INTRODUCTION
Problem Statements
Foreign language education, particularly in English, is a critical issue in today's global society The rapid advancement of information and communication technologies has brought nations closer together, enabling effective communication through English as a common language A significant portion of knowledge, including books, academic papers, and documentation across various fields such as economics, science, and culture, is predominantly published in English and widely accessible online Bolton (2006) noted that English is experiencing the fastest expansion of any language worldwide Furthermore, English facilitates communication among speakers of different languages, fostering long-term cooperation and understanding As of 2003, English was recognized as the most widely spoken language globally, with over 1.2 billion users.
According to Crystal (2003), English is now spoken in 75 countries, and Graddol (2008) predicts that the number of people learning English as a second language will approach two billion in the next decade Eastern European countries have also shifted to teaching English in schools instead of Russian (Modiano, 2006) Recognizing the significance of English education, Nergis (2011) emphasizes the need for government investment in this area In developing nations like Turkey, there is a consensus that enhancing English proficiency is essential for meeting modern communication demands, facilitated by the Turkish language reform.
In the decade leading up to Vietnam's accession to the WTO, the growth of English language learning in the country surged at an unprecedented rate, as noted by Thinh (2006) Statistics reveal that over 90% of foreign language learners in Vietnam are focused on English, significantly outpacing the popularity of other languages such as Chinese, Japanese, and French.
The growing demand for English language skills in Vietnam has led to over 900,000 learners enrolling in language centers in Ho Chi Minh City, driven by job opportunities and the need for overseas studies This trend has prompted the introduction of English teaching programs in universities, high schools, and government agencies Following Vietnam's accession to the WTO and the influx of foreign investments, there is an urgent need for a qualified labor force capable of effectively communicating and collaborating with international partners As a result, many parents are prioritizing English language education for their children from an early age to ensure they are well-prepared for the global economy.
This study aims to explore the significance parents place on English education by examining their financial investments in their children's English language learning at the primary school level in Ho Chi Minh City The findings will highlight the crucial role of English language education in fostering national development, emphasizing the need for both individual and government investment in Vietnam's educational landscape.
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
(2) To identify the determinants of household’s 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, work 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 the extent to which these factors contribute to educational expenditures.
Research methodology
This study utilizes the theory of education expenditure proposed by Pritchett and Filmer (1999) to explore the significance of English education and its expenditure determinants It employs descriptive statistics to provide an overview of English education spending among households in Ho Chi Minh City, considering factors such as total income and expenditure Additionally, ordinary least squares (OLS) regression is used to identify the influential factors affecting English language expenditure for primary school-aged children Furthermore, logit regression analyzes the impact of these determinants on households' decisions to invest in English education Lastly, ordered logit regression is applied to address the ordinal nature of English education expenditure, which is categorized on a scale from zero to six, reflecting varying levels of investment.
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: the household production function, income elasticity of education expenditure, and recent empirical research on education spending in Vietnam and globally Chapter 3 outlines the research methodology, detailing data collection methods, variable definitions, measurements, and model specifications Chapter 4 provides an overview of education, with a specific focus on English education in Ho Chi Minh City, and analyzes influential factors such as parental income, expenditure, education level, English proficiency, and household demographics that impact English education expenses for primary school-aged children.
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) propose a theory of education expenditure through the lens of the education production function, which illustrates how various inputs contribute to educational outcomes Their research focuses on the causal effects of both school inputs, such as teacher education levels, class size, teacher experience, and educational resources like textbooks, and non-school inputs, including family background, environmental factors, and children's inherent abilities By examining these elements, the education production function aims to understand their impact on children's academic 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 denotes children's innate abilities The term Ii is used generically to encapsulate the fixed student contribution associated with congenital variables, as there are currently no available datasets to accurately measure non-figurative aspects like innate ability.
Theory of household production function
Becker (1965) and Muth (1966) introduced a household production function model that illustrates how market-purchased commodities serve as inputs for household production Notably, they applied this model to analyze the production function related to child health.
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:
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 parents' English proficiency, reflecting genetic characteristics, and their working environment, representing an environmental factor.
Theory of income elasticity of educational expenditure:
Benson (1961) highlights the direct relationship between household income levels and educational expenditure, as indicated by income elasticity of education Households are categorized into low, middle, and high-income groups Low and high-income households exhibit an income elasticity of education ranging from zero to one, suggesting limited concern for educational quality In contrast, middle-income families demonstrate a higher income elasticity, exceeding one, indicating a greater commitment to investing in their children's education Consequently, middle-income households tend to allocate more funds towards education compared to their low and high-income counterparts, who are less likely to prioritize educational spending relative to 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 factors influencing expenditure on English language education, viewing it as a human capital investment, as highlighted by Espenshade (1997) The study emphasizes that spending on English education is a multifaceted variable, shaped by various independent factors rather than a single determinant While existing literature primarily addresses general education expenditure, there is a notable lack of focused studies on English language education Previous research by Kanellopoulos (1997), Tansel (2006), and Donkoh (2011) identifies key determinants of educational spending, including household income, expenditure, parental education, employment sector, employment status, age and gender of the household head, mother's employment, household size, and homeownership Building on these insights, this study will utilize these independent variables to develop a new model aimed at understanding the determinants of spending on English language education, with further details provided in the methodology section.
Household income significantly influences education expenditure, as wealthier families prioritize improving their living standards Investing in education is a key aspect of this enhancement, particularly for the next generation, as highlighted by Donkoh (2011) Research by Glewwe (1999) and Tansel and Bircan further supports this connection between income and educational investment.
(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 for assessing the influence of income on education spending Research indicates that the Tobit model is commonly utilized to determine this elasticity Notably, Hashimoto and Heath (1995) identified that middle-income households exhibit the highest education expenditure elasticity, exceeding one, while lower and higher income groups demonstrate elasticity values ranging from zero to one This suggests that middle-income households increase their education spending more significantly with income growth compared to other income levels In Greece, Kanellopoulos and Psacharopoulos (1997) calculated an elasticity of 3.18, while Hashimoto and Heath (1995) found a value of 2.35 in Japan, both suggesting that education is a luxury good Conversely, Tansel and Bircan (2006) reported a unitary elasticity in Turkey, challenging the notion that education is a luxury and indicating different dynamics in education spending across various income levels.
This research examines the role of informal education, specifically private tutoring, in English language education Stevenson and Baker (1992) highlight that households are willing to invest significantly in informal educational activities, driven by the expectation of their children achieving higher education and successful careers Consequently, the likelihood of increased spending on educational activities correlates with the household's overall expenditure level On average, families allocate approximately 11.2% of their total expenditure to tutor fees for extra 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 clear trend: parental spending on children's education escalates in tandem with overall household expenses.
To address the issue of bias arising from the simultaneous relationship between total and individual household expenses, researchers have proposed 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), which involves a two-step process The first step regresses total spending on household income, and the second step incorporates the residuals from this regression into the Tobit model for additional education spending to assess significance Their findings showed a significant result at the one percent level, leading them to conclude that total household expenses should be used as an explanatory variable instead of household income.
Numerous studies have explored the relationship between parental education and education expenditure, including research by Knight and Shi (1996), Kanellopoulos and Psacharopoulos (1997), Tansel and Bircan (2006), Qian and Smyth (2011), and Donkoh and Amikuzuno (2011), all of which highlight the positive impact of parental education on spending for children's education Knight and Shi (1996) identified two key findings: first, that a parent's educational attainment is the most significant factor influencing children's education expenditure, and second, that a father's education holds greater importance than a mother's Furthermore, Kanellopoulos and Psacharopoulos (1997) emphasized the influence of parental education on household spending, revealing that families with a more educated head are more inclined to allocate income towards education, with a notable 2.2% increase in the likelihood of educational expenditure for each additional year of education attained by the household head.
Research highlights the significant influence of a mother's education on educational decisions for their children According to Qian and Smyth (2011), households where mothers possess senior secondary or college degrees tend to invest more in their children's education Similarly, Donkoh and Amikuzuno (2011) argue that well-educated individuals are more inclined to provide their children with similar opportunities, fostering expectations for higher educational attainment.
Research by Kanellopoulos and Psacharopoulos (1997) and Andreou (2012) indicates that households in the private sector are more inclined to invest in their children's education Additionally, Qian and Smyth (2011) discovered that families with fathers in professional occupations tend to allocate more resources toward education Thus, the private sector plays a crucial role in influencing educational spending within households.
According to Kanellopoulos and Psacharopoulos (1997), Donkoh and Amikuzuno
The occupation of parents plays a significant role in shaping a household's willingness to invest in children's education There are two prevailing perspectives on this matter: one suggests that lower-class families may increase spending on education to compensate for their own lack of educational attainment, while the other argues that upper-class parents may undervalue education relative to their household wealth, leading to reduced investment in educational expenses However, Andreou (2012) contends that parental occupation does not significantly impact private spending on education.
Numerous 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) consistently indicates a negative correlation between the age of the household head and their spending choices in education.
Donkoh and Amikuzuno (2011) analyze the impact of age on household spending for education, using age and age squared variables to represent both young and old household heads Their findings indicate that older household heads are generally less willing to invest in education In contrast, younger household heads tend to be more progressive, recognizing the long-term benefits and importance of education compared to their older counterparts.
Kanellopoulos and Psacharopoulos (1997) categorize age into six groups: under 25, 25-34, 35-44, 45-54, 55-64, and 65 and older Their research indicates that the highest educational spending is found among individuals aged 35 to 44, with approximately 62.6% of heads in this group willing to invest in education Additionally, they found that the likelihood of spending decreases in the age groups that follow.
Tansel and Bircan (2006) presented a different perspective on private tutoring expenditure in Turkey, revealing that as the age of the household head increases, there is a greater willingness to invest in tutoring for their children This study will examine the impact of the household head's age on educational spending for their children.
This study aims to investigate the impact of gender on household decisions regarding education expenditure Empirical research indicates that there are differences in spending patterns between mothers and fathers for their children, with female heads of households generally allocating more funds than their male counterparts However, contrary to these findings, Andreou (2012) reported no significant effect of gender on educational spending by the household head.
In Vietnam, research by Dang (2007) highlights the complex relationship between household size and investment in children's education, suggesting that smaller families tend to prioritize quality over quantity in their educational spending He posits that as the number of children increases, family expenditures rise, leading to reduced investment in education This viewpoint is echoed by Jelani and Tan (2012) Conversely, Donkoh and Amikuzuno (2011) emphasize that larger households may actually increase overall educational spending, indicating a different perspective on the impact of family size on educational investment.
Conceptual framework
Overall of the above empirical literature, the study is going to test the relationship between the private expenditure for English education and the explanation variables as the following:
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
RESEARCH METHODOLOGY
Sampling strategy and data collection
The study utilized primary data collected through face-to-face surveys, employing a questionnaire that addressed key factors such as household income, parents' education and English proficiency, parental careers, and various demographic details including age, gender, and marital status The surveyed households comprised families with children in pre-primary and primary education levels in Ho Chi Minh City Participants were randomly selected from different districts and sub-districts, ensuring a diverse representation by choosing households randomly within a specific 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 surveyed household does not have children of primary school age, we seek responses from the next neighboring houses If the subsequent three houses also lack children in the target age group, that sample is considered empty Additionally, some selected households may leave the questionnaire unanswered due to personal reasons As a result, certain districts were unable to provide the required 20 responses, leading to a total of 267 observations for this study A detailed table of the questionnaires can be found in the annex.
Variables’ measurement and explanation
3.2.1 Current expenditure on English education
The expenditure on English education is a complex variable viewed as an investment in human capital (Espenshade and Fu, 1997) This study aims to analyze the factors influencing spending on English education by adapting models used for general education expenditures Building on previous research by Kanellopoulos and Psacharopoulos (1997), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011), we investigate key factors 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 home ownership The goal is to determine how these variables affect households' spending patterns on English education.
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, while levels one through five represent increasing expenditure brackets: level one (0 to 300,000 VND), level two (300,000 to 500,000 VND), level three (500,000 to 1,000,000 VND), level four (1,000,000 to 2,000,000 VND), and level five (above 2,000,000 VND) These classifications are derived from the average fees for extra English classes at schools and language centers, with data collected from ten schools and eleven English centers catering to primary children in beginning and pre-intermediate classes For a detailed list of the institutions involved, please refer to the appendix.
The influence of household income on education expenditure is significant, as wealthier households tend to prioritize education as a key investment in enhancing their living standards (Donkoh and Amikuzuno, 2011) Research by Glewwe and Desai (1999), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011) indicates that increased household income correlates with a greater willingness to invest in private tutoring, including English education This study posits that English education is a form of private tutoring affected by overall household income To assess the impact of income on education expenditure, two evaluation methods are employed: direct evaluation, which utilizes OLS and Probit/Logit models to analyze income levels' effects on current English education payments, and indirect evaluation, which categorizes income into low, middle, and high brackets to calculate the income elasticity of English education expenditure through the Tobit model.
In this study, the household’s total income variable is also divided into five levels:
The income classification system categorizes individuals based on their earnings into four direct evaluation 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 In an indirect evaluation method, these brackets are ranked as low, middle, and high income According to the World Bank's 2012 classification, low-income individuals are defined as those with a GNI per capita of $1,035 or less, while lower middle-income individuals fall into the subsequent category.
Income classifications are divided into four categories: lower income, which is defined as earning $1,036 to $4,085 (or 1,811,250 VND/month or less); lower middle income, ranging from $4,086 to $12,615 (1,813,000 to 7,148,750 VND/month); upper middle income, earning between $12,616 and $38,000 (7,148,750 to 22,076,250 VND/month); and high income, which is defined as earning $38,000 or more (22,078,000 VND/month or more) For clarity, the low income group is categorized as level (1), earning below 5,000,000 VND, while the middle income group encompasses levels (2), (3), and (4), and the high income group corresponds to level (5).
Empirical studies indicate that middle-income households exhibit the highest income elasticity of education expenditure, exceeding a value of one In contrast, lower and higher income classes show an elasticity range between zero and one This suggests that as income increases, middle-income households significantly increase their education spending more than other income groups, while lower and higher income households appear less concerned about the quality of their children's education, as noted by Hashimoto and Heath.
This paper investigates the relationship between income levels and expenditure on English education, examining whether an increase in income positively influences spending on English education It also explores the differences in income elasticity of English expenditure among low, middle, and high-income groups Grounded in theoretical frameworks and previous empirical research, the study aims to test these hypotheses.
H1: The household’s total income has positive relationship with the English education expenditure children
This research highlights the correlation between household total expenditure and investment in English education Stevenson and Baker (1992) note that families are willing to spend more on informal educational activities when they aspire for their children to achieve higher education and successful careers Consequently, there is a clear trend where the likelihood of spending on educational activities increases with household expenditure levels Kanellopoulos and Psacharopoulos (1997) reveal that over sixty-three percent of total educational spending is allocated to foreign language education Therefore, it is evident that parental investment in their children's education rises significantly in tandem with overall household spending.
In this study, we utilized multiple-choice responses to assess total expenditure based on the VHLSS 2010 dataset, categorizing it into six levels: (1) below 2,000,000 VND, (2) 2,000,000 to 3,500,000 VND, (3) 3,500,000 to 5,000,000 VND, (4) 5,000,000 to 10,000,000 VND, and (5) over 10,000,000 VND The research aims to examine two key hypotheses: first, whether a positive correlation exists between household total expenditure and English education spending; and second, if the simultaneous consideration of total and individual expenses introduces bias when using income as an instrumental variable, as suggested by Liviatan (1961) To investigate this, Tansel and Bircan (2006) tested the exogeneity of household total expenditure using a Tobit model, as defined by Smith and Blundell (1986), which involves two steps: regressing total spending on household income, followed by incorporating the residuals into the Tobit model for additional education spending If the regression results show significance, we can confidently use household total expenditure as an explanatory variable in place of total 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
A study by Knight and Shi (1996) emphasizes that a father's education significantly outweighs a mother's education in importance This research aims to explore the correlation between parents' education levels and expenditures on English education Following the VHLSS 2010 framework, education levels are categorized from one to eight, ranging from Primary school to Doctorate The study seeks to validate the proposed hypothesis regarding this association.
H4: Parents’ education level has a positive relationship with the expenditure on English education
H5: The level of English of Parents is positively related to their spending on English education
This study explores the impact of employment sector on English education expenditure among households in Ho Chi Minh City Previous research by Kanellopoulos and Psacharopoulos (1997) and Andreou (2012) indicates that families in the private sector tend to invest more in their children's education Specifically, we aim to determine whether parents employed by foreign companies or NGOs are more likely to allocate funds for English education compared to those in other sectors The employment landscape in Ho Chi Minh City comprises four main sectors: the public sector, the domestic private sector, the foreign private sector, and a residual category labeled as 'others.' To analyze this, we will utilize dummy variables representing each employment sector, with the public sector serving as the control variable The study will test the hypothesis that employment sector influences English education spending.
H6: Parents’ sector of employment could explain the current expenditure on English education
Research indicates distinct spending behaviors between mothers and fathers regarding their children's education To explore this further, we aim to examine how the gender of the household head influences decisions on English education expenditures Based on empirical studies, we utilize a binary variable where zero denotes a female household head and one signifies a male Subsequently, we will conduct tests to evaluate our hypothesis.
H7: There is a difference between a mother household’s head and father household’s head in their way of expense on their children’s English education
Generally, the age of head appeared to be negative efficiency to their choice of spending according to Kanellopoulos and Psacharopoulos (1997), Donkoh and Amikuzuno
Research by Donkoh and Amikuzuno (2011) indicates that households led by younger heads tend to be more progressive, recognizing the long-term benefits of education In contrast, Tansel and Bircan (2006) found that in Turkey, older heads of households are more inclined to invest in private tutoring for their children, suggesting a different perspective on educational spending based on the age of the household head.
In this study, we build on the work of Donkoh and Amikuzuno by incorporating age and age square variables to represent the household heads' ages We further refine this approach by distinguishing between four specific variables: the husband's age, the husband's age square, the wife's age, and the wife's age square Our objective is to examine the impact of the household heads' ages on their investment in their children's education expenditures, guided by the hypothesis outlined below.
H8: Parents’ age has a negative impact on current payment for English education
H9: Household has wife are working is more likely to spend on their children’s English education
Research indicates that urban households tend to invest more in their children's education than those in rural areas (Tansel and Bircan, 2006; Donkoh and Amikuzuno, 2011) This study focuses on Ho Chi Minh City, allowing us to specifically examine the differences in English education expenses between urban and suburban households To analyze this, we treat the location as a dummy variable, with urban households represented by one and suburban households as the comparison group Consequently, we propose the following hypothesis:
H10: Households in urban area are likely to spend more on English education for their children than the suburban area
Some studies conclude that the household own a house is more likely to expense for their children’s education such as Kim and Lee (2002) and Donkoh and Amikuzuno
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 employs ordinary least squares (OLS) to analyze the factors influencing English language expenditure among primary school children The OLS model reveals the relationships and trends of explanatory variables related to English spending To assess whether these determinants influence households' decisions to invest in English education, logit regression is applied, as the standard OLS model is insufficient for this purpose Additionally, ordered logit regression is utilized to address the scenario where English education expenditure is an ordered, rather than continuous, variable The expenditure is categorized into six ranked levels, which are not equidistant The overall model will be structured accordingly.
In this study, E signifies the current expenditure on English education, while X represents income levels Y refers to the English proficiency of parents, and Z indicates their working environment Additionally, T encompasses various demographic factors, including parental 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 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 behavior 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 a household's expenditure on education based on different characteristics.
The probability (P) of a household's spending on education is influenced by various independent variables, including household characteristics such as income, the age and gender of the household head, and location, as outlined by Kanellopoulos and Psacharopoulos (1997) This analysis is conducted through two separate 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 following the 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 various independent variables In this model, the ordered outcomes are predicted as a linear function of the explanatory variables and their cutpoints According to Fu (1998), the probability of achieving a specific outcome is determined by the estimated independent variables and an error term, situated within the defined cutpoints.
In this study, current expenditure for English education at level 0 indicates no expenditure, while levels 1 to 5 correspond to increasing expense brackets, ranging from below 300,000 VND to over 2,000,000 VND The independent variables, denoted as x1, x2, …, xk, 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 like parental age, gender of the household head, employment status of the wife, number of children, household location, and ownership status The coefficients β1, β2, …, βk represent the explanatory power of these variables in the analysis.
K 1 , K 2 ,… K k-1 , are the cutpoints u j is the logistically distributed of error term
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 analysis indicates that households with total expenditures exceeding 10,000,000 VND and incomes below 2,000,000 VND show a positive correlation with various factors Current payments for additional education (cpec) are also positively linked Additionally, the education levels of both spouses, ranked from 1 to 8, contribute positively to household dynamics Furthermore, the husband's English proficiency (englishh) and the wife's English proficiency (englishw), indicated by dummy variables, both positively influence the overall outcomes.
The analysis includes several key variables affecting household dynamics The dummy variable for the wife's employment status (dwifeworking) is positive when she stays at home, indicating a potential positive impact on the household Conversely, the location of the household (dlocal) is also positive if situated in an urban area The ages of both husband (ageh) and wife (agew) are negatively correlated with certain outcomes, suggesting that as age increases, there may be adverse effects Lastly, the ownership of a house (ownh) is positively associated with household stability, as it indicates that the family owns their residence.
Nchildren Number of children Child (+)/(-)
EMPIRICAL ANALYSIS RESULTS
General information of the Household’s characteristic in HCM City
A recent survey conducted in Ho Chi Minh City reveals that the education levels of parents with primary school-aged children predominantly fall within the senior high school and university categories Notably, the educational distribution between husbands and wives is nearly equivalent, although husbands generally possess higher educational qualifications For instance, 29.96% of husbands have completed university education compared to only 25.09% of wives Additionally, 7.87% of households have husbands who have attained a Doctor of Physical Education degree, while there are no households with wives holding such advanced qualifications.
A comparison of the Vietnam Household Living Standard Survey (VHLSS) 2010 reveals key insights about family education levels: husbands generally have higher educational attainment than their wives In Ho Chi Minh City, parents' education levels are predominantly concentrated in no education, primary, junior high, and senior high school, while a notable 11.69% of parents have attained a university degree.
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 compulsory subject in junior and senior high schools, with a structured curriculum established between 1982 and 2002, offering both a three-year program for grades 10-12 and a seven-year program for grades 6-12 Since 2002, English has also been introduced as an elective subject in primary schools, starting from grade 3 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 provide students with a foundational proficiency in listening, speaking, reading, and writing by the time they graduate from senior high school, enabling them to understand textbooks at a comparable level with the aid of a dictionary.
Between 2008 and 2013, the number of foreign language centers in Vietnam surged from 843 to 1,935, as reported by the Ministry of Education and Training (MOET) This growth aligns with the National Foreign Languages 2020 Project, initiated by Decision No 1400/QD-TTg on September 30, 2008, which aims to enhance foreign language education within the national system The project focuses on creating a comprehensive qualifications framework with six levels, aligning with international standards It also mandates new foreign language training programs at basic school levels, ensuring students achieve specific qualifications upon graduation: Level 1 for primary, Level 2 for junior high, and Level 3 for senior high Additionally, the project emphasizes the need for university programs to incorporate English instruction in core subjects for final-year students.
The current state of English teaching and learning in Vietnam is still lacking, prompting many parents to supplement their children's education by enrolling them in English language centers Numerous domestic and international centers, such as the British Council, VUS, VASS, Apollo, and ILA, operate successfully in Ho Chi Minh City and Hanoi, with plans for significant national expansion Additionally, a variety of smaller centers, along with both private and public schools, have emerged to address the growing demand for English education in the country.
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
Figure 4.3 illustrates that households in Ho Chi Minh City allocate a significant portion of their total education expenditure to English education.
Basic education accounts for an average of 61.4% of total education expenses in households This represents 4.7% of total household income and 6.7% of total household 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 families spend between 300,000 VND and 500,000 VND per month on these educational services For detailed statistics, please refer to the table in the appendix.
Figure 4.3 The distribution of current English education expenditure in basic education, total income and total expenditure
Empirical analysis results
This section presents the empirical analysis results and discussions, starting with descriptive statistics for both the dependent and explanatory variables, along with their correlation matrix It then summarizes the estimated results from three regression models, including the marginal effects derived from these regressions, followed by a detailed discussion of the findings.
This section presents the descriptive statistics from the survey, offering essential information for future model discussions The main dependent variable is illustrated through histogram graphics, while the explanatory variables are summarized in Table 4.1, which details 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 around 300,000 VND or less per month, representing approximately 41% of all households.
Figure 4.4 illustrates a histogram depicting the current expenditures on English education in Ho Chi Minh City The expenditure categories are defined as follows: 0 indicates no spending on English education, 1 ranges from 0 to 300,000 VND, 2 spans from 300,001 to 500,000 VND, 3 covers 500,001 to 1,000,000 VND, 4 includes expenditures from 1,000,001 to 2,000,000 VND, and 5 represents spending above 2,000,000 VND This data provides valuable insights into the financial commitment towards English education in the city.
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 comprises nearly 70% of households, making it the largest demographic The low-income group follows, accounting for 23.60%, while the high-income group represents only 6.74% Among the five income brackets, households earning between 5 to 10 million VND make up 40.07% of the total surveyed, with the below 5 million VND group at 23.60% and those earning 10 to 20 million VND at 20.60% Conversely, the highest income group, earning over 30 million VND, has the lowest representation at just 6.75% This data underscores the dominance of the middle-income segment in Ho Chi Minh City's household income distribution.
The total income distribution of households in Ho Chi Minh City is categorized into two distinct formats: (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 classifications—low income, middle income, and high income.
The majority of surveyed households, comprising 74.15%, report monthly expenditures between 3,500,000 VND to 10,000,000 VND, with 40.82% specifically spending within the 3,500,000 VND to 5,000,000 VND range This trend aligns with the income distribution, as most middle-income families allocate their earnings towards essential needs such as food, education, and healthcare A strong correlation exists between total household income and expenditure, indicating that as income increases, so does spending capacity Additionally, a significant number of households prioritize private tutoring for their children, with only 15.67% opting out of extra classes, highlighting the growing emphasis parents place on educational support.
The study investigates the demographic characteristics of households in Ho Chi Minh City, revealing that over 35% of parents are English speakers, with husbands more likely to know the language than wives Educationally, 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 a notable 34.08% of husbands and 25.47% of wives employed by domestic companies, while foreign companies and NGOs employ few Additionally, around 25% of individuals work informally, engaging in market trade or temporary labor, and 18.66% of wives are homemakers The survey indicates that 77.9% of household heads are male, with husbands aged between 26 and 58 and wives between 25 and 55 Most households, 75%, reside in urban areas, and over 64% own their homes Finally, the average number of children per household is 1.65, reflecting a trend towards smaller, modern families with one to two primary-aged 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
Table 13 in the appendix illustrates the correlation among explanatory variables, revealing no significant relationships except between the education levels and ages of both spouses, reflecting Vietnam's social characteristics Additionally, the data indicates that the high-income group five tends to spend more, leading to a notable correlation between this income group and total expenditures in groups five and six This correlation is further supported by the relationship between total expenditure and current payments for English education, corroborating Benson's (1961) theory of income elasticity in education expenditure.
The article examines the correlation between household income, total expenditure, and spending on English education Table 4.2 clearly illustrates that higher-income households allocate more funds toward 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 at all In contrast, households with incomes exceeding 30 million VND show a significant increase in spending, primarily in the 1,000,000 to 2,000,000 VND and over 2,000,000 VND ranges Furthermore, total household expenditure also influences educational spending, with higher total expenditures leading to increased investments in English education, particularly in the 1,000,000 to 2,000,000 VND and 2,000,000 VND and above categories Conversely, households with lower total expenditures primarily focus on basic living expenses and tend to spend less on English education.
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%
This chapter addresses the research questions outlined in Chapter One and is grounded in the hypotheses presented in Chapter Three The study focuses on the significance of English education in Vietnam by examining how factors such as parental income, working environment, English proficiency, and other demographic variables influence expenditures on English education for children Table 4.5 presents the findings from two regression analyses, as defined in the methodology section, to explore the relationship between these explanatory variables and the current spending on English education among 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)
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
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 reveal 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 views of Glewwe and Desai (1999), Tansel and Bircan (2006), and Donkoh and Amikuzuno (2011), indicating that higher income levels correspond to a greater willingness to invest in additional education.
Model 1 reveals 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 traditional role of Vietnamese women, who often dedicate time to teaching their children at home Consequently, wives with higher English skills are able to educate their children themselves, which reduces the overall costs associated with English education, aligning with findings from Huy's research.
In 2012, the education level of a wife significantly influenced the willingness to invest in children's education, particularly in English education, with a notable correlation at the 1% significance level.
The analysis indicates that a wife's age positively correlates with household spending on English education, with a significant level of 5% Additionally, households that own their homes tend to allocate more funds towards English education This is likely because homeownership alleviates the financial burden of rent and reduces concerns about saving for a house, thereby increasing their capacity to invest in other areas, such as their children's education.
The study found that variables such as total expenditure, parents' education, employment sector, whether the wife works, gender of the household head, age of the husband, household location, and number of children did not have a statistically significant impact on the researched object Model 2, which examines the relationship between total expenditure and English education spending, revealed that households with expenditures over 10 million had a positive influence on English education expenses, though this was only significant at the 10% level When both total income and total expenditure were included in a single regression, it was determined that each had a positive effect on household spending for English education at a 5% significance level Other controlled variables remained consistent with Model 1, except for home ownership, which showed no significant effect on English education spending in this model.