreover, Lusardi (2008) also suggested that financial literacy supports

in the empowerment and education of the poor so that they are knowledgeable and capable of evaluating various financial products and services to make informed financial decisions and get maximum benefit Financial literacy promotes decision-making, which improves savings rates and potential borrowers' credit worthiness, leading in greater access and usage of financial services by the poor (OCED 2009)

2.3.2 Control variables

- Fintech

The majority of studies now show that Fintech is an important driver of financial inclusion ( Jack & Suri, 2013; Gosh 2016; Gosavi 2018;…) Besides that, there is also evidence of a link between mobile money use and household

and firm financial inclusion According to Andrianaivo & Kpodar (2012), there

is evidence of a strong link between mobile phone penetration and financial inclusion in both developed and developing countries Through its effects on increased access to bank credit, mobile money has also been found to have a positive impact on SME financial inclusion (Gosavi, 2018) Households with a mobile money account are more likely to be banked, receive/send remittances on

a more regular basis, and save more money (Morawczynski, 2009; Jack & Suri, 2011; Mbiti & Weil, 2011,…) Through that, In countries where the majority of the population is unbanked (or informally banked) but owns a mobile phone, mobile technology has enormous potential for expanding the reach of the formal banking system (Demir, Pesqué-Cela, Altunbas, & Murinde, 2020)

Fintech is considered an independent variable in this study Following the previous researches, mobile phone penetration and fixed broadband penetration are the instruments used in Fintech (Andrianaivo & Kpodar 2012; Ghosh 2016; Demirgüç-Kunt et al 2018) However, despite the fact that there are a variety of measurement tools available, most studies opt for a common metric, which is the use of telephone services In this study, the factor “using mobile to payment” was used to measured Fintech The use of mobile phones to pay bills is a proxy for Fintech (Asongu & Odhiambo, 2018; Asongu & Nwachukwu, 2018; Demir, Pesqué-Cela, Altunbas, & Murinde, 2020)

- Demographics

According to a growing body of evidence, individual characteristics can influence financial inclusion Individual characteristics such as gender, age, education, and income levels have been identified as key factors influencing financial inclusion in the literature For instance, Soumaré et al (2016) proved that gender, education, age, income, residence area, employment status, marital status, household size, and degree of trust in financial institutions all played a role

in financial inclusion Shihadeh (2018) also investigates how personal

characteristics influence financial inclusion in the MENAP region Zins & Weill (2016) use the World Bank's Global Index database to find that in Africa being a man, richer, more educated and older, favor financial inclusion with a higher influence of education and income Evans (2016) also identified the factors that influenced financial inclusion in Africa from 2005 to 2014 Financial inclusion was found to be driven by per capita income, broad money as a percentage of GDP, literacy rate, internet access, and the presence of Islamic banking activities

In Sub-Saharan Africa, macroeconomic variables, age, education, gender, and affluence are individual-level covariates that have a significant impact on financial inclusion (Asuming et al, 2019)

Within the research, some studies have even taken a more localized approach

to investigate the relationship between financial inclusion and financial technology For example, mobile money allows users to conduct financial transactions such as bill payments, savings, money transfers, loan acquisition, and product and service purchases (Donovan, 2012) The provision of financial services via mobile phones and related devices can improve access to finance for the excluded population (World Bank, 2016) According to Bongomin & et.al(2018), social networks improved financial inclusion in Uganda by increasing social cohesion Evans (2018) examine the relationship between the internet, mobile phones and financial inclusion in Africa from 2000 to 2016, and find that the internet and mobile phones improved the ability of individuals to access basic financial services thereby increasing the level of financial inclusion

Gender is considered an independent variable in this study Individual characteristics may influence both financial inclusion and financial literacy (Allen et al, 2016) According to previous studies, it was assumed that women and men have different financial capabilities such as: in South Africa, women mostly use formal transactional products and informal financial mechanisms, while men mostly use formal credit, insurance, and products (Nanziri, 2016);

women in Comoros either lack money or are unaware of available financial services, making it difficult for them to escape poverty (Ali, 2019)

Age is an independent variable in the study because the use of bank accounts

is expected to rise and fall with age In terms of financial inclusion, studies look

at the adult population aged 15 and up because they have a better chance of being financially educated and included in the financial system (Akakpo, 2020) A higher age dependency ratio should reduce financial inclusion because a larger portion of the population is either too young or too old to work, preventing them from accessing financial services because they do not earn an income (Park & Mercado, 2015)

Place of study is also an independent variable in the study because where respondents are located often has a relationship with their levels of financial education and financial inclusion (Lyons & Kass-Hanna, 2021) showed that The comparison of urban and rural areas adds to our understanding of which types of financial services and products are most effective in different geographical locations and for different types of people Marshall (2004) emphasized that People and their geographical location can have an impact on their ability to participate in the formal financial system

Educational level is considered as the correlation between financial literacy and financial inclusion because individuals who are more educated are better able

to comprehend basic financial concepts and use financial products According to Fungáová and Weill (2015), higher income, better education, being a man, and being older are all linked to more use of formal accounts and formal credit in China Yangdol & Sarma (2019) looked at the demand-side factors that affect financial inclusion and found that higher levels of education and income increase people's financial inclusion

Field of study is also an independent variable in the study because major of respondents often have a relationship with their levels of financial literacy and financial inclusion Ergün (2018) shows that the impact of finance courses on financial literacy is significant

Employment status is also an independent variable because their employers are likely to require an account for the payment of their salaries Demirgüç-Kunt, Klapper & Singer (2013) used the Global Findex database to show that the employment status is a key determinant of owning an account According to Ghosh & Chaudhury (2019), the lack of a bank account, formal savings, and formal credit requirements are primarily due to females' lower employment status Finance your course is considered as the correlation with financial literacy and financial inclusion because individuals who are more educated are better able

to their decision People had to be careful with the limited financial resources provided by education service providers in the form of a scholarship or a study loan to cover university and personal expenses that are critical to their education and financial success (Hazudin, Tarmuji, Kader, Majid, Aziz & Ishak, 2018).Spending is spending will increase students' financial inclusion Households with very limited resources will prioritize spending their resources to resolve food security and health problems rather than buy a mobile phone (Abor, Amidu & Issahaku, 2018; Duflo, 2012)

Table 1.2 Summary of previous research on financial inclusion

Region Regime place

Variables Method

regression

Result

Gender;

Education;

Age; Finacial literacy, Financial inclusion, Growth

PLS-SEM Financial

literacy has an important role in creating

financial inclusion and also providing better

opportunities for business

development for business actors

Qualitative Method

Financial inclusion can be seen as having three different levels At the third level, financial literacy involves rational use of financial services

Lyons,

Grable &

24,047 respondents

Finacial literacy, Financial

Analysis regression

indicated that there is evidence

that financial literacy and how

it is defined can have different effects

depending on how financial inclusion is also defined

Lyons &

Kass-Hanna

(2019)

131,191 observations

countries and 12,377

observations for the MENA countries (The Global

Findex,2014)

Financial literacy;

Financial inclusion;

Economically vulnerable

Probit regression

Financial literacy was also associated with a higher

probability of formal

borrowing among women and a lower probability of informal

borrowing among youth and the less educated Grohmann.,

Klühs &

Menkhoff

(2018)

1,000 adults per country in

143 countries

of the world

Variables:

Financial literacy;

Qualitative Method;

OLS regression;

Improving financial literacy could be an important

instrument of

(The World Bank, 2014

financial inclusion

regression

IV-financial development in addition to the more

conventional

expanding financial inclusion

Variables:

Financial literacy;

cognition;

financial inclusion

Hierarchical regression

cognition in the relationship between financial literacy and financial inclusion

(Source: The author synthesized)

2.4 Summary

This chapter provides a theoretical overview of the research topic There are also discussions of empirical findings on widespread financial inclusion, financial literacy Furthermore, previous research on empirical relationships between financial inclusion, financial literacy are also discussed

CHAPTER 3: RESEARCH METHODOLOGY

3.1 Research Data

The data for this study was collected from participants via an online survey This study's survey is an open, self-selected, unrestricted survey that anyone can take There are no restrictions on who can participate in these types

of surveys, and it is entirely up to the individual to decide whether or not to participate This type of survey's sample is certainly not generalizable, but it does provide data that would be difficult to obtain in any other way (Fricker, 2008) Data collect more than 600 students took part in the survey, only 567 questionnaires were accepted for analysis Respondents were excluded from the study mainly because they did not respond, or were of different age or profession than the stated research objectives When regions were selected for this study, it was for the purpose of drawing conclusions about the nature of these regions

We selected three regions based on the bank's distribution density for comparison: Ho Chi Minh city, Vinh Long and Lai Chau However, in Lai Chau

area, the number of respondents is very small In detail, Ho Chi Minh City is

home to the highest distribution of banks (1953), the medium is Vinh Long (104) and the lowest is Lai Chau (31) (Viet Nam Banking Network, 2021)

The Google online survey tool was used to create the survey, and it was hosted on the Google survey platform, which is a free survey creation and hosting platform The survey questions were based on the findings of the literature review and were tweaked to fit the needs of this study

3.2 Regression method

3.2.1 Binary logistic model

The probability of the binary logistic models is essentially described by

yi =1, though they are frequently derived from an underlying latent variable model (see below) For function G(yi) (1) the formula is shown

P{ yi = 1| xi} = G(xi, β) (1) The probability of having yi = 1 is determined by the vector xi containing individual characteristics, according to this equation Clearly, the function G(.)

in (1) should take on values in the interval (0, 1) only Usually, one restricts attention to functions of the form G(xi, β) = F(xi, β) As F (.) also has to be between 0 and 1, it seems natural to choose F to be some distribution function Common choices are the standard normal distribution function

F(w) = L(w) = 𝑒

𝑤 1+𝑒 𝑤 ’ (3) The logit model is the result of this A uniform distribution with distribution function over the interval (0, 1) is the third option

F(w) = 0, w < 0 F(w) = w , 0 ≤ w ≤ 1 (3) F(w) = 1, w > 1

This results in the so-called linear probability model If xi’β exceeds the lower or upper limits, the probabilities are set to 0 or 1

The coefficients in these binary choice models are difficult to interpret directly, aside from their signs Consider the partial derivative of the probability that yi equals one with respect to a continuous explanatory variable, say xik, to interpret the parameters (and to make comparisons between different models easier) We get the following results for the three models above:

𝜕∅(𝑥′𝛽)

𝜕𝑥𝑖𝑘 =∅( xi’β) 𝛽𝑘

as a dummy, can be determined by computing the implied probabilities for the two different outcomes while fixing the values of all other explanatory variables (Verbeek, 2008)

3.2.2 Model specification

The data was analyzed using a logistic regression model, which is an econometric model constructed using an iterative maximum likelihood procedure Logistic regression generates the coefficients of a formula to predict a logit transformation of the probability of the presence of the characteristic of interest, and uses the following equation to generate coefficients with standard errors and significance levels to predict a logit transformation of the probability of occurrence:

𝐿𝑜𝑔𝑖𝑡(𝑝) = log ( 𝑝

1 − 𝑝) = 𝛽0+ 𝛽1𝑋1+ 𝛽2𝑋2+ 𝛽3𝑋3+ ⋯ + 𝛽𝑘𝑋𝑘Where: p is probability of an event to occur The logit transformation is defined as the logged odds:

𝑜𝑑𝑑𝑠 = ( 𝑝

1 − 𝑝)

p = probability of an event to occur (scoring higher than the median score)

1-p = probability of an event not to occur (scoring equal or lower than the median score) and

FI i is the financial inclusion score;

FLi is the financial literacy score, if participant had scores higher than the sample median take value “1”, the others “0”;

Xi is a vector of control variables; and ni is the error term

Table 2.1 Summary of variable in the research

compouding

Correct answer = 1;

wrong = 0

Van Rooij et al (2011)

Allgood & Walstad, (2016)

Time value of

money

Understanding time value of money

Correct answer = 1;

wrong = 0

Van Rooij et al (2011) Atkinson et al (2012)

Diversification Understanding

diversification

Correct answer = 1;

wrong = 0

Van Rooij et al (2011) Atkinson et al (2012)

Financial

technology

Mobile phone Using mobile

phone service to pay for orders

1= if yes;

0=otherwise

Asongu & Odhiambo (2018); Asongu & Nwachukwu (2018);

Demir, Pesqué-Cela, Altunbas, & Murinde (2020)

0=otherwise

Ergün, K (2018) Allgood & Walstad, (2016)

Education level Education level of

respondents

Altunbas, & Murinde (2020)

Field of study Field of study of

the respondent

1= if related finance;

0=otherwise

Demir, Pesqué-Cela, Altunbas, & Murinde (2020)

Ergün, K (2018)

study 2

Finance your study

by student loan

1=if related ; 0=otherwise Finance your

study 3

Finance your study

by family

1=if related ; 0=otherwise Employment

status

Employment status

of the respondent

1= if haved a job;

0=otherwise Current place Current place of

the respondent

Ergün, K (2018) Kodongo (2018)

Current place 1 Rental house 1=if related ;

0=otherwise Current place 2 Dormitory 1=if related ;

0=otherwise Current place 3 Famliy 1=if related ;

0=otherwise Monthly

Abor, Amidu & Issahaku, (2018)

Spending 1 1 million – 2

million

1=if related ; 0=otherwise Spending 2 2 million – 3

million

1=if related ; 0=otherwise Spending 3 3 million – 4

million

1=if related ; 0=otherwise Spending 4 >4 million 1=if related ;

0=otherwise (Source: Synthesized by the author)

3.3 Testing

3.3.1 Omnibus Tests

There is an omnibus test statistic to determine whether the overall model

is significant, similar to linear (or curvilinear) regression The F-statistic from an ANOVA is used in linear regression, whereas a chi-square statistic is used in logistic regression to determine whether the model and its predictors are

significantly greater than the constant alone In addition to the constant, a regression coefficient is calculated for each predictor variable Individual values (e.g., scores on the predictor variables) can then be used to calculate the predicted probability of being assigned to a specific group on an individual basis (Maroof, 2012)

The Omnibus Tests of Model Coefficients is used to check that the new

model (with explanatory variables included) is an improvement over the baseline

model It uses chi-square tests to see if there is a significant difference between

the Log-likelihoods (specifically the -2LLs) of the baseline model and the new model If the new model has a significantly reduced -2LL compared to the baseline then it suggests that the new model is explaining more of the variance

in the outcome and is an improvement Value sig in the model is tested for whether it has any effect If sig value less than 0.05 that means it has some discernible effect If the sig value is greater than 0.05 it means it is not significant (Maroof, 2012)

3.3.2 Hosmer and Lemeshow Test

The Hosmer and Lemeshow test is basically a way of ascertaining how

well the data fits the model It is calculated using the deviance (-2LL) and produces a p-value based on a chi-square distribution It tests the null hypothesis that the model is a good enough fit for the data As usual, we only

reject the null hypothesis if p<0.05, so in this case the model is a good fit if the p value is greater than 0.05 (p>.05) (Hosmer, Lemeshow & Sturdivant, 2013)

3.4 Summary

This chapter focuses on the methodology that was used to carry out the study

It includes the study's research approach and design, as well as the data source, model specification, and measurement of the variables under consideration It also specifies the empirical estimation techniques used in the study