INTRODUCTION
Problem Statements
Foreign language currently is a prominent issue in worldwide education and society
The rapid advancement of information and communication technologies has brought nations closer together, facilitating understanding through a common language, primarily English Most knowledge, including books, academic papers, and documentation in various fields such as economics, science, and culture, is predominantly available in English and widely shared on global networks Bolton (2006) described the expansion of English as the fastest spread of any language worldwide This common language enables effective communication among speakers of different languages, fostering long-term cooperation As of 2003, English was recognized as the most widely spoken language globally, with over 1.226 billion users.
According to Crystal (2003), English is spoken in 75 countries worldwide, and Graddol (2008) predicts that the number of people learning English as a second language will approach two billion in the next decade Additionally, some Eastern European countries have replaced Russian with English as a school subject (Modiano, 2006) Recognizing the importance of English education, Nergis (2011) emphasizes the need for government investment in this area In developing countries like Turkey, there is a consensus that enhancing English proficiency is essential for meeting modern communication demands, facilitated by the Turkish language reform.
In Vietnam, Thinh (2006) noted a remarkable increase in the spread of English over the decade leading up to the country's accession to the WTO Statistics indicate that over 90% of foreign language learners in Vietnam are studying English, significantly outpacing other languages such as Chinese, Japanese, and French.
The demand for English language skills has surged in Ho Chi Minh City, with over 900,000 learners enrolling in language centers due to the need for job opportunities and overseas studies This trend has led to the implementation of English teaching programs in universities, high schools, and government agencies Following Vietnam's accession to the WTO and the adoption of open policies, a significant influx of foreign investors has entered the domestic market, necessitating a qualified labor force capable of effective communication with international partners Consequently, learning foreign languages has become a pressing issue in the context of today's global economic integration.
Recognizing the need for English language development, many parents are planning for their children a foundation of language, namely English, since they start school
This study aims to explore the significance that parents in Ho Chi Minh City place on English education by examining their financial investment in their children's English language learning at the primary school level The findings will highlight the crucial role of English language education in fostering national development, emphasizing the need for both individual and governmental support and investment in this area in Vietnam.
Research Objectives
General objective: To investigate household’s expenditure on English language education for children at starting school age (primary school)
(1) To identify the importance of English language education in a household’s decision
This study aims to identify the factors influencing household expenditure on English education for primary school children in Ho Chi Minh City.
Research Questions
This study investigates the influence of various demographic factors, including parents' income, working environment, English proficiency, age, gender, marital status, location, home ownership, and employment status, on the financial investment in English education for their children It aims to determine whether these factors significantly affect educational expenditures and to quantify their contributions.
Research methodology
This study bases on Pritchett and Filmer (1999)’s theory of education expenditure
This study employs both descriptive statistics and regression analysis to assess the significance of English education and its expenditure determinants among households in Ho Chi Minh City Initially, descriptive statistics provide an overview of English education spending relative to total income and expenditure, along with household characteristics Subsequently, ordinary least squares (OLS) regression identifies influential factors affecting English language expenditure for primary school children Additionally, logit regression examines the impact of these determinants on households' decisions to invest in English education Finally, ordered logit regression addresses the issue of non-continuous, ordered expenditure levels, ranking English education spending from zero to six, with unequal intervals between levels.
The structure of the study
This study is structured into five chapters, beginning with an introduction in Chapter 1 Chapter 2 examines three key theories related to education expenditure, including the household production function and the income elasticity of education spending, while also referencing recent empirical research on education expenditure in Vietnam and globally Chapter 3 focuses on the research methodology, detailing data collection methods, variable explanations and measurements, as well as model specifications.
Chapter 4 will provide an overview of education in general, with a specific focus on English education in Ho Chi Minh City It will examine influential factors such as parents' total income, expenditure, education level, English proficiency, and various demographic characteristics of households that may impact the expenses related to English education for children at the primary school age.
LITERATURE REVIEW
Theoretical literature
In order to comprehend the purpose of this research, we first discuss education expenditure theories
Theory of Education expenditure: Education production function
Pritchett and Filmer (1999) introduce a theory of education expenditure through the education production function, which explains how various inputs contribute to educational outcomes This function examines the causal effects of both school inputs—such as teacher education levels, class sizes, teacher experience, and educational resources like textbooks—and non-school inputs, including family background, environmental factors, and children's innate abilities, on student achievement.
The specific function of education production is defined as below:
In this context, Cit represents children's outputs, Sit signifies school inputs, Fit refers to non-school inputs (such as family contributions), and Ii indicates children's congenital abilities The term used encompasses the congenital variable that reflects a fixed contribution from students, as there are no available data sets to measure non-figurative variables like congenital ability.
Theory of household production function
Becker (1965) and Muth (1966) introduced a household production function model to illustrate how commodities purchased in the market serve as inputs for household production Specifically, they applied this model to the production function of child health, demonstrating its significance in understanding household dynamics.
Whereas, Yj are other good affect child’s health; Ik present for health input and à is the family-specific health endowments such as genetic characteristics or environmental factors
Later on, from this household production function, they developed household’s reduced-form demand function:
Zt = St ( p, F, à) Whereas, p is the price of goods or services; F is the exogenous income and à is the family specific endowment
To measure household expenditure on English language education, we consider education as a consumable good This analysis examines various factors influencing the household production function, including household income, family-specific endowments, and demographic variables Specifically, the family-specific endowments analyzed include the English proficiency of parents, reflecting genetic characteristics, and the parents' working environment, representing environmental influences.
Theory of income elasticity of educational expenditure:
Benson (1961) highlights that household income significantly influences educational expenditure, as indicated by the income elasticity of education Income levels are categorized into low, middle, and high Specifically, low and high-income households typically exhibit an income elasticity of education ranging from zero to one, while middle-income households demonstrate a different elasticity value.
Middle-income families tend to prioritize their children's education, often spending more on it compared to other income groups In contrast, low-income families show less concern for the quality of schooling, leading to a predicted increase in education expenditure that is lower than their total income.
Use the Lorenz curve to measure the distribution of income to the education expenditure The form of income elasticity of educational expenditure as follows:
Whereas E i is the elasticity of income v i (x) is the Engel function of the i expenditure items.
Empirical literature
This research aims to analyze the expenditure on English language education, viewing it as a human capital investment, as highlighted by Espenshade (1997) The study emphasizes that the costs associated with this investment and the expected returns vary among individuals Given the complexity of English education expenditure, it cannot be explained by a single independent variable While previous studies have focused on general education expenditure, there is a lack of detailed research specifically addressing English language education According to Kanellopoulos (1997), Tansel (2006), and Donkoh (2011), factors such as household income, expenditure, parental education, employment sector, employment status, age and gender of the household head, maternal employment, household size, and homeownership significantly influence educational spending Building on these findings, this study incorporates these independent variables to develop a new model for understanding English language education expenditure.
8 determinants of spending on English language education We will talk about the specific model later in the methodology section
Household income significantly influences education expenditure, as wealthier families prioritize enhancing their living standards Investing in education is a key focus for these households, aiming to benefit future generations (Donkoh, 2011) Research by Glewwe (1999) and Tansel and Bircan supports this correlation.
(2006) and Donkoh and Amikuzuno (2011) found that when the household’s income rise they are more willing to pay for the private tutoring
The income educational expenditure elasticity of households serves as a key measure to assess the influence of income on education spending Research, particularly by Hashimoto and Heath (1995), indicates that middle-income households exhibit the highest income elasticity for education expenditure, exceeding one, while lower and higher income classes show elasticity values between zero and one This suggests that middle-income households increase their education spending more significantly with income growth compared to other income groups, who appear less concerned about the quality of their children's education In Greece, Kanellopoulos and Psacharopoulos (1997) reported an elasticity of 3.18, while Hashimoto and Heath (1995) found a value of 2.35 in Japan, both concluding that education expenditure is a luxury good However, Tansel and Bircan (2006) challenged this notion, identifying a unitary elasticity of income on education demand.
Hence, they conclude education is not a luxury good in the case of Turkey as it is discovery in some researches
Household total expenditure tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
This research examines the significance of informal English language education, particularly private tutoring Stevenson and Baker (1992) highlight that households are willing to invest more in informal educational activities to ensure their children achieve higher education and successful careers Consequently, the likelihood of increased spending on educational activities correlates with household expenditure levels On average, families allocate approximately 11.2% of their total expenditure to tutor fees for additional educational support, with over sixty-three percent of this amount dedicated to foreign language education, as noted by Kanellopoulos and Psacharopoulos (1997) Their findings indicate a strong relationship between parents' educational spending and their overall financial outlay.
To address the issue of simultaneous bias between total and individual expenses, some researchers advocate for the use of instrumental variables, such as household income (Liviatan, 1961) Tansel and Bircan (2006) tested the exogeneity of total household expenses using a Tobit model, as defined by Smith and Blundell (1986) Their methodology involved two steps: first, regressing total spending on household income, and second, incorporating the residuals from this regression into the Tobit model for additional education spending Their findings indicated a significant result at the one percent level, leading them to conclude that total household expenses should be used as an explanatory variable rather than household income.
Numerous studies, including those by Knight and Shi (1996), Kanellopoulos and Psacharopoulos (1997), Tansel and Bircan (2006), Qian and Smyth (2011), and Donkoh and Amikuzuno (2011), have examined the relationship between education expenditure and parental education levels The majority of these studies consistently demonstrate a positive correlation between parental education and their financial investment in their children's education Notably, Knight and Shi (1996) emphasize this relationship in their findings.
Parental educational attainment significantly influences children's education expenditure, with fathers' education having a greater impact than mothers' According to Kanellopoulos and Psacharopoulos (1997), households led by individuals with higher education levels are more inclined to allocate a larger portion of their income towards their children's education Specifically, each additional year of education for the household head correlates with a 2.2% increase in the likelihood of families agreeing to invest in educational expenses.
Research highlights the significant influence of a mother's education on decision-making regarding spending on education According to Qian and Smyth (2011), households where mothers possess senior secondary or college education tend to allocate more resources towards their children's education.
Donkoh and Amikuzuno (2011) assert that individuals with higher education are more likely to provide their children with similar educational opportunities, fostering expectations for them to achieve advanced levels of education.
Research by Kanellopoulos and Psacharopoulos (1997) and Andreou (2012) indicates that households in the private sector are more likely to invest in their children's education.
Qian and Smyth (2011) discovered that households with fathers in professional occupations tend to allocate more resources towards education Their research highlights the significant role of the private sector as a key determinant in the working environment of the household head.
According to Kanellopoulos and Psacharopoulos (1997), Donkoh and Amikuzuno
The occupation of parents significantly influences a household's willingness to invest in their children's education There are two perspectives on this matter: one suggests that higher occupational status positively impacts educational investment, while the other indicates that lower-class households may face challenges in supporting their children's educational pursuits.
Many parents compensate for their lack of education by investing more in their children's schooling However, this can lead to negative financial consequences Upper-class parents often perceive education as having less value compared to their household wealth, leading them to overlook its importance Despite this, Andreou (2012) argues that parental occupation does not significantly influence private spending on education.
Many studies highlight the age of the household head as a crucial factor influencing educational investment Research by Kanellopoulos and Psacharopoulos (1997), Donkoh and Amikuzuno (2011), and Andreou (2012) indicates that an older head of household tends to negatively impact spending decisions related to education.
Donkoh and Amikuzuno (2011) analyze the impact of age on household spending for education, finding that older household heads are less willing to invest in education They suggest that younger household heads tend to be more progressive and recognize the long-term benefits of education compared to their older counterparts.
Conceptual framework
This study aims to examine the relationship between private expenditure on English education and various explanatory variables.
Figure 2.1 Analytical framework for the impact explanatory variable on English education expenditure
Age Gender (dummy V) Marital status Location (dummy V) Home ownership (dummy V) Employment status Number of children
PRIVATE EXPENDITURE for English language Education
Demographic Factors tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
RESEARCH METHODOLOGY
Sampling strategy and data collection
The study employed primary data collection through face-to-face surveys, utilizing a questionnaire that addressed key aspects such as total household income, parents' education and English proficiency levels, parental careers, and various demographic factors including age, gender, and marital status The surveyed households consisted of families with children enrolled in pre-primary and primary education in Ho Chi Minh City Participants were randomly selected from different districts and sub-districts, ensuring a representative sample by choosing households based on the number of residences within a randomly chosen ward of each district.
20 households were interviewed in each districts/sub-districts The internal districts in Ho Chi Minh City comprise district one to twelve, Tan Phu, Tan Binh, Binh Tan, Binh Thanh,
Go Vap, Phu Nhuan The sub-districts include Binh Chanh, Hoc Mon, Cu Chi, Nha Be whereas we excluded the Can Gio’s observation because of its low population density
In cases where a household does not have children of primary school age, we seek responses from the next neighboring house If the subsequent three houses also lack children in the target age group, we will consider that sample as empty Additionally, some selected households may choose to leave the response sheet blank due to personal reasons As a result, certain districts did not meet the required 20 responses, leading to a total of 267 observations for this study A table of the questionnaires will be included in the annex.
Variables’ measurement and explanation
3.2.1 Current expenditure on English education
Expenditure on English is a complex and varied investment in human capital, as noted by Espenshade and Fu (1997) This investment encompasses both the costs incurred and the anticipated returns associated with it.
This study investigates the factors influencing English education expenditure, building on previous research by Kanellopoulos and Psacharopoulos (1997), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011) It examines variables such as total household income, total expenditure, parents' education levels, employment sectors, age and gender of the household head, maternal employment status, household size, and homeownership The aim is to determine how these factors affect spending patterns on English education within households.
This study assesses parental interest in children's English education by analyzing current expenditure levels, categorized into six distinct tiers A level of zero indicates no spending on English education, while level one represents expenditures ranging from 0 to 300,000 VND Level two encompasses spending from 300,000 to 500,000 VND, and level three includes amounts from 500,000 to 1,000,000 VND Level four covers expenditures from 1,000,000 to 2,000,000 VND, and level five signifies spending above 2,000,000 VND These classifications are derived from the average fees for extra English classes at schools and English centers, with data collected from ten schools and eleven English centers catering to primary children at the beginning and pre-intermediate levels.
See the list of school and English center in the appendix
The influence of household income on education expenditure is significant, as wealthier households tend to improve their living standards, with education being a key area of investment (Donkoh and Amikuzuno, 2011) Research by Glewwe and Desai (1999), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011) indicates that as household income increases, families are more inclined to invest in private tutoring.
English education is a form of private tutoring that is significantly influenced by a household's total income To assess the impact of income on education expenditure, two evaluation methods are employed: direct and indirect evaluation The direct evaluation utilizes Ordinary Least Squares (OLS) and Probit/Logit models to measure the effect of all income levels on current payments for English education In contrast, the indirect evaluation categorizes income into low, middle, and high brackets to calculate the income elasticity of English education expenditure using the Tobit model.
In this study, the household’s total income variable is also divided into five levels:
In the direct evaluation method, income levels are categorized into four brackets: below 5,000,000 VND, from 5,000,000 VND to 10,000,000 VND, from 10,000,000 VND to 20,000,000 VND, and over 20,000,000 VND Conversely, the indirect evaluation method classifies income into three categories: low, middle, and high income.
According to the World Bank's 2012 classification, low-income countries are defined as those with a Gross National Income (GNI) per capita of $1,035 or less, while lower middle-income countries fall within a specific range above this threshold.
Income classifications are categorized as follows: low income ranges from \$1,036 to \$4,085; upper middle income spans \$4,086 to \$12,615; and high income starts at \$12,616 In Vietnamese Dong (VND), this translates to lower income at 1,811,250 VND per person per month or less; lower middle income from 1,813,000 to 7,148,750 VND; upper middle income from 7,148,750 to 22,076,250 VND; and high income at 22,078,000 VND or more The low income group is defined as level (1), below 5,000,000 VND, while the middle income group includes levels (2), (3), and (4), and the high income group is classified as level (5).
Previous empirical studies indicate that middle-income households exhibit the highest income elasticity of education expenditure, with a value exceeding one In contrast, lower and higher income classes show an elasticity ranging from zero to one This suggests that as income increases, middle-income households significantly increase their education spending compared to other income groups Additionally, it appears that lower and higher income households are less concerned about the quality of their children's education, as noted by Hashimoto and Heath.
In 1995, some studies indicated that there was no significant difference in education demand among various income groups This paper aims to explore the factors influencing education demand, particularly focusing on the implications of these findings.
The study investigates whether an 18% increase in income would positively impact expenditures on English education and examines the differences in income elasticity of English expenditure among low, middle, and high-income groups Based on theoretical frameworks and previous empirical research, the study aims to test this hypothesis.
H1: The household’s total income has positive relationship with the English education expenditure children
This research highlights the correlation between total household expenditure and spending on English education Stevenson and Baker (1992) found that households are willing to invest more in informal educational activities when they anticipate their children pursuing higher education and successful careers As a result, the likelihood of spending on educational activities increases with the household's expenditure level Kanellopoulos and Psacharopoulos (1997) noted that over sixty-three percent of total educational spending is allocated to foreign language education Therefore, it is evident that parents' investment in their children's education significantly rises in tandem with their overall household expenses.
In this study, we utilized multiple-choice options to assess total expenditure, based on the 2010 VHLSS dataset The total expenditure is categorized into six levels: (1) below 2,000,000 VND, (2) from 2,000,000 VND to 3,500,000 VND, (3) from 3,500,000 VND to 5,000,000 VND, (4) from 5,000,000 VND to 10,000,000 VND, and (5) over 10,000,000 VND We aim to investigate two key aspects: first, whether a positive relationship exists between household total expenditure and English education expenditure; second, whether the simultaneous consideration of total and individual expenses introduces bias when using income as an instrumental variable, as suggested by Liviatan (1961) To achieve this, we will employ the Tobit model, as proposed by Tansel and Bircan (2006), to test the exogeneity of household total expenditure.
Smith and Blundell (1986) outline a two-step process for analyzing household spending The first step involves regressing total spending against household income In the second step, the residuals from this regression are incorporated into a Tobit model to assess the significance of additional education spending If the regression results indicate a significant rejection of the null hypothesis, total household expenses can be utilized as an explanatory variable in place of household income.
In summary, the study is going to test the proposed hypothesis as following:
H2: The level of household’s total expenditure has positive relationship with the English education expenditure
H3: The current expenditure on extra education relates to the English education expenditure
Many studies found the positive impact of parental education to their spending for children’s education such as Knight and Shi (1996), Kanellopoulos and Psacharopoulos
(1997), Tansel and Bircan (2006), Qian and Smyth (2011) and Donkoh and Amikuzuno
Knight and Shi (1996) emphasized that a father's education plays a more significant role than a mother's education Consequently, this study explores the relationship between parents' education levels and their investment in English education expenditures.
Model specification
To investigate the impacts of all suggested independent variables to the English education expenditure, this study use five models to test the twelve proposed hypotheses
This study utilizes the ordinary least squares (OLS) method to identify the influential factors affecting English language expenditure among primary school children The OLS model specifically analyzes the relationship between explanatory variables and English expenditure To assess the impact of these determinants on household decisions regarding English education spending, a logit regression is employed, as the standard OLS model is insufficient for this purpose Additionally, an ordered logit regression is applied to address the issue of the dependent variable, English education expenditure, being ordered rather than continuous, with expenditure levels ranked from zero to six, indicating unequal intervals between them The general model is structured accordingly.
In this study, E signifies the current payment for English education, while X represents the income variable Y indicates the English proficiency level of parents, and Z refers to their working environment Additionally, T encompasses various demographic factors, including parents' age, the gender of the household head, whether the wife is employed, the number of children, household location, and ownership status.
Various regression methods are utilized to achieve the research objectives, starting with the application of Ordinary Least Squares (OLS) regression to examine the relationship between dependent and independent variables.
In this case, there are two specific models employed as following:
Model 1: OLS model 1 tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Model 3 and model 4: Logit models with income (model 3) and expenditure (model 4)
The logit regression is utilized to examine the impact of various determinants on households' decisions to invest in English language education Given that the spending decision is a binary variable (0-1), a logit model is employed for this analysis Unlike ordinary least squares (OLS) regression, this model estimates the probability (P) of household expenditure on education based on different characteristics.
The probability of a household's spending on education, denoted as P, is influenced by various independent variables, including household characteristics such as income, age of the household head, gender, and location, as outlined by Kanellopoulos and Psacharopoulos (1997) This analysis is conducted through two regression models: Model 3, which examines income and other explanatory variables, and Model 4, which assesses total expenditure alongside other explanatory factors for comparison The marginal effects of each explanatory variable are calculated post-logit model to determine their impact on English education expenditure.
This study categorizes English education expenditure into six ordinal levels, ranging from zero to five, making it an ordinal dependent variable Consequently, the ordered logit model is appropriate for examining the relationship between this ordered dependent variable and the independent variables.
The ordered outcomes are modeled as a linear function of explanatory variables and cutpoints As noted by Fu (1998), the likelihood of observing a specific outcome is determined by the estimated independent variables along with an error term, relative to the defined cutpoints This relationship can be expressed through a specific function.
In this study, the variable \( cpe_j \) represents the current expenditure for English education, categorized as follows: 0 indicates no expenditure, 1 signifies expenses below 300,000 VND, 2 represents expenses ranging from 300,000 VND to 500,000 VND, 3 denotes expenses from 500,000 VND to 1,000,000 VND, 4 corresponds to expenses between 1,000,000 VND and 2,000,000 VND, and 5 indicates expenses exceeding 2,000,000 VND The independent variables \( x_1, x_2, \ldots, x_{kj} \) include factors such as the household's total income, total expenditure, current payments for extra classes, parents' education levels, parents' English proficiency, and various demographic characteristics, including parents' ages, the gender of the household head, whether the wife is employed, the number of children, household location, and ownership status The coefficients \( \beta_1, \beta_2, \ldots, \beta_k \) represent the explanatory power of these variables.
The cutpoints \( K_1, K_2, \ldots, K_{k-1} \) are essential in the analysis, while \( u_j \) represents the logistically distributed error term For the latest updates and resources, please contact via email at z z vbhtj mk gmail.com regarding the master's thesis and related inquiries.
Table 3.1: Variable description and expected sign for Model 1
Variable name Description Units Expected sign
CPE Current payment for English education VND dIncome2 Dummy household’s total income variable Equal to income rank from
5,000,000 to 10,000,000; otherwise equal to income below 5,000,000 VND Positive (+) dIncome3 Dummy household’s total income variable Equal to income rank from
10,000,000 to 20,000,000; otherwise equal to income below 5,000,000 VND Positive (+) dIncome4 Dummy household’s total income variable Equal to income rank over
20,000,000; otherwise equal to income below 5,000,000 VND Positive (+) dtotalexp2 Dummy total expenditure variable Equal to rank from 2,000,000 to
3,500,000; otherwise equal to income below 2,000,000 VND Positive (+) dtotalexp3 Dummy total expenditure variable Equal to rank from 3,500,000 to
5,000,000; otherwise equal to income below 2,000,000 VND Positive (+) dtotalexp4 Dummy total expenditure variable Equal to rank from 5,000,000 to
The total expenditure variable, denoted as dtotalexp5, is positive when income exceeds 10,000,000 VND, while it remains positive for incomes below 2,000,000 VND Current payments for extra education, represented as cpec, also show a positive correlation Additionally, the education level of the wife, ranked from 1 to 8, is positively associated with these variables.
The education level of the husband is categorized into eight ranks, ranging from 1 to 8 Additionally, there are two dummy variables for English proficiency: the first indicates whether the husband knows English, assigned a value of 1 for proficiency and 0 for non-proficiency, while the second variable reflects the wife's English knowledge, following the same coding system.
The article discusses various variables affecting household dynamics The variable "dwifeworking" indicates the wife's employment status, with a positive impact when she stays at home (equal to 1) and zero otherwise The "dlocal" variable reflects the household's location, showing a positive effect if situated in an urban area (equal to 1) and zero if not The ages of the husband and wife, represented by "ageh" and "agew," respectively, have a negative influence on household outcomes Lastly, the "ownh" variable signifies homeownership, positively impacting the household if they own a house (equal to 1) and zero if they do not.
Nchildren Number of children Child (+)/(-)
Source: Author analysis tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
EMPIRICAL ANALYSIS RESULTS
General information of the Household’s characteristic in HCM City
A recent survey in Ho Chi Minh City reveals that parents of primary school-aged children predominantly hold senior high school and university degrees The educational attainment of husbands and wives is nearly equal, although husbands generally have a higher level of education Specifically, 29.96% of husbands have completed university, compared to only 25.09% of wives Notably, 7.87% of households have husbands with a Doctor of Physical degree, while no wives have reached this level of education.
A comparison of the Vietnam Household Living Standard Data Set (VHLSS 2010) reveals key insights about family education levels: (1) husbands generally have a higher education level than their wives; (2) in Ho Chi Minh City, parents' education levels are predominantly concentrated in no education, primary, junior high, and senior high school, with university-educated parents representing a significant 11.69% of the total.
Figure 4.1 The education level of the parents in Ho Chi Minh City – Author’s survey 2013
Figure 4.2 The education level of the parents in Ho Chi Minh City – VHLSS 2010
General information of English education in Vietnam
In Vietnam, English is a mandatory subject in both junior and senior high schools The period from 1982 to 2002 marked significant developments in the English education curriculum.
Vietnam has implemented two English learning programs: a three-year program for students in grades 10 to 12 and a seven-year program for those starting in grades 6 to 12 Since 2002, English has been a mandatory subject in junior and senior high schools, while also being offered as an elective in primary schools In primary education, English is taught from grades 3 to 5 with two periods per week, increasing to three periods per week in junior and senior high schools This comprehensive English language teaching program aims to equip students with a foundational knowledge of English, enabling them to proficiently use the language across four skills: listening, speaking, reading, and writing, and to comprehend textbooks at a similar level with the aid of a dictionary.
The Ministry of Education and Training (MOET) reports a significant increase in foreign language centers in Vietnam, rising from 843 to 1,935 between 2008 and 2013 This growth is part of the National Foreign Languages 2020 Project, established by Decision No 1400/QD-TTg on September 30, 2008, aimed at enhancing foreign language education within the national system from 2008 to 2020 The project seeks to develop a comprehensive qualifications framework for foreign languages, featuring six levels that align with international language proficiency standards, promising substantial potential for success in improving English education in the country.
To enhance foreign language proficiency, it is essential to establish and enforce new compulsory training programs at the basic school level These programs should aim to ensure that students graduate with the following qualifications: Level 1 for primary school, Level 2 for junior high school, and Level 3 for senior high school, in accordance with the foreign language qualifications framework.
Thirdly, implement training according to new foreign language program for the university
Establish and implement teaching by English in some basic subjects and major subjects for the last year student of university
The current state of English teaching and learning in Vietnam remains inadequate In addition to formal education, many parents seek to enhance their children's English skills through various resources and support.
Vietnam is experiencing a significant demand for English education, leading to the establishment of numerous domestic and international language centers Prominent institutions like the British Council, VUS, VASS, Apollo, and ILA are operating successfully in Ho Chi Minh City and Hanoi, with plans for substantial national expansion Additionally, many smaller centers and home-based English education options have emerged to cater to this growing need, resulting in a diverse landscape of both private and public educational offerings.
Table 4.1 The development of number of foreign language center through the years
Source: Ministry of Education and Training
Importance of English expenditure in household’s decision
In Ho Chi Minh City, the current expenditure on English education significantly contributes to the overall educational spending of households, as illustrated in Figure 4.3.
Basic education accounts for an average of 61.4% of total school education fees In relation to household finances, it represents 4.7% of total income and 6.7% of total expenditure The study indicates that English education is viewed similarly to private tutoring, with 84.7% of households willing to invest in English classes and 84.3% for other extracurricular activities Most spending falls within the range of 300,000 VND to 500,000 VND per month For detailed statistics, refer to the table in the appendix.
The distribution of current English education expenditure in basic education reflects the relationship between total income and total expenditure.
Empirical analysis results
This section presents the empirical analysis results and discussions, beginning with the descriptive statistics of the dependent and explanatory variables, along with their correlation matrix It then summarizes the estimated results from three regression models, including the marginal effects following the regressions and a detailed discussion of these findings.
This section outlines the descriptive statistics of the survey variables, providing essential information for subsequent model discussions The main dependent variable is illustrated through histogram graphics, while the explanatory variables are summarized in Table 4.1, which includes mean, frequency, maximum, minimum, and standard deviation Notably, 84.7% of households are willing to invest in their children's English education, with the majority spending 300,000 VND or less per month, representing approximately 41% of total households.
The histogram in Figure 4.4 illustrates the current expenditure on English education in Ho Chi Minh City The expenditure is categorized into six distinct ranges: 0 indicates no spending, while 1 represents expenditures from 0 to 300,000 VND, 2 covers 300,000 to 500,000 VND, 3 spans from 500,000 to 1,000,000 VND, 4 ranges from 1,000,000 to 2,000,000 VND, and 5 includes expenditures exceeding 2,000,000 VND.
Current payment for English tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Figure 4.5 Histogram graphic of the dummy variable of current payment for English education in Ho Chi Minh City (0 – no expenditure on English education, 1 – present expenditure on English education)
Dummy variable of current payment for English education
The survey shows that the groups of household which gain total income from 5,000,000 VND to 10,000,000 VND per month mostly predominate over the households in
In Ho Chi Minh City, the distribution of household total income reveals that the middle-income group constitutes nearly 70% of the population, making it the largest segment The low-income group follows with 23.60%, while the high-income group accounts for only 6.74% Among the five income categories, households earning between 5 to 10 million VND represent 40.07% of those surveyed The next largest groups include those earning below 5 million VND at 23.60% and those earning between 10 to 20 million VND at 20.60% Conversely, the highest income group, which earns over 30 million VND, has the lowest representation at just 6.75% This data underscores the predominance of the middle-income demographic in Ho Chi Minh City.
The total income distribution of households in Ho Chi Minh City is illustrated in Figure 4.6 This distribution is categorized into two distinct groupings: (a) five income brackets—below 5 million VND, 5 to 10 million VND, 10 to 20 million VND, 20 to 30 million VND, and over 30 million VND; and (b) three broader categories—low income, middle income, and high income.
The majority of surveyed households, accounting for 74.15%, spend between 3,500,000 VND and 10,000,000 VND per month, with 40.82% specifically in the 3,500,000 VND to 5,000,000 VND range This spending pattern aligns with the income distribution, as most middle-income families allocate their earnings towards essential activities such as food, education, and healthcare Additionally, there is a strong correlation between total income and total expenditure, indicating that as income increases, so does the demand for living expenses Notably, a significant portion of households invest in private tutoring for their children, with only 15.67% opting not to enroll them in extra classes.
The current interest of parents in their children's education is reflected in the increasing engagement and support they provide.
The study explores the demographic characteristics of households in Ho Chi Minh City, revealing that over 35% of parents are proficient in English, with husbands having a higher proficiency than wives In terms of education, 29.96% of husbands have completed university, while the percentage for wives is lower Employment data shows that 25.09% of husbands and 28.46% of wives work in the public sector, with 34.08% of husbands and 25.47% of wives employed by domestic companies; however, few work for foreign companies or NGOs, and about 25% are self-employed Additionally, 18.66% of wives are homemakers The survey indicates that 77.9% of household heads are male, with husbands aged between 26 and 58 years and wives between 25 and 55 years Furthermore, 75% of households reside in urban areas, and over 64% own their homes Lastly, the average number of children per household is 1.65, reflecting a trend towards smaller families with one to two children.
Table 4.2 Summary statistic of variables (a)
Cpe cpe0 cpe1 cpe2 cpe3 cpe4 cpe5
Income dincome1 dincome2 dincome3 dincome4 dincome5
Total expenditure dtotalexp1 dtotalexp2 dtotalexp3 dtotalexp4 dtotalexp5 dtotalexp6
1.50 8.99 40.82 33.33 11.99 3.37 cpec dcpec1 dcpec2 dcpec3 dcpec4 dcpec5
15.67 44.78 26.49 8.58 4.48 eduh Primary Senior HS Junior HS Primary VS College University Master PhD
6.74 15.36 28.84 8.99 0 29.96 2.25 7.87 eduw Primary Senior HS Junior HS Primary VS College University Master PhD
Englishh_0 38.20% husband know English 61.80% don’t know English
Englishw_0 35.96% wife know English 64.04% don’t know English
Private (Foreign.) NGOs Stay at home
Private (Foreign.) NGOs Stay at home
Wifeworking 81.34% wife are working 18.66% wife stays at home
Genderhh 77.9% HH are male 22.1% are female
Local 75% HH in urban 25% HH in Suburban
Ownh 64.18% own a house 35.82% not own a house
Table 4.2 Summary statistic of variables (b) Variable Mean Std Dev Min Max
Nrofchildren 1.65 0.90 1 5 tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Table 13 in the appendix illustrates the correlation among explanatory variables, revealing no significant relationships except for the education levels and ages of both spouses, which aligns with the social characteristics of Vietnam Additionally, the correlation matrix indicates that the highest income group tends to spend more, leading to a notable correlation between income group five and total expenditures in groups five and six This is further supported by the correlation between total expenditure and current payments for English education, reinforcing Benson's (1961) theory of income elasticity in education expenditure.
The article examines the relationship between household income, total expenditure, and spending on English education Table 4.2 clearly indicates that higher-income households allocate more funds to their children's English education Specifically, households earning below 5 million VND per month predominantly invest in low-level English education, with 37% spending under 300,000 VND monthly, 15% spending between 300,000 and 500,000 VND, and 27% spending nothing In contrast, households with incomes exceeding 30 million VND are more likely to invest significantly in English education, particularly in the 1,000,000 to 2,000,000 VND and over 2,000,000 VND categories Additionally, total household expenditure influences educational spending similarly, with higher expenditure correlating with increased investment in English education, while lower expenditure limits support for educational expenses.
Table 4.3 The relationship of total income and current payment for English education
Current payment for English education (VND)
20 - 30 millions VND 2% 8% 6% 23% 12% 0% over 30 millions VND 0% 3% 6% 3% 40% 25%
Table 4.4 The relationship of household’s total expenditure and current payment for
Current payment for English education (VND)
10 - 15 millions VND 2% 5% 13% 23% 36% 25% over 15 millions VND 0% 2% 4% 3% 12% 25%
Total 100% 100% 100% 100% 100% 100% tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
This chapter addresses the research questions posed in the first chapter and is grounded in the hypotheses outlined in chapter three The study emphasizes the significance of English education in Vietnam by examining how factors such as parents' income, working environment, English proficiency, and other demographic variables influence their spending on English education for their children Table 4.5 presents the results from two regression methods, as defined in the methodology section, to analyze the relationship between these explanatory variables and the current expenditures on English education for children in Ho Chi Minh City.
Table 4.5 The results of the models
Current payment for English education
Coefficient Coefficient Coefficient Marginal effect (dy/dx)
Coefficient Marginal effect (dy/dx)
(0.47) (0.09) (0.14) tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Current payment for extra class
0.327 *** 0.309 *** 0.368 0.020 0.188 0.011 (0.00) (0.00) (0.16) (0.18) (0.47) (0.48) Dummy English var of husband
0.009 0.049 -1.121 -0.069 -0.971 -0.063 (0.96) (0.80) (0.08) (0.14) (0.13) (0.18) Dummy English var of wife
-0.393 ** -0.356 * -0.489 -0.028 -0.267 -0.016 (0.04) (0.06) (0.42) (0.47) (0.68) (0.70) Dummy Public sector of husband
0.096 0.082 -0.365 -0.021 -0.300 -0.018 (0.60) (0.66) (0.59) (0.60) (0.64) (0.66) Dummy Public sector of wife
( * ): Statistic significance at 10% level, ( ** ): Statistic significance at 5% level, ( *** ): Statistic significance at 1 % level
Source: Author’s calculation tot nghiep down load thyj uyi pl aluan van full moi nhat z z vbhtj mk gmail.com Luan van retey thac si cdeg jg hg
Models 1 and 3 examine the relationship between total income and various explanatory variables, while models 2 and 4 focus on the connection between total expenditure and current spending on English education The findings from model 1 indicate a positive correlation between total income, current payments for extra education, and the education level of the wife with expenditures on English education Notably, households in the highest income bracket, earning over 20 million VND, show a statistically significant impact on English education spending at a 1% significance level This supports the assertions made by Glewwe and Desai (1999), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011) that higher income levels lead to a greater willingness to invest in extra education.
Model 1 indicates that spending on extra classes positively influences expenditure on English education at a 1% significance level Interestingly, a wife's English proficiency negatively impacts English education spending at a 5% significance level This phenomenon can be attributed to the characteristics of Vietnamese women, who often dedicate time to teaching their children at home Consequently, wives with higher English skills can educate their children themselves, leading to reduced costs for English education, aligning with Huy's research findings.
In 2012, the education level of a wife significantly influenced the willingness to invest in children's education, particularly in English education expenditures, with a notable significance at the 1% level.
The age of the wife positively influences the expenditure on English education, indicating that older wives are more willing to invest in their children's education This relationship is statistically significant at the 5% level Additionally, households that own their homes tend to allocate more funds towards English education Homeownership alleviates the financial burden of rent, allowing families to redirect their resources towards other priorities, such as their children's education.