ProblemStatements
Foreign language education, particularly English, has become increasingly important in today's global society due to advancements in information and communication technologies As people from different nations connect more closely, English serves as a common language that facilitates understanding and cooperation A significant portion of knowledge, including literature, academic papers, and documentation in various fields, is predominantly available in English, making it essential for global communication According to Bolton (2006), English has rapidly spread worldwide, with Crystal (2003) noting over 1.2 billion English speakers in 2003 across 75 countries Graddol (2008) predicts that the number of English learners as a second language will approach two billion in the next decade This shift is evident in Eastern European countries, where English has replaced Russian as a primary school subject (Modiano, 2006) Given its vital role in education, governments should prioritize investment in English language education, as emphasized by Nergis.
(2011)InsomedevelopingcountriessuchasTurkey,theyrecognizethat“theonlywaytob r i n g Turkishuptothelevelofthecommunicationalrequirementsofthemodernworldisthroughth einteractionofknowledgeofEnglishwiththederivationalconveniencep r o v i d e d bytheTurkis hlanguagereform.”
InVietnam,T h i n h ( 2 0 0 6 ) o b s e r v e d t h a t i n t h e p a s t t e n yearsb e f o r e t h e j o i n i n g WTO,t h e s p r e a d of English has facingw i t h a n u n p r e d i c t e d speedi n
In Ho Chi Minh City, learners have increasingly turned to language centers, driven by a growing demand for English education in universities, high schools, and government agencies Following Vietnam's accession to the WTO and the implementation of open policies, a significant influx of foreign investment has occurred, necessitating a qualified labor force capable of effective communication with international partners This highlights the urgent need for language learning in the context of today's global economic integration Acknowledging this necessity, many parents are prioritizing English language development for their children from the start of their education.
Forthesereasons,thisstudyistoinvestigatehowimportantparentsseetheroleofE n g li sh educationbyidentifyingparents’e x p e n d i t u r e oneducatingEnglishlanguage oftheirchildrenatstartingschoolage (primaryschool)inHoChi
Minhcity.Then,ithelpstoc l a r i f y theimportantroleofEnglishlanguageeducationingene ralandEnglishinp ar t i cu l ar forthedevelopmentofthecountrywhichshouldbeconcern edandinvestedbybo ththeindividualinvestorandthegovernmentinVietnam.
ResearchObjectives
Generalo b j e c t i v e : T o investigatehousehold’sexpenditureonE n g l i s h l a n g u a g e e d u c a t i o n forchildrenatstartingschoolage(primaryschool)
(2) Toidentifythedeterminantsofhousehold’sexpenditure onEnglisheducati onforp r i m a r y schoolchildreninHoChiMinhCity.
ResearchQuestions
Inthisstudy,weattempttoanswerthequestion:Doparent’sincome,parentworkinge n v i r o n m e n t , parent’sEnglishlevelandotherdemographicissue(age,gender,maritalstatus,location,homeownershi pandemploymentstatus…)impactontheexpendituretoEnglisheducationfortheirchildren?
Researchmethodology
This study is grounded in the theory of education expenditure by Pritchett and Filmer (1999) and employs both descriptive statistics and regression analysis to assess the significance of English education and its expenditure determinants Initially, descriptive statistics provide an overview of English education expenditure among households in Ho Chi Minh City, considering factors such as total income and expenditure Subsequently, Ordinary Least Squares (OLS) regression is utilized to identify the influencing factors of English language expenditure for primary school-aged children Additionally, logit regression is applied to examine whether these determinants affect households' decisions to invest in English language education Finally, ordered logit regression is used to address the scenario where the dependent variable, English education expenditure, is not continuous but rather ordered, ranking expenditure from zero to a sixth level to reflect the varying degrees of spending.
Thestructureofthestudy
This study is organized into five chapters, beginning with an introduction Chapter 2 reviews three theories related to education expenditure, household production functions, and the income elasticity of education spending It also references recent empirical research on education expenditure in Vietnam and globally Chapter 3 outlines the research methodology, detailing data collection methods, variable explanations, and model specifications Chapter 4 presents an overview of education in general, with a focus on English education in Ho Chi Minh City It also examines influential factors, including parents' total income, total expenditure, education level, English proficiency, and various demographic characteristics that impact English education expenses for primary school-aged children.
Theoreticalliterature
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 specifically examines the causal effects of both school inputs—such as teacher education level, class size, teacher experience, and educational resources like textbooks—and non-school inputs, including family factors, environmental influences, and children's innate abilities, on children's academic achievements.
WhereCitpresentsforchildren’soutput,Sitp r e s e n t sforschoolinputs,Fitdenotesthenon- schoolinputs(familyinputs)andIiisthechildren’scongenitalability.Inthiscase,theyusea g e n e r a l t e r m tor e p r e s e n t a p p r o x i m a t e l y t h e c o n g e n i t a l v a r i a b l e t h a t i s f i x e d s t u d e n t c o n t r i b u t i o n Becausethereisnodatasetswhichcanmeasurethenonfigurat ivevariablelikecongenitalability.
BothBecker(1965)andMuth(1966)raiseahouseholdproductionfunctionmodelt o explainthatcommoditieswhicharepurchasedonmarketsimultaneouslyaretheinputoft h e h o u s e h o l d p r o d u c t i o n I n p a r t i c u l a r l y , theyemployt h e p r o d u c t i o n f u n c t i o n o f c h i l d h ealthwhichcanbeshownasbelow:
Whereas,Yjareothergoodaffectchild’shealth;Ikpresentforhealthinputandà),isthef a m i l y - s p e c i f i c healthendowmentssuchasgeneticcharacteristicsorenvironmentalfactors
Latero n , fromt h i s h o u s e h o l d p r o d u c t i o n f u n c t i o n , theyd e v e l o p e d h o u s e h o l d ’ s redu ced -fo rm demandfunction:
Learningfromthistheory,inordertomeasurethehouseholdexpenditureonE n g l i s h l a n g u a g e e d u c a t i o n , s u p p o s e s t h a t e d u c a t i o n i s a l s o a k i n d o f g o o d s w h i c h i s consumedbyh o u s e h o l d Hence,wetestthefactorswhichcanaffectthehouseholdp r o d u c t i o n functionsuchasthehousehold’sincome,thefamily specificendowmentf a c t o r s andmanyothersdemographicfactors.Moredetails,thefamilyspeci ficendowmentu s i n g inthiscaseareEnglishleveloftheparents(akindofissueconcerngeneticch aracteristic)andworkingenvironmentofparents(anenvironmentalfactor).
AccordingtoBenson(1961),thelevelofhouseholdincomehasdirecteffectontheeducat ionalexpenditurewhichismeasuredbytheincomeelasticityofeducation.Therearet h r e e levelso fincomedividedintolow,middleandhighincome.Indetail,thehouseholdsa t lowandhighinco meareexpectedtohavetheamountofincomeelasticityofeducationf r o m zerotoone.Incon trast,amiddleincomehouseholdhasvalueofincomeelasticity higherthanone.Thisexplainsclearlythatthemiddleincomefamilieshave thetendencytoc o n c e r n a b o u t t h e i r c h i l d r e n ’ s e d u c a t i o n a n d t h e y spend morem o n e y fort h e m t ha nt h e o t he r class.Forthelowincomefamilies,theylessconcernaboutthe qualityofschoolingsothattheireducationexpenditurearepredictedincreaselessthantheirtotali ncome.
Empiricalliterature
This research aims to analyze the factors influencing expenditures on English language education among U.S immigrants, considering it a crucial human capital investment Previous studies, such as those by Espenshade (1997) and others, highlight that spending on English education is influenced by a variety of complex and diversified variables, making it difficult to interpret through a single independent variable Limited research has focused specifically on English language education expenditures, with most studies addressing general education spending Key determinants identified include household income, expenditure, parental education, employment sector, employment status, age and gender of the household head, and household size By utilizing these independent variables, we will develop a new model to better understand the determinants of spending on English language education, which will be detailed in the methodology section.
Theimpactofhousehold’sincomeoneducationexpenditureispreciselyexisted.Iti s c learlythatoncethehouseholdsgetwealthiertheywouldliketoenhancetheirliving standards.Educationisoneoftheimportantstandardswhichareconsideredtoinvestfort h e i r newgenerationinpriority,Donkoh(2011).BothGlewwe(1999),TanselandBircan(2006)a ndDonkohandAmikuzuno(2011)foundthatwhenthehousehold’sincomeriset h e y are morewillingtopayfortheprivatetutoring.
The impact of income on education expenditure is evaluated using the income educational expenditure elasticity of households as a proxy, with many studies employing the Tobit model for analysis Research 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 an elasticity ranging from zero to one This suggests that as income increases, middle-income households significantly boost their education spending, unlike lower and higher-income groups who appear less concerned about the quality of their children's education In Greece, Kanellopoulos and Psacharopoulos (1997) found an elasticity of 3.18, while Hashimoto and Heath (1995) reported a lower value of 2.35 in Japan Both studies conclude that education expenditure is a luxury good However, Tansel and Bircan (2006) challenge this notion, finding unitary elasticity for education demand in Turkey, suggesting that education is not considered a luxury good in that context.
In examining English language education, particularly through informal educational activities such as private tutoring, it is evident that households tend to invest significantly in these services, driven by the expectation of their children achieving higher education and successful careers According to Stevenson and Baker (1992), the likelihood of increased spending on educational activities correlates with the overall expenditure level of the household Notably, tutoring fees account for approximately 11.2% of a family's total expenses, with foreign language education comprising over 63% of these costs, highlighting the substantial financial commitment parents make towards their children's education, as noted by Kanelopoulos and Psacharopoulos (1997) This underscores the trend that parental spending on education escalates in line with their total household expenditures.
There are significant concerns regarding the selection of variables to avoid simultaneous problems in research Some authors argue that the simultaneous relationship between total and individual expenses can lead to bias, suggesting the use of instrumental variables like household income to mitigate this issue (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 to assess significance Their findings indicated a one percent significance level, leading them to conclude that total household expenses should be used as an explanatory variable rather than household income.
Therearemanystudiesemploythisindependentvariabletoexplainitsrelationshipof e ducation expenditure suchasKnight andShi(1996), Ka ne ll op ou los andPsachar
1 0 opoulos( 1 9 9 7 ) , T a n s e l a n d B i r c a n ( 2 0 0 6 ),Q i a n a n d S m y t h ( 2 0 1 1 ) a n d D o n k o h a n d A m i k u z u n o ( 2 0 1 1 ) Nearlyallofthemfound thepositive impactofparentaleducationt o theirspendingforchildren’seducation.Inthere,Knight andShi(1996)pointouttwo
( 2 ) F a t h e r ’ s e d u c a t i o n i s moreimportantf a c t o r t h a n mother’seducation”.Kanel lopoulosandPsacharopoulos(1997)foundthesignificanceofp a r e n t a l educationont hehouseholdexpenditureontheirchildren’seducation.Thehouseholdswherethehe ad has hi gh ere du cat io n rangeare mo re willing todev ot e moreincomef o r e d u c a t i o n S p e c i f i c a l l y , i t i s a p p r o x i m a t e l y 2 2 % i n c r e a s e i n p r o b a b i l i t y off a m i l y a g r e e t o e x p e n s e f o r e d u c a t i o n w h e n a h o u s e h o l d h e a d g e t o n e m o r e yearo f education.
Especially,somea u t h o r s e m p h a s i z e t h e i m p o r t a n t r o l e o f m o t h e r ’ s e d u c a t i o n i n makingt h e d e c i s i o n Q i a n a n d S m y t h (2011)s a i d “ t h e h o u s e h o l d w h e r e mothersh a v e s e n i o r s e c o n d a r y s c h o o l o r c o l l e g e e d u c a t i o n a r e l i k e l y t o s p e n d moreo n e d u c a t i o n ”.D o n k o h andAmikuzuno(2011)claimsitconnectstothef actthatthe personswhoarewelle d u c at e d w o u l d b e a b l e a n d p l e a s e t o g i v e t h e i r s o n / d a u g h t e r t h e sameo p p o r t u n i t y andexpect themgothighereducationlevel.
EitherKanellopoulosandPsacharopoulos(1997)orAndreou(2012)comeupwitht h e s i m i l a r c o n c l u s i o n o f t h i s c o n c e r n e d t h a t t h e h o u s e h o l d s w h i c h a r e w o r k i n g i n t h e p r i v a t e s e c t o r h a v e t e n d e n c i e s t o f i n a n c e moref o r theirs o n / d a u g h t e r ’ s e d u c a t i o n Recently,QianandSmyth(2011)also found that
“householdwherefathersareworkinginp r o f e s s i o n a l occupations,arelikelytospendm oreoneducation”.So,theprivatesectorist h e keydeterminantsofintheirresearchregardingt heworkingenvironmentofthehouseholdhead.
AccordingtoKanellopoulos andPsacharopoulos(1997),DonkohandAmiku zuno(2011),theoccupationoftheparentscouldalsoaffectthewillingnessofahouse
11 holdtoi n v e s t inchildren’seducation.Therearetwoschoolsofthoughtaboutthisissue.Oneisthe o c c u p a t i o n hasapositiveeffectsinceitissupposedthelowerclassofhouseholdtend to compensatetheirlackofeducationbyspendingmoreforyourchildren’seducation.Otheri s the negativeeffectontheirexpense.Theupperclassparentsthinkthateducationbringsa relativelo wvalueincomparedwiththeirhouseholdvalue.Hence,theydisregardtheroleo f education.Nevert heless,Andreou(2012)saidtheoccupationofparentsdoesnotaffects i g n i f i c a n t l y onprivates pendingforeducation.
Mostofthestudiesemploytheageofhousehold’sheadasanessentialvariabletoe v al u a t e itseffectonthehousehold’sinvestmentineducation.Generally,theageofheadap p ear ed tobenegativeefficiencytotheirchoiceofspendingaccordingtoKanellopoulosa n d Psacharopoulos(1997),DonkohandAmikuzuno(2011)andAndreou(2012).
DonkohandAmikuzuno(2011)employtheageandagesquarevariablerepresen tf o rtheyoungandoldhouseholdhead.Asaresult,theolderthehousehold’shead,thelesswilling tos p e n d f o r e d u c a t i o n Theya r g u e t h a t t h e h o u s e h o l d w i t h youngerh e a d isc o n s i d e r e d moreadvanced andcomprehendthelong- termbenefitandtheroleof educationincomparisonwiththeiroldercounterparts.
KanellopoulosandPsacharopoulos(1997)dividethisvariableintosixagegroups: u nd er 25,from25to34,from35to44,from45to54,from55to64andabove65.Theydiscover ed thatthetopofspenderforeducationbelongtothegroupwithheadsfrom35-
Nevertheless,TanselandBircan(2006)stateddifferentlyaboutthiscontext.Whenan alyzingthedemandforprivatetutoringexpenditureinTurkey,theyfoundthatthemorea c c u m u l a t i o n ofhead’sage,themorewillingtopayfortutoringtheirchild.Hence,wewilltestt h e a f f e c t i v e t r e n d o f t h e h o u s e h o l d ’ s h e a d a g e o n t h e i n v e s t m e n t i n t h e i r c h i l d ’ s education expenditure.
Likewise,w e w i l l a t t e m p t t o t e s t w h e t h e r t h e g e n d e r w o u l d a f f e c t t h e h o u s e h o l d decisiono n e d u c a t i o n e x p e n d i t u r e L e a r n i n g f r o m t h e e m p i r i c a l s t u d i e s , theya p p l y thed u m m y forthisvariable.Somestudiesfoundthedifferentiationbetweenmoth erandfatherspendingw i l l i n g l y ont h e i r son / da ug ht er Andt h a t a f ema le hea dte nd t o e x p e n s e moret h a n amalehead.Bycontrast, Andreou(2012)didnotfindthemeaningofgenderontheh o u s e h o l d ’ s headexpenditureone ducation.
Dang (2007) examined the determinants and impact of private tutoring classes in Vietnam, arguing that the number of children in a household is an endogenous variable affecting educational investment He suggests that parents are likely to invest more in their children's education when their household size is smaller, prioritizing quality over quantity Similarly, Jelani and Tan (2012) support this view, noting that an additional child increases family expenditures, leading to reduced educational investment In contrast, Donkoh and Amikuzuno (2011) emphasize the quantity aspect, asserting that larger household sizes correlate with higher educational expenses.
TheauthorssuchasTanselandBircan(2006)andDonkohandAmikuzuno(2011)fou ndthepreciselinkbetweenthehigherexpenditureoneducationandtheurbanareas.Theya l l c o n c l u d e t h a t t h e h o u s e h o l d i n u r b a n a r e a s t e n d tos p e n d m oremoneyf o r e d u c a t i n g theirchildincomparisonwithruralcounterparts.OnlyAndreou(2012)saidthevaryhousehold’sregiondoesnotresultindifferentofeducation’sdisbursement.
Inparticular,DonkohandAmikuzuno(2011)statesthedifferentiationofthenumber o f h o u s e h o l d e x p e n s e f o r p r i v a t e e d u c a t i o n ( t h e q u a n t i t y o f spending)a n d t h e a m o u n t ofmoneytheyspend(thequalityofspending).Theirstudyshowsthereisalarger numberofhouseholdagreetospendforeducationintheruralpartthanthecitypart.Byco ntrast ,the concentratedcityhas thehigher qualityof education investmentthan theruralp a rt Thus,wewillhavehousehold’slocationasanendogenousvariable as sameastheabo vementionaboutthehouseholdage.
BothK i m a n d L e e ( 2 0 0 2 ) a n d D o n k o h a n d Amikuzuno( 2 0 1 1 ) c l a i m t h a t theh o u s e h o l d ownahouseismorelikelytoexpensefortheirchildren’seducation.Iti swella c c e p t e d t h a t h a v i n g ah o u s e i s e q u i v a l e n t t o t h e b e t t e r l i v i n g c o n d i t i o n s a s w e l l a s correlated t othe higherincome.F o r t h e se r e a s o n, theyar ee as i e r totake t h e charges o f theirson/daughter’seducation.
Conceptualframework
Overalloftheaboveempiricalliterature,thestudyisgoingtotesttherelationship b et w e e n theprivateexpenditureforEnglisheducationandtheexplanationvariablesasthefollo wing:
Age Gender(dummyV)Ma ritalstatusLocation(du mmyV)Ho me owners hip( du mm y V)Empl oymentstatusNumber ofchildren
Samplingstrategyanddatacollection
Thestudyusedtheprimarydatacollectionbyfacetofacesurvey.Aquestionnairew a s c o m p o s e d t o c o v e r t h e m a i n q u e s t i o n s w h i c h i n c l u d e s h o u s e h o l d ’ s t o t a l i n c o m e , p a r e n t ’ s e d u c a t i o n l e v e l a n d E n g l i s h l e v e l , c a r e e r o f t h e p a r e n t , a n d someo t h e r dem ogr ap hic i s s u e ( a g e , g e n d e r , maritals t a t u s ) T h e h o u s e h o l d s s u r v e y e d i n c l u d e thosew i t h c h i l d r e n a t p r e - p r i m a r y a n d p r i m a r y e d u c a t i o n l e v e l i n H o C h i M i n h City.T h e h o u s e h o l d s were cho sen randomly fromeachdistrictsor su b d i s t r i c t s Households we r e selectedrandomlybythenumberofhouseandinonerandomwardofthedistrict.About2 0 householdswereinterviewedineachdistricts/sub- districts.TheinternaldistrictsinHoChiMinhCitycomprisedistrictonetotwelve,TanPhu,Tan
Binh,BinhTan, BinhThanh,G o Vap,Phu Nhuan T h e sub- districtsincludeBinh Cha nh, H oc Mo n, C u Chi,N ha Be w h e r e a s weexcludedtheCa nGio’sobservationbecauseofitslowpopulationdensity.
Whenaquestionedhouseholdwhichhasnochildrenattheprimaryschoolage,wea s k t h e n e x t h o u s e f o r r e p l a c e m e n t I f t h e n e x t t h r e e h o u s e s h a v e n o c h i l d r e n a t o u r objectiveage,wewillleavethissampleempty.Somechosenhouseholdslea vetheemptya n sw e r s h e e t d u e tot h e i r p r i v a t e i s s u e s
H e n c e , somed i s t r i c t s d i d n’tg e t e n o u g h 2 0 r e s p o n s e s andfinallythesurve ygot267observationsintotalforthisstudy.Theq u e s t i o n n a i r e s tablewouldbelisted intheannex.
Variables’measurementandexplanation
The expenditure on English language education is a complex and varied aspect of human capital investment, as highlighted by Espenshade and Fu (1997) This study examines the costs associated with this investment and the expected returns, which can differ among spenders Given the limited research on language education expenditure, we analyze factors influencing general education spending to create a new model specifically for English education expenditure Building on the findings of Kanellopoulos and Psacharopoulos (1997), Tansel and Bircan (2006), and Donko and Amikuzuno (2011), this research explores various factors such as total household income, total expenditure, parental education, employment sector, age and gender of the household head, mother's employment status, household size, and homeownership The aim is to determine how these factors impact spending behavior on English education within households.
This study evaluates parental interest in children's English education by analyzing current expenditure levels, categorized into six tiers A ranking of zero indicates no expenditure on English education, while one signifies spending between 0 to 300,000 VND Level two denotes expenditures ranging from above 300,000 to 500,000 VND, and level three reflects spending between 500,000 to 1,000,000 VND Level four represents expenditures from above 1,000,000 to 2,000,000 VND, and level five indicates spending above 2,000,000 VND These rankings are derived from the average fees of extra English classes at ten schools and eleven English centers, specifically for beginner and pre-intermediate classes for primary children For a complete list of schools and English centers, please refer to the appendix.
Asdiscussioninthepreviouschapter,theimpactofhousehold’sincomeone d u c a t i o n e x p e n d i t u r e i s considerable.O n c e t h e h o u s e h o l d s g e t w e a l t h i e r theyt e n d t o enh an ce t h e i r l i v i n g s t a n d a r d s inw h i c h e d u c a t i o n i s o n e o f t h e i m p o r t a n t s t a n d a r d s t o invest,D o n k o h a n d A m i k u z u n o ( 2 0 1 1 ) B o t h G l e w w e a n d D e s a i ( 1 9 9 9 ) , T a n s e l a n d Bircan( 2 0 0 6 )a n d
17 thatEnglisheducationisoneofthetypesofprivatetutoringandhence,itisinfluencedbythehou sehold’stotalincome.Therearetwomethodstoevaluatetheimpactofincomeone d u c a t i o n expenditure:directandindirectevaluation.Thedirectevaluationmeasuresthei mp act ofalllevelsofincometothecurrentpaymentforEnglish educationin theOLS andProbit/Logitmodel.Whiles,int h e i n d i r e c t e v a l u a t i o n t h e incomeisd i v i d e d i n t o l o w , middlea n d h i g h i n c o m e andt h e n a p p l i e d toc a l c u l a t e t h e i n c o m e e l a s t i c i t y o f E n g l i s h e d u c a t i o n expenditure.ItisexecutedbytheTobitmodel.
( 1 ) below5,000,000VND,(2)from5,000,000VNDto10,000,000VND,(3)from
( 4 ) o v e r 2 0 , 0 0 0 , 0 0 0 V N D i n d i r e c t e v a l u a t i o n method.Andit’srankedaslow, middleandhighincomeintheindirectevaluationmethod.B a s e d ontheclassificationofinco megroupoftheWorldBank2012,lowincomeistheg ro u p whichhasGNIpercapitaequalor lessthan$1,035percapita;lowermiddleincome,
$ 1 2 , 6 1 6 o r more.AscalculationtoVND,itmeansthatlowerincome,1,811,250VND/head/ monthorl e s s ; lowermiddleincome,from1,813,000to7,148,750VND/head/ month;uppermiddleincome,f r o m 7, 1 4 8 , 7 5 0 t o 2 2 , 0 7 6 , 2 5 0 V N D / h e a d / m o n t h ; h i g h i n c o m e , 2 2 , 0 7 8, 0 0 0 V N D / h e a d / m o n t h Relatively,wesupposethatlowincomegroupisthelevel(1)income,below5,0 00,000VND;middleincomegroupiscomprisedoflevel(2),
Inthepreviousempiricalstudies, thehighestincomeelasticityofeducatione xpenditurebelongedtothemiddleincome levelofhouseholdand thevalue ishigher thano n e ; whileitrangesfromzeroandoneforlowerandhigherincomeclass.Thismeansthatth e riseineducationexpenditureof themiddleincomehouseholdishigherthanotherclassa s l o n g a s t h e i r i n c o m e i n c r e a s e s a u n i t A n d t h e l o w e r a n d h i g h e r incomec l a s s s e e m s r e g a r d l e s s t h e q u a l i t y o f t h e i
18 r c h i l d r e n ’ s e d u c a t i o n a c c o r d i n g t o Hashimotoa n d H e a t h (1995).However,s omestudiesfoundnodifferencebetweentheseincomegroupswhicha f f e c t oneducati ondemand.F o r thesereasons,thepaperisgoingtoinvestigatewhether
18 incomeincreasewouldbringpositiveexpenditureforEnglisheducationornotandwhetherincomeelas ticityofEnglishexpenditurebetweenthelow,middleandhighincomegroupa r e different? Overall,reliedontheoreticalstudiesandpriorempiricalresearches,thestudya i m s totestthefollowing hypothesis:
This research examines the relationship between household total expenditure and spending on English education According to Stevenson and Baker (1992), households tend to invest more in informal educational activities when they anticipate that their children will achieve higher education and successful careers As a result, the likelihood of spending on educational activities increases in line with the household's overall expenditure levels Additionally, Kanellopoulos and Psacharopoulos (1997) note that expenses for foreign language education account for over sixty-three percent of total spending on general education Thus, it is evident that parents' financial commitment to their children's education rises significantly with their total expenditures.
Ino u r c a s e , w e d i d u s e t h e multiplec h o i c e s f o r t h e a n s w e r o f totale x p e n d i t u r e q u e s t i o n BasedontheresultofVHLSSdataset2010,thetotalexpenditureanswerinthis studyis r a n k e d i n t o s i x l e v e l s : ( 1 ) b e l o w 2 , 0 0 0 , 0 0 0 V N D ,
(3)from3,500,000VNDto5,000,000VND,(4)from5,000,000VNDto
(5)over10,000,000VND.Thestudywilltesttwocontents:firsttestisw h e t h e r t h e r e isa p o s i t i v e r e l a t i o n s h i p b e t w e e n t h e h o u s e h o l d ’ s t o t a l e x p e n d i t u r e a n d En glish educationexpenditure.Secondiswhetherthesimultaneousbetweentotalexpenseand
Using individual expenses as an instrument variable can introduce bias, as noted by Liviatan (1961) To address this, Tansel and Bircan (2006) tested the exogeneity of a household's total expenses through a Tobit model, as defined by Smith and Blundell (1986) This process involves two steps: first, regressing total spending on household income, and second, utilizing the residuals from this regression in the Tobit model for additional education spending to assess significance If the regression results indicate significance, the total expenses of a household can be used as an explanatory variable instead of relying on the total income variable.
Manystudiesfoundthepositiveimpactofparentaleducationtotheirspendingforc hildren’se d u c a t i o n s u c h a s K n i g h t a n d S h i ( 1 9 9 6 ) , K a n e l l o p o u l o s a n d P s a c h a r o p o u l o s (1997),TanselandBircan(2006 ),QianandSmyth(2011)andDonkoh and Amikuzuno (2011).Moredetail,KnightandShi(1996)statedthat“Father’seducationismo reimportantfactorthanm other’se d u c a t i o n ” T h u s , t h e s t u d y i n v e s t i g a t e s o n t h e p a r e n t ’ s e d u c a t i o n l e v e l t o f i n d o u t t h e a s s o c i a t i o n o f i t t o t h e E n g l i s h e d u c a t i o n e x p e n d i t u r e SimilarlytotheVHLSS2010,theeducationlevelisrangedfromo netoeightinwhichthemotherorfatherhadfinishedthePrimaryschool,Juniorhighschool,S eniorhighschool,P r i m a r y v o c a t i o n a l school,Colleges,University,MasterandPhys icalofdoctorrespectively.Thestudyattempttotestthehypothesisasbelow:
Households working in the private sector tend to invest more in their children's education, as noted by Kanellopoulos and Psacharopoulos (1997) and Andreou (2012) This study aims to examine whether the sector of employment influences English education expenditure Specifically, it investigates if parents employed in private sectors, such as foreign companies or NGOs, are more likely to spend on English education for their children In Ho Chi Minh City, there are four main employment sectors: public, domestic private, foreign private, and others, with private sector households showing a tendency to finance their children's education more Each employment sector is treated as a dummy variable in the regression analysis, with the public sector serving as the control variable The study will test the hypothesis regarding these expenditure patterns across different employment sectors.
Somes t u d i e s f o u n d t h e d i f f e r e n t i a t i o n b e t w e e n mothera n d fathers p e n d i n g w i l l i n g l y ontheirson/ daughter.Inordertoclarifythispointofview,wewillattempttotestw h e t h e r thegenderofhousehol dheadwouldaffectthehouseholddecisionontheEnglishe d u c a t i o n expenditure.Learnin gfromtheempiricalstudies,weapplythedummyforthisv a r i a b l e Whereas,zeroreprese nttofemaleandonerepresenttomale.Afterthatwerunthetestofbelowhypothesis:
H7:Thereisa differencebetween amotherhousehold’sheadandfatherhousehold’sheadintheirwayofexpenseontheirchildren’sE nglisheducation.
Generally,t h e a g e o f h e a d a p p e a r e d t o b e n e g a t i v e e f f i c i e n c y t o t h e i r c h o i c e o f spendingaccordingtoKanellopoulosandPsacharopoulos(1997),DonkohandAmikuzun o(2011)andAndreou (2012).DonkohandAmikuzuno(2011)explained thehouseholdwithyoungerheadisconsideredmoreadvancedandcomprehendthelong- termbenefitandther o l e o f e d u c a t i o n i n c o m p a r i s o n w i t h theiro l d e r c o u n t e r p a r t s N e v e r t h e l e s s , T a n s e l a n d Bircan( 2 0 0 6 )s t a t e d reversely.Whena n a l y z i n g t h e d e m a n d f o r p r i v a t e t u t o r i n g expenditurei n T u r k e y , theyf o u n d t h a t t h e morea c c u m u l a t i o n o f h e a d ’ s a g e , t h e morew i l l i n g topayfortutoringtheirchild.
In this study, we build on the work of Donkoh and Amikuzuno by incorporating age and age squared variables to represent the heads of young and old households We specifically separate these variables into four distinct categories: husband’s age, husband’s age squared, wife’s age, and wife’s age squared Our objective is to examine the impact of the household head's age on their investment in children's education expenditures, guided by the hypothesis outlined below.
Theprincipalofthispointof viewisthatthehouseholdinurbanareastendtospendmoremoneyforeducatingtheirchildinco mparisonwithruralcounterpartsaccordingtoT a n s e l andBircan(2006)andDonkoh andAmikuzuno(2011).Inthisstudy,becausewelimittheresearchareatoHo Chi
MinhCity,sowe couldonlytest whether or notit has thedifferencefromurbanareasandthesuburbanareasontheexpenseforEnglisheducatio n.T h i s variableistreatedasadummyvariableinwhichonerepresentforthehousehold inurbanareaandsuburbanisthecomparisonvariable.Accordingly,theproposedhypothesisis:
Somestudiesconcludethatthehouseholdownahouseismorelikelytoexpensefort h e i r c h i l d r e n ’ s e d u c a t i o n s u c h a s K i m a n d L e e ( 2 0 0 2 ) a n d D o n k o h a n d A m i k u z u n o (2011).I t i s a l s o w e l l a c c e p t e d t h a t h a v i n g a h o u s e i s e q u i v a l e n t t o t h e b e t t e r l i v i n g conditionsandmorelikelytospend fortheir children’seducation.For thesereason,we’reg o i n g t o t e s t the relationshipbetweenhousehold owna houseto theirspendingfor
Englisheducation.Andattempttotestwhetherithasinteractionwiththehousehold’stotalexpend iture.Sameasbefore,itistreatedasadummyvariablewith1presentforhouseholdo w n ahouseand0f orhouseholddoesnotownahouse.Afterall,thestudy wouldtesttheb e l o w specifichypothesis:
According to Dang (2007), the number of children in a household may influence family decisions regarding both the quantity and quality of education Jelani and Tan (2012) highlight that adding an additional child can increase family expenditures, potentially leading to reduced investment in education Conversely, Donkoh and Amikuzuno (2011) argue that larger households are likely to spend more on education This study aims to explore the impact of household size on English education expenditure and to identify the trends associated with this influence.
Modelspecification
Toi n v e s t i g a t e t h e i m p a c t s o f a l l s u g g e s t e d i n d e p e n d e n t v a r i a b l e s t o t h e E n g l i s h educationexpenditure,thisstudyusefivemodelstotestthetwelvepropose dhypotheses.I n p a r t i c u l a r l y , t h e o r d i n a r y l e a s t s q u a r e ( O L S ) i s e m p l o y e d t o f i g u r e o u t t h e i n f l u e n t f a c t o r s ofEnglishlanguageexpenditureonthechild renatprimaryschoolage.The OLSmodelshowstherelationshipandtrend ofthese e xplanatory variablesonEnglishexpenditureonly.Next,thelogitregressionisapplied toinvestigatewhetherornotthesed et e r m i n a n t s affectonthehousehold’sdecisiontosp endornotfortheirEnglishlanguageeducation,w h e r e a s , t h e normalO r d i n a l L e a s t
S q u a r e modelc a n ’ t d o that.T h e n , t h e o r d e r e d logitregressionisusedforsett lingtheproblemwhenthedependentvariable,in thiscaseistheEnglisheducationexpe nditure,isnotacontinuousbutitisordered.Inthisstudy,theanswertheexpenditureonEnglishisra nkedfromzerotosixthlevelwhichisnote q u a l betweentheselevels.Thegeneralmodelwillbeperfor medasbelow:
Whereby,Erepresentsfor the currentpayment for English education, X denotes forincomevariable,YdenotesforEnglishlevelofparents,Zistheparents’workinge n v i r o n m e n t ; andTpresentsforthegroupofotherdemographicfactorssuchasparent’sage, g e n d e r o f h o u s e h o l d h e a d , w i f e w o r k i n g o r n o t , n u m b e r o f c h i l d r e n , l o c a t i o n o f h o u s eh o l d andhouseholdownership,etc…
Specifically,t h e d i f f e r e n t r e g r e s s i o n m e t h o d s a r e a p p l i e d tof i n d o u t t h e a b o v e r e s e a r c h objectives F i r s t l y , the O r d i n a r y LeastSquare ( O L S ) r e g r e ss i o n is e m p l o ye d totestwhethertherehasrelationshipbetweendependentvariablesandind ependentvariables.I n thiscase,therearetwospecificmodelsemployedasfollowing:
Model3andmodel4:Logitmodelswithincome(model3)andexpenditure(model4)
Secondly,thelogitregressionisappliedtoinvestigatewhetherornotthesed e t e r m i n a n t s affectonthehousehold’sdecisiontospendfortheirEnglishlanguageeducation.Bec ausethespenderisa0-
1limiteddependentvariable,alogitmodelisfittedw i t h thisanalysis.DifferencefromtheOL Sregression,thismodelpresentstheprobability
WherePisprobabilityofdependentvariableofahouseholdspendingforeducation,βisthelo gitcoefficientandXisthebunchofindependentvariablesuseforevaluatethedepend en t variable suchashouseholdcharacteristicsuchasincome,household’sheadage,gend er, l o c a t i o n , a c c o r d i n g t o K a n e l l o p o u l o s a n d P s a c h a r o p o u l o s ( 1 9 9 7 ) I n t h i s r e g r e ss i o n , iti s s e p a r a t e d i n t o t w o model3 a n d 4 w h e r e a s model3 analyzeb u n c h o f inc omea n d o t h e r e x p l a n a t o r y v a r i a b l e s a n d model4 e m p l o y t h e t o t a l e x p e n d i t u r e a n d o t h e r explanatory variablestocomparewithmodel3.Themarginaleffectsofeache x p l a n a t o r y variableafterth elogitmodelarecalculatedtoevaluatetheimpactrateofthemo n Englisheducationexpenditure.
AslongastheEnglisheducationexpenditureinthis studyisnota numericformat typeanditiscategorizedintosixlevelsfromzerotofivewhichcalledordinaldependentv ar iab le Hence,theorderedlogitmodelissuitableforanalyzingtherelationshipbetweent h i s k indofordereddependentvariableandthesetofindependentvariable.Inthismodel, theorderedoutcomesareestimatedasalinearfunctionofthesetofexplanationvariablesand thecutpoints.AccordingtoFu(1998),theprobabilityofobservingoutcomeIc o r r e s p o n d totheprobabilityofestimatedindependentvariablesplustheerrorterm,withinthelevelofthecutpoi nts.Itistreatedasbelowfunction:
Where, cpe jis definedascurrentexpenditureforEnglisheducationatlevel0equaltonoexpenditure;1 e q u a l tot h e e x p e n s e b e l o w 3 0 0 , 0 0 0 V N D , 2 e q u a l t o t h e e x p e n s e f r o m 3 0 0 , 0 0
0 VNDto500,000VND,3equaltotheexpensefrom500,000VNDto1,000,000V N D , 4 presentsfortheexpensefrom1,000,000VNDto2,000,000VNDand5fortheexp en s eover2,000,000VND x 1,x2,… x kjdenotes f o r t h e i n d e p e n d e n t v a r i a b l e s:t h eh o u s e h o l d ’ s t o t a l i n c o m e , t o t a l expenditure,c u r r e n t p a y m e n t f o r e x t r a c l a s s , p a r e n t s ’ e d u c a t i o n l e v e l , p a r e n t ’ s Englishl e v e l andsomeothersdemographiccharacteristicssuchasparent’s age,genderofh o u s e h o l d h e a d , w i f e w o r k i n g o r n o t , n u m b e r o f c h i l d r e n , l o c a t i o n o f h o u s e h o l d a n d h o u seh o l d ownership. β 1 ,β 2 ,…β k denotefortheexplanationcoefficients
CPE CurrentpaymentforEnglisheducation VND dIncome2 Dummyhousehold’stotal incomevariable.Equal to incomerankfrom5 , 0 0 0 , 0 0 0 t o 1 0 , 0 0 0 , 0 0 0 ; otherwiseequal to incomebelow5,000,000
VND Positive(+) dIncome3 Dummyhousehold’stotal incomevariable.Equal to incomerankfrom1 0 , 0 0 0 , 0 0 0 t o 2 0 , 0 0 0 , 0 0 0 ; otherwise equalto incomebelow5,000,000
VND Positive(+) dIncome4 Dummyhousehold’stotalincomevariable.Equal to incomerankover2 0 , 0 0 0 , 0 0 0 ; otherwiseequalto incomebelow5,000,000
The study analyzes various expenditure variables categorized by income levels in VND, with specific thresholds defined for total expenditures ranging from 2,000,000 VND to over 10,000,000 VND Each expenditure category is assigned a positive value, indicating an increase in total expenditure as income rises Additionally, the impact of education levels for both spouses is considered, with rankings from 1 to 8, showing a positive correlation with household expenditures Furthermore, a dummy variable for the husband's English proficiency is included, indicating a value of 1 if he possesses English knowledge.
The study examines several variables affecting household dynamics, including the husband's English proficiency, which is positively correlated with a dummy variable indicating whether he knows English The wife's employment status is represented by a dummy variable, where staying at home is negatively associated with her work status Additionally, the household's location is categorized as urban or rural, with urban households showing a positive correlation Age factors for both the husband and wife are negatively correlated, while homeownership is positively associated with the household's overall stability.
Thisc h a p t e r m o s t l y r e p r e s e n t s t h e e m p i r i c a l a n a l y s i s r e s u l t a n d d i s c u s s i o n F i r s t l y , t h e c h a p t e r presentstheoverviewinformationoftheeducationinHoChiMinh City.Inthere,wef o c u s o n t h e p a r e n t ’ s e d u c a t i o n a n d p a r e n t ’ s E n g l i s h l e v e l asw e l l a s t h e i n c o m e structureinHCMCity.Secondly,thesectionsummarizestheEn glisheducationsysteminH o ChiMinhCity.Thirdly,thestudycomesoutwiththeempirical analysisresultsofthec o l l e c t e d data.
Generalinformationof theHousehold’scharacteristicin HCM City
Fromthesurvey,thestudyfindthattheparents’educationlevelofhouseholdwhichh a s c h i l d r e n a t p r i m a r y s c h o o l a g e i n H o C h i M i n h Citym a i n l y b e l o n g t o S e n i o r h i g h s c h o o l a n d U n i v e r s i t y l e v e l I n t h e r e , t h e wifea n d t h e h u s b a n d h a v e n e a r l y e q u i v a l e n t e d u c a t i o n distribution.However,thehusbandseemshavinghighereducationlevelthan thew i f e ingeneral.Aswe canseeinthebelowfigure4.1,thepercentageof husbandcompleteu n i v er s i t y i s 29.96%whileitisonly25.09%forthewife.Moreover,withintheconductedh o u s e h o l d s , t hehouseholdhashusbandfinishPhysicalofDoctordegreeare7.87%wh er easthereisnohous eholdwithwifegetthishigheducationlevel.
(2)parents’educationlevelinHCMCitysubstantiallydistributeinnoeducation,primaryan djuniorhighschoolandseniorhighschool.Besides,theparentsg e t universityalsotakesaconsi derablenumberat11.69%intotal.
GeneralinformationofEnglisheducationinVietnam
InVietnam,the Englishingeneraleducationis assignedasacompulsorysub jectf r o m juniorhighschoolandseniorhighschool.Fromtheyear1982to2002,itwassetinto
12.However,a f t er 2002, Englishisaforcedsubject forjunior andsenior highschool aswell asbeingane l e c t i v e subjectatprimaryschool.Inprimaryschool,Englishistaughtfr omclass3–
5w i t h t w o p e r i o d s w e e k , w h e r e a s , i t i n c r e a s e s t o t h r e e p e r i o d s p e r w e e k f o r j u n i o r a n d se n i o r h i g h s c h o o l T h i s n e w E n g l i s h l a n g u a g e t e a c h i n g p r o g r a m h a s b e e n u s e d f o r t h e w h o l e generaleducationalsystemofVietnamtothepresent.Th eproposeofthisprogramistoequipthestudentafterfinishedseniorhighschoolabasic knowledgeofEnglishbeabletouseproficientlyEnglishatfourskills:listen,speak,readandwrit eandtheabilitytou n d e r s t a n d thesameleveloftextbookwiththeassistofdictionary.
According to the Ministry of Education and Training (MOET), the number of foreign language centers in Vietnam has significantly increased from 843 to 1,935 between 2008 and 2013 This growth highlights the rising demand for English education in the country Additionally, the National Foreign Languages 2020 Project, established under Decision No 1400/QD, aims to further enhance foreign language proficiency among Vietnamese students.
TTgsignedon30/9/2008byt h e PrimeMinisterto“Teachandlearnforeignlanguageinthenat ionaleducationsystem,p e r i o d 2008–
2020”.Itwasagreatandpotentialprojectifithaddonesuccessfully.Theprojectfirstlyd evelopsandissuestheunique,detailedqualificationsframeworkofforeignlanguage,including6 levels,compatiblewiththeinternationallanguageproficiencylevel.Secondly,developandim plementnewforeignlanguagetrainingprogramscompulsoryatthebasicschoolleveltomeet thefollowing qualifications after graduation:primaryschoollevel1qualificationsaccordingqualificationsframeworkoffor eignlanguage;juniorhighschoollevel2,seniorhighschoollevel3ofqualificationsframework offoreignlanguage.Thirdly,implementtrainingaccordingtonewforeignlanguage programfortheuniversity.E s t a b l i s h andimplementteachingbyEnglish insomebasicsubjectsandmajorsubjectsforthelastyearstudentofuniversity.
The current state of English teaching and learning in Vietnam remains inadequate In addition to school education, many parents enhance their children's English skills by enrolling them in various 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 investments and national expansion Furthermore, a variety of smaller centers and English education options at schools and homes are available to address the growing demand for English education in Vietnam, prompting both private and public institutions to establish programs to meet this need.
ImportanceofEnglishexpenditureinhousehold’sdecision
In Ho Chi Minh City, household spending on English education constitutes a significant portion of total educational expenditures, accounting for an average of 61.4% of basic education costs When compared to overall household income and total expenditures, English education represents 4.7% and 6.7%, respectively The study indicates that English education is viewed similarly to private tutoring, with 84.7% of households willing to invest in English lessons and 84.3% for additional classes Notably, most expenditures fall within the range of 300,000 VND to 500,000 VND per month.
Figure4.3The d i s t r i b u t i o n ofcur re nt E n g l i s h education expenditure inbasic edu ca ti on, totalincomeandtotalexpenditure
Empiricalanalysisresults
Descriptivestatistics
Thiss e c t i o n p r e s e n t s t h e d e s c r i p t i v e s t a t i s t i c s o f t h e v a r i a b l e s c o l l e c t e d f r o m t h e survey.Itprovidesreferentialinformationforlaterdiscussionofthemodel.Asthef o l l o w i n g , themaindependentvariableisdescribedbythehistogramgraphicswhile theexplanationv a r i a b l e s a r e s u m m a r i z e d s t a t i s t i c a l l y i n t a b l e 4 1 w h i c h i n c l u d e s m e a n o r frequency,maximum,m i n i m u m a n d s t a n d a r d d e v i a t i o n Itc a n b e s e e n fromt h e b e l o w f i g u r e s that84.7%householdagreetospendoneducatingEnglis hfortheirchildren.Them a j o r i t y householdsspendabout300,000VNDorlesspermonthandh oldsapproximately4 1 % intotalhouseholds.
Figure4.4HistogramgraphicofthecurrentpaymentforEnglisheducationinHoChiMinhCity( 0-noexpenditure forEnglisheducationatthepresent time,1- thecurrentexpenditureisrankedfrom0to300,000VND,2- thecurrentexpenditureisrankedfromabo ve300,000to500,000VND,3- thecurrentexpenditureisrankedfrom above500,000t o 1,000,000VND,4- thecurrentexpenditureisrankedfromabove1,000,000to2,000,000VND,5- thecurrentexpenditureisrankedfromabove2,000,000VND)
Dummy variable of current payment for English education
Figure4 5 H i s t o g r a m g r a p h i c o f t h e d u m m y v a r i a b l e o f c u r r e n t payment f o r E n g l i s h e d u c a t i o n inH o C h i M i n h City( 0 – n o e x p e n d i t u r e onE n g l i s h e d u c a t i o n , 1 – p r e s e n t expenditureonEnglisheducation)
Thes u r v e y s h o w s t h a t t h e g r o u p s o f h o u s e h o l d w h i c h g a i n t o t a l incomefrom5,000,000VNDto10,000,000VNDper monthmostlypredominateoverthehouseholdsinH o ChiMinh.Thebelowdistributionchart ofhousehold’stotalincomeinHoChiMinhCityp r e s e n t s t h a t t h e h i g h e s t d e n s i t y b e l o n g s t o t h e middlei n c o m e g r o u p w h i c h t a k e s n e a r l y 70%intotal.Second isth elow incomegroup with23.60%.Andlastisthehigh incomegroupwhichisonly6.74% Inthefivegroupsdivisionofincomelevel,itshowst h a t thegroupofincomefrom5to10 millionVNDwhichtakesup40.07%ofthetotalsurveyedhouseholds.Nextdensitygroup sarethegroupofbelow5millionsVND( 2 3 6 0 % ) and10–
20millionsVND(20.60%).Similarly,thehighestincomegroupwithincomerangesover30millionsVNDisthelowestdensitywithonly6.75%intotal.Thisindicatesthatthemiddlein comegroupisthelargestdistributionofthehouseholdsinHoChiMinhCity.
Figure4.6Household’stotal incomedistribution inHoChiMinhCity.
( a ) Divided intof i v e groups:below5millionsVND,5–10millionsVND,10–
In the surveyed households, 74.15% allocate their monthly expenses between 3,500,000 VND and 5,000,000 VND, which accounts for 40.82% of total expenditures This expenditure level aligns with the income of the largest group, primarily consisting of middle-income families who prioritize spending on essential activities such as food, children's education, and healthcare There is a strong correlation between total household income and total expenditure, indicating that as income rises, so does the ability to spend and meet living demands Additionally, a significant portion of households invest in private tutoring for their children, with only 15.67% opting not to enroll them in extra classes, highlighting the growing interest of parents in enhancing their children's education.
The study explores the demographic characteristics of households in Ho Chi Minh City, focusing on factors such as parents' education, English proficiency, and the age and gender of the household head, as well as location and homeownership Notably, over 35% of parents are proficient in English, with a higher percentage of husbands than wives demonstrating this skill Additionally, 29.96% of husbands have completed university education, while the percentage for wives is lower Employment data reveals 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, employment in foreign companies and NGOs is less common Approximately 25% of individuals are freelancers, engaging in market trading or temporary labor Among surveyed households, 18.66% of wives are homemakers, and 77.9% of household heads are male Husbands' ages range from 26 to 58 years, while wives are aged between 25 and 55 years Furthermore, 75% of households are located in urban areas, and more than 64% own their homes in Ho Chi Minh City Lastly, the average number of children per household is 1.65, reflecting a trend towards smaller families with one to two children at primary school age.
Cpe 15.30 cpe0 41.42 cpe1 19.40 cpe2 13.06 cpe3 cpe4 9.33 cpe5 1.49
Income dincome1 dincome2 dincome3 dincome4 dincome5
Totalexpe nditure 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 SeniorHS JuniorHS PrimaryVS College University Master PhD
6.74 15.36 28.84 8.99 0 29.96 2.25 7.87 eduw Primary SeniorHS JuniorHS PrimaryVS College University Master PhD
Englishh_0 38.20%husbandknow English 61.80%don’tknow English
Englishw_0 35.96%wifeknowEnglish 64.04%don’tknow English
Private(F oreign.) NGOs Stayatho me Others
Private(F oreign.) NGOs Stayatho me Others
Variable Mean Std.Dev Min Max
Appendixi n ordertoanalyzetherelationshipbetweenthesevariables.Thetableshowsth atthereisn o c o r r e l a t i o n b e t w e e n t h e e x p l a n a t i o n v a r i a b l e s e x c e p t t h e t w o p a i r o f v a r i a b l e s : theed u cat io n l e v e l o f t h e w i f e an d h u s b a n d a n d theag e o f w i f e a n d h u s b a n d Itp r e c i s e l y appropriatewiththecharacteristicofVietnam’ssocial.In addition,itisalsoexpressedont h e matrixcorrelationthatthehighincomegroupfivetendsto expensemoremoney.Andt h i s ca u se s t h e r a t h e r h i g h c o r r e l a t i o n b e t w e e n incomeg r o u p f i v e a n d t o t a l e x p e n d i t u r e g r o u p f i v e a n d s i x C o o r d i n a t i n g w i t h t h e co r r e l a t i o n b e t w e e n t o t a l e x p e n d i t u r e a n d t h e currentpaymentforEnglisheducation,se etheevidenceontheappendices.Itreinforcesthetheoryofincomeelasticityofeducationex penditureofBenson(1961).
The article examines the correlation between household income, total expenditure, and spending on English education As illustrated in Table 4.2, higher-income households tend to allocate more funds for their children's English education Specifically, households earning below 5 million VND per month primarily spend less, with 37% investing under 300,000 VND, 15% spending between 300,000–500,000 VND, and 27% contributing nothing In contrast, households with incomes exceeding 30 million VND are more likely to spend significantly on English education, particularly in the ranges of 1,000,000–2,000,000 VND and above 2,000,000 VND Additionally, total household expenditure influences education spending, with those who have higher overall expenses dedicating more to English education, particularly in the 1,000,000–2,000,000 VND range.
2,000,000VNDpermonthand2,000,000VNDp er month.V i c e v e r s a , t h e l o w l e v e l o f t otale x p e n d i t u r e h a s onlysup po rt ab le f o r t h e i r standardlivingandpaylessinEnglisheduc ation.
Regressionresults
Int h i s c h a p t e r , thestudya t t e m p t s t o a n s w e r t o t h e e x p o s e d q u e s t i o n s o n t h e resear ch q u e s t i o n s o f c h a p t e r o n e a n d r e l i e d o n t h e h y p o t h e s i s o f c h a p t e r t h r e e A s t h e ab o v e mention,thestudyfocusonidentifytheimportantofEnglish educationinVietnambyi n v e s t i g a t i n g t h e i m p a c t o f p a r e n t ’ s i n c o m e , p a r e n t w o r k i n g e n v i r o n m e n t , p a r e n t ’ s En glishlevelandotherdemographicissues wouldaffectonexpenditureonEnglishe d u c at i o n f o r t h e i r c h i l d r e n T h e t a b l e 4 5 s t a t e s t h e r e s u l t s o f t w o r e g r e s s i o n methodsw h i c h a r e d e f i n e d i n a d v a n c e i n t h e m e t h o d o l o g y s e c t i o n t o a n a l y s i s t h e r e l a t i o n s h i p betweentheseex planationvariablesandthecurrentpaymentforEnglisheducationofthec h i l d r e n inHoChi MinhCity.
Coefficient Coefficient Coefficient Marginal effect(dy /dx)
Coefficient Marginal effect(dy /dx) Income
Whereasmodel1 a n d 3 f o c u s o n i n v e s t i g a t i n g t o t a l incomec o r p o r a t e w i t h o t h e r e x p l a n a t o r y variables,model2and4paysattentionintestingtherelationshipbetweentotalexp enditurewi th o t h e r explanatory variablesandth e current sp en di ng f o r English edu cation.Itcanbeevidencedfromthefirstmodelthattotalincome,currentpaymentfore x t r a ed ucation,educationlevelofwifehasapositiverelationshipwithEnglisheducationexpenditure Inmoredetails,thereisthestatisticallysignificantinfluenceofhousehold’st o t a l i n c o m e t h e h i g h e s t incomeg r o u p , o v e r 2 0 millionsV N D , int h e e x p e n d i t u r e f o r
E n g l i s h e d u c a t i o n a t s i g n i f i c a n t l e v e l o f 1 % T h i s c o n s o l i d a t e s t h e p o i n t ofviewo f G leww eandDesai(1999),TanselandBircan(2006)andDonkohan dAmikuzuno(2011)thatthemoreincomethemorewillingtopayforextraeducation.
Model 1 indicates that expenditure on extra classes positively influences spending on English education at a 1% significance level Conversely, a wife's English proficiency negatively affects English education expenditure at a 5% significance level This can be attributed to the role of Vietnamese women, who often dedicate time to teaching their children at home Consequently, wives with higher English skills can instruct their children themselves, reducing the need for external English education costs Similarly, research by Huy (2012) demonstrates that a wife's education level significantly impacts the willingness to invest in their children's education, particularly in English, at a 1% significance level.
Thenextpointwouldconcerntheageofthewife.Thepositivecoefficientbetweenthea geofwifeandtheexpenseforEnglishshowsthatthemoreageofthewifethemorewillingto payfortheEnglisheducation.Itiscomputedat5%significantlevel.Thelastpo in tf r o m t h e O L S modeli s h o u s e h o l d o w n a houset e n d s t o s p e n d moreo n E n g l i s h educati on.It’struebecausewhenahouseholdgota house,theydon’thave payforhiringal i v i n g placeandalsohavenorusttoworryaboutthesavingtobuyahouse.H
The study examined various factors affecting household expenditure on English education, including total expenditure, parents' education, employment sector, and household demographics Model 2 revealed a positive relationship between total expenditure exceeding 10 million and spending on English education, significant at the 10% level When both total income and total expenditure were analyzed together, results indicated that either factor positively influences English education spending at a 5% significance level Other controlled variables remained consistent with Model 1, except for homeownership, which showed no significant impact on English education expenditure.
Next,model3providesthesimilarresultwithmodel1thatisthecurrentpaymentf o r extraclass,theageofwifeandthehouse’sownershiphaspositiveeffectontheEnglishexpenditureat1
The logistic model effectively analyzes the dependent variable, which indicates spending on English education represented as either zero (no expense) or one (expense incurred) Specifically, for each additional year in the wife's age, the odds of spending on English education increase by 0.176 Furthermore, households that own a home see a 1.010 increase in the odds of investing in English education The marginal effect calculation reveals that a one-unit increase in extra education payment raises the probability of spending on English education by 0.093 Additionally, an increase in the wife's age contributes to a 0.009 increase in the likelihood of making decisions regarding English education spending.
The results from model4 indicate a significant relationship between total expenditure and spending on English education, differing from model2 In model5, total expenditure notably impacts English education spending across all expenditure groups at 5% and 10% significance levels Specifically, households with expenditures below 10 million VND per month show a positive impact on English spending at 10%, while those exceeding 10 million VND per month demonstrate a stronger positive relationship at a 5% significance level The logistic model coefficients reveal that moving from lower expenditure groups to higher ones increases the odds of spending on English education significantly Furthermore, households with total expenditures over 10 million VND per month have a 0.104 higher probability of investing in English education compared to those below 2 million VND This underscores the importance of total household expenditure on education, particularly English Additional factors such as current payments for extra education, the age of the wife, and homeownership also play crucial roles in influencing English education expenditure, with marginal effects of 0.093 and 0.011, respectively, in model3.
Besides,t h e s t u d y h a s p e r f o r m e d t h e o r d e r e d l o g i t t e s t t o c o n s o l i d a t e t h e l o g i t modelandtheestimatedresultislistedintheappendix,table.Allofmodelsaretest edandr e p a i r e d fortheheteroskedasticity.Simultaneously,theMulticollinearitytestisalsocarrie do u t t o t e s t t h e c o l l i n e a r i t y b e t w e e n t h e c o n t r o l v a r i a b l e s a f t e r r u n n i n g O L S a n d L o g i t regression.ThelowvalueofmeanVIF(2.05)indicatesagoodmodelwithinsignifican tmul ti coll in earit y (seeappendix,table).
Conclusionsandrecommendations
Conclusion
This study explores the significance of English education in Ho Chi Minh City and the factors influencing household decisions on English education spending for primary school-aged children The findings reveal that 84.7% of households allocate funds for their children's English education from the start of school, highlighting its growing importance Key factors affecting English education expenditure include household characteristics such as income, the wife's education level, and her English proficiency In contrast, variables like the husband's education level, English proficiency, employment status, age, household location, and the number of children do not significantly impact current spending on English education The results underscore the wife's crucial role in financial decisions regarding education, reflecting her influence on the family's overall educational priorities.
Recommendations
UnderstandingtheimportantroleandtherequirementofEnglisheducationin HoC h i MinhCityinparticularly andgenerallyinVietnam,thestudyrecommendsthef o l l o w i n g t o t h e G o v e r n m e n t Ast h e a b o v e analysisr e s u l t s s t a t e t h e E n g l i s h e d u c a t i o n expendituredependsonthehous ehold’stotalincomeandthewifeeducationandEnglishl e v e l aswellasfactorofhomeow nership.However,thespendingisunequalbetweenthegroupso f h o u s e h o l d ’ s t o talinco me.Onlychildren b o r n inh o u s e h o l d w i t h t o t a l i n c o me o v e r 2 0 millionsV N D a r e s e n t t o a g o o d a n d h i g h q u a l i t y o f E n g l i s h e d u c a t i o n c l a s s
Whilesthelow- incomehouseholdshavenoabilitytospendonthataffordablemoney.Thisr a i s e s a n i n e q u i t y pr oblemin t h e c h i l d r e n ’ s e d u c a t i o n F o r t h i s r e a s o n , t h e G o v e r n m e n t s h o u l d i n t e r v e n e t o e n s u r e t h e e q u i t y i n e d u c a t i o n E n g l i s h b e t w e e n d i f f e r e n t c l a s s ofh o u s e h o l d ’ s income.Propagandizeandeducatetheconsciousofthehousehol d’swifetheimportant ofEnglisheducationsothattheypaymoreattentiontotheirchildren.Moreover,t h e studyprovide sthatmostofthefamilyappreciatetheEnglisheducationandtheysendt h e i r childrentothe Englishclassfromprimaryschoolage.Thus,shouldtheGovernmentc o n s i d e r t e a c h i n g
I n somed e v e l o p e d co u n t ri e s suchasthecountriesinEurope,theyhadappliedthebilingualeduc ationfromtheprimaryschoolwhereEnglishistaughtasasecondlanguage.
Limitations
The study acknowledges several limitations in data collection and methodology Firstly, due to privacy concerns, households were unable to provide direct figures regarding their total income and expenditures, only offering approximate monthly amounts Consequently, the information on income and expenditure was gathered using rank values and dummy variables, which may introduce bias Secondly, accurately calculating expenditures on English education for households sending children to international schools is challenging, as these costs cannot be distinctly separated from general education expenses As a result, the research primarily focuses on households in normal schools Lastly, due to time constraints, the study is limited to analyzing the English education status in Ho Chi Minh City and does not provide a comprehensive overview of English education across Vietnam, particularly in rural areas.
48 area.Therefore,thef u t u r e researchshouldattempttoextendthescopeofinvestigationandc arriedoutaccompaniedwiththeVHLSS surveybytheGovernment.Anotherinterestingissue which thestudyshouldconcernisthereversecausalityeffectofEnglisheducationexpenditureont h e i r f u t u r e i n c o m e F o u r t h l y , thestudycouldnot evaluate theincome elasticityofEnglishexpenditureaslongasthedependentvariableisnotastringvariable.H ence,wesuggestcalculatingtheincomeelasticityofEnglishexpenditureinordertoapproac hthewideandd e e p explanationforhouseholdexpenditureforEnglisheducationinthefutureresearch.
( 2 0 1 2 ) Analysiso f HouseholdE x p e n d i t u r e o n E d u c a t i o n i n Cyprus.CyprusE conomicPolicyReview,6(2),17-38.
(2011).T h e determinantso f householdeducatione x p e n d i t u r e i n Ghana.EducationalResea rch andReviews,6(8),570-579.
LanguageP r o f i c i e n c y amongU S Immigrants.American SociologicalReview,62(2),288- 305.doi: 10.2307/2657305
(1999).T h e economicsofschoolqualityinvestmentsindevelopingcountries:Anempiricalstudy of Ghana:MacmillanLondon.
Graddol,D (2008).Whyglobal English maymeantheendof ‘English as aForeignLanguage’.
(2012).Determinantsofparticipationandexpenditurepatternsofprivatet u i t i o n receiv edbyp r i m a r y schools t u d e n t s i n Penang,Malaysia:ane x p l o r a t o r y study.A s i a Paci ficJournalofEducation,32(1),35-51.
(1997) Privateeducationexpenditure ina‘freeeducation’country:thecaseofGreece.Inter nationalJournalofEducationalDevelopment,17(1),73-81.
Knight,J.,& Shi,L.(1996).EducationalAttainmentandtheRural‐UrbanDivideinChina.Oxford
( 1 9 6 1 ) E rr or s i n variablesandE n g e l curveanalysis.Econometrica:Journalo f t h e Econom etricSociety, 336-362.
(2006).TheHandbookofWorldEnglishes,eds.BrajKachru,YamunaKachruandCecilL.Ne lson,Oxford:Blackwell.
Nergis,A (2011).Foreignlanguageteachereducation inTurkey:A historicaloverview.Procedia-
(1999).W h a t educationproductionfunctionsr e a l l y show: a p o s i t i v e t h e o r y ofeducati onexpenditures.Economicsof EducationReview,18(2),223-239.
(2011).EducationalexpenditureinurbanChina:incomeeffects,familycharacteristicsandth e demandfordomestic andoverseaseducation.AppliedEconomics,43(24),3379-3394.
(1986).A n e x o g e n e i t y t e s t f o r a s i m u l t a n e o u s e q u a t i o n T o b i t m o d e l w i t h ana pplicationt o l a b o r s u p p l y Econometrica:Journalo f t h e EconometricSociety,679-685.
(1992).Shadoweducationandallocation in formalschooling: Transitionto universityinJapan.AmericanJournal ofSociology,1639-1657.
(2006).D e m a n d f o r educationi n Turkey:A t o b i t analysisofp r i v a t e t u t o r i n g expen ditures.EconomicsofEducationReview,25(3),303-313.
(2006).TheroleofEnglishinVietnam'sforeignlanguagepolicy:Abriefhistory.AnnualE A Educatio nConference2006,Perth,Australia.9,1-12.
(1992).Shadoweducationandallocation in formalschooling:Transitionto universityinJapan.AmericanJournal ofSociology,1639-1657.
(2006).D e m a n d f o r educationi n Turkey:A t o b i t analysisofp r i v a t e t u t o r i n g expen ditures.EconomicsofEducationReview,25(3),303-313.
F(1 7 , 245)= 15.75 Prob>F =0 0 0 0 0 R-squared = 0.4592 RootM S E = 94909 cpe Coef
4 cpe ced u he d u w englishh_0e n g l i s h w _ 0 soeh_
4 2.17 0.461415 cpec 1.19 0.841647 eduh 2.96 0.337550 eduw 3.38 0.295742 englishh_0 2.26 0.441967 englishw_0 2.37 0.421661 soeh_0 1.59 0.627896 soew_0 1.64 0.610243 wifeworking 1.22 0.819173 genderhh 1.06 0.947707 ageh 3.49 0.286877 agew 3.40 0.293784 local 1.18 0.846103 ownh 1.24 0.807576
Logpseudolikelihood=-80.705588 PseudoR2 = 0.2910 dcpe Coef RobustSt d.Err z P>|z| [95%Conf.Interval] incomet
4 cpec e du hed uw englishh_0e n g l i s h w _ 0 soeh_
= 94340895 variable dy/dx Std.Err z P>|z| [ 95%C.I ] X dinco~t2* d i n c o ~ t
~ t 4 * cpec ed u he d uw engl~h_0
F(1 8 , 244)= 18.02 Prob>F =0 0 0 0 0 R-squared = 0.4525 RootM S E = 95694 cpe Coef
RobustS t d E r r t P>|t| [95%C o n f I n t e r v a l dtotalexpt2 -.0409011 251212 -0.16 0.871 ] -.535722 453919 dtotalexpt3 0035058 2393392 0.01 0.988 -.4679287 474940 dtotalexpt4 2198905 3040206 0.72 0.470 -.3789491 818730 dtotalexpt5 6874581 3585757 1.92 0.056 -.0188406 1.39375 cpec 4552241 073478 6.20 0.000 3104921 599956 eduh -.0539666 0577517 -0.93 0.351 -.167722 059788 eduw 3086596 0809731 3.81 0.000 1491642 46815 englishh_0 0488498 1904441 0.26 0.798 -.3262744 423974 englishw_0 -.3558126 1872655 -1.90 0.059 -.7246759 013050 soeh_0 0817378 185508 0.44 0.660 -.2836637 447139 soew_0 -.2352022 1909597 -1.23 0.219 -.6113421 140937 wifeworking -.2760428 1772245 -1.56 0.121 -.625128 073042 genderhh -.0242883 1474851 -0.16 0.869 -.3147946 266218 ageh -.0051432 0165262 -0.31 0.756 -.0376953 02740 agew 0433232 0181667 2.38 0.018 0075395 079106 local 0542165 1396164 0.39 0.698 -.2207907 329223 ownh 2427965 1341195 1.81 0.071 -.0213831 506976 Nrofchildren -.0535274 0896321 -0.60 0.551 -.2300789 12302
Variable VIF 1/VIF dtotalexpt3 19.45 0.051414 dtotalexpt4 19.33 0.051727 dtotalexpt5 12.43 0.080422 dtotalexpt2 7.02 0.142376 eduw 3.52 0.283793 ageh 3.49 0.286735 agew 3.42 0.292610 eduh 2.85 0.351058 englishw_0 2.34 0.426472 englishh_0 2.26 0.443037 soew_0 1.67 0.597484 soeh_0 1.59 0.630849 cpec 1.29 0.775292 ownh 1.25 0.800912 wifeworking 1.24 0.808125 local 1.21 0.826600
RobustS t d E r r z P>|z| [95%C o n f I n t e r v a l dtotalexpt2 2.143534 1.294358 1.66 0.098 -.3933617 ] 4.68042 dtotalexpt3 2.263512 1.261546 1.79 0.073 -.2090731 4.73609 dtotalexpt4 2.419262 1.435419 1.69 0.092 -.3941084 5.23263 dtotalexpt5 3.888525 1.759674 2.21 0.027 4396263 7.33742 cpec 1.64758 4723387 3.49 0.000 7218131 2.57334 eduh -.0994752 1741595 -0.57 0.568 -.4408215 241871 eduw 1883084 2600612 0.72 0.469 -.3214021 69801 englishh_0 -.9710477 6419314 -1.51 0.130 -2.22921 287114 englishw_0 -.2666764 6403972 -0.42 0.677 -1.521832 98847 soeh_0 -.2999803 6442077 -0.47 0.641 -1.562604 962643 soew_0 -.5504442 6030762 -0.91 0.361 -1.732452 631563 wifeworking -.3144039 6618085 -0.48 0.635 -1.611525 982716 genderhh -.4665157 5253627 -0.89 0.375 -1.496208 563176 ageh -.0646416 065009 -0.99 0.320 -.1920569 062773 agew 1924707 0741705 2.59 0.009 0470992 337842 local 39491 4160752 0.95 0.343 -.4205823 1.21040 ownh 736127 4496512 1.64 0.102 -.1451731 1.61742 Nrofchildren -.1674733 3214882 -0.52 0.602 -.7975786 46263
= 93879449 variable dy/dx Std.Err z P>|z| [ 95%C.I ] X dtota~t2* d t o t a ~ t
~ t 4 * d t o t a ~ t 5 * cpec ed u he d uw engl~h_0
Table09–Statisticsummaryofvariablecpe/cpbe,cpe/income,cpe/totalexp
Variable Obs Mean Std.D e v Min Ma cpecpbe 267 6139513 7110703 0 x 4 cpeincome 267 0470075 0435199 0 3 cpetotalexp 267 06704 0515155 0 4705882
Currentpaymentfor extraclass Freq Percent Cum
Source SS df MS Numbero f o b s = 267
AdjR - = 0.2062 Total 411.198502 266 1.54585903 RootM S E = 1.1077 cpe Coef Std.E r r t P>|t| [95%C o n f I n t e r v a l dincome2 -.0075167 2249593 -0.03 0.973 ] -.450515 435481 dincome3 1816083 3129473 0.58 0.562 -.4346592 797875 dincome4 2338345 363168 0.64 0.520 -.4813296 948998 dincome5 1.104559 4581295 2.41 0.017 2023931 2.00672 dtotalexp2 6666667 5982413 1.11 0.266 -.5114126 1.84474 dtotalexp3 1.022503 5846873 1.75 0.082 -.1288853 2.17389 dtotalexp4 1.484905 6184192 2.40 0.017 267091 2.7027 dtotalexp5 1.950373 6677354 2.92 0.004 6354436 3.26530 dtotalexp6 1.727824 7812856 2.21 0.028 1892874 3.26636 _cons 25 5538639 0.45 0.652 -.8406895 1.34068
The correlation matrix reveals significant relationships among various explanatory variables related to income and total expenditures Notably, there is a negative correlation between income variables dincome2 and dincome3 (-0.42) and a positive correlation between total expenditures dtotalexp3 and dtotalexp4 (0.41) Additionally, educational variables such as eduh and eduw demonstrate a strong positive correlation (0.77), indicating a potential link between education levels and income Gender and age factors show minimal correlation with income, while the variable "wifeworking" presents a slight positive correlation with income variables Overall, the analysis suggests complex interdependencies among the variables, highlighting the importance of considering multiple factors when evaluating income and expenditure patterns.
The analysis of various factors reveals significant correlations among demographic variables, such as the number of children (Nrofchildren), income levels (dincome2 to dincome5), and educational attainment (eduh, eduw) Notably, the presence of children negatively impacts income and total expenditure, with coefficients indicating a downward trend The relationship between household gender dynamics (genderhh) and spousal employment (wifeworking) shows mixed effects, while age variables (ageh, agew) correlate positively with educational outcomes Locality (local) demonstrates minimal influence on these variables, suggesting that family structure and educational attainment may play a more critical role in economic stability.
Model1 Model2 Model3 Model4 Model5
OLS 1 OLS 2 Logit OrderedLogit Tobit dincome2 -0.1141 -0.0149 -0.8824 -0.3152 -0.1141 dincome3 -0.1302 0.1100 -1.1158 -0.2819 -0.1302 dincome4 0.0631 0.2830 0.7016 0.2856 0.0631 dincome5 1.1466 *** 1.2753 *** (omitted) 2.5108 *** 1.1466 *** dtotalexp2 -0.0173 1.9596 0.7523 -0.0173 dtotalexp3 0.0754 2.6390 1.1614 0.0754 dtotalexp4 0.2648 2.9232 * 1.5204 0.2648 dtotalexp5 0.3637 3.5090 1.5906 0.3637 dtotalexp6 -0.0792 (omitted) 0.2832 -0.0792 cpec 0.4903 *** 0.5083 *** 1.5987 *** 1.0854 *** 0.4903 *** eduh -0.0455 -0.0457 -0.1096 -0.1371 -0.0455 eduw 0.2839 *** 0.2909 *** 0.2883 0.6514 *** 0.2839 *** englishh_0 0.1231 0.0964 -0.9516 0.1391 0.1231 englishw_0 -0.4324 ** -0.4309 ** -0.5446 -0.9070 ** -0.4324 ** soeh_0 0.0452 0.0410 -0.2945 0.1520 0.0452 soew_0 -0.1284 -0.1321 -0.6157 -0.4450 -0.1284 wifeworking -0.2180 -0.2419 -0.2230 -0.4132 -0.2180 genderhh -0.0295 0.0203 -0.4308 0.0124 -0.0295 ageh -0.0034 -0.0019 -0.0545 -0.0308 -0.0034 agew 0.0428 ** 0.0410 ** 0.1826 *** 0.1140 *** 0.0428 ** local 0.0098 -0.0118 0.4860 0.1003 0.0098 ownh 0.2786 ** 0.2777 ** 0.8505 * 0.5253 * 0.2786 **
corincometotalexpcpe(obs&7) incometotalexp cpe income 1.0000 totalexp 0.8064 1.0000 cpe 0.4299 0.4521 1.0000
Source SS df MS Numberofobs = 263
The analysis reveals an Adjusted R-squared value of 0.4373, indicating a moderate fit of the model Among the variables, "dincome5" shows a significant positive coefficient of 1.1466 (p = 0.008), suggesting a strong impact on the outcome Conversely, "englishw_0" has a notable negative coefficient of -0.4324 (p = 0.021), indicating a significant adverse effect Additionally, "cpec" demonstrates a strong positive relationship with a coefficient of 0.4903 (p < 0.001) Other variables, such as "eduw," also show significance (p < 0.001) with a positive coefficient of 0.2839, while "agew" is significant with a positive coefficient of 0.0428 (p = 0.023) However, several variables, including "dincome2," "wifeworking," and "genderhh," do not show significant effects (p > 0.05) Overall, the results highlight key factors influencing the dependent variable, providing insights into the relationships between income, education, and other demographic variables.
Table17-Theresultsofthemodels(OLS,Logit,Tobit)
Coefficient Coefficient Marginalef fect(dy/dx)
Table18-Theresultsofthemodels(OLS,Logit,Tobit)
Coefficient Coefficient Marginalef fect(dy/dx)
Coefficient Marginalef fect(dy/dx)
Pleasetellusthefull nameo f yourfamily'smemb ers,startfromthehousehold's l e a d
Thefamily'smemberistheone wholiveandeattogetherwithy ourfamilyatl e a s t 6/12month sandsharestheexpenses
(Write the name ofdist ri ct )
Note oCenterofthecityincludeDist.1,3,4,5,6,7,8,10,11,BinhThanh,PhuNhuan,TanBinh,TanPhuandpartofDist.2o Suburbsareainclu deDist.2,9,12,BinhTan,BinhChanh,HocMon,CuChi
Pleaselet us know theeducationinformationofyourhousehold'smembers
Other(specific_ )…12 10 Whatisthetypeofthesc hool? Publicschool…
Gradeof Englishwh ich [name] a t t a i n (ifany) 12 Self- assessmenttheEngli shlevelof [name] Don'tknow…………0
Intermediate(goodcom muni cation)…… 2Advance(fluentin4skil ls(Listen,speak,r e a d , write…………3
13 14 FORTHECHILDREN Doesthe[name]takepartinan y E nglishclasswithinlast12months? Yes .1
Extralea rningEn glisha t English center d
Classname Price Divided Rank ofCPE
VND/month BeginnnerandPre- intermediatelevel(from6-
Forpreschoolchildren(below 6 VND/month yearsold)