(Luận văn) determinants of secondary school dropouts in vietnam, panel data evidence

t to UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ng INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS hi ep w n lo VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ad ju y th yi pl ua al n DETERMINANTS OF SECONDARY SCHOOL DROPOUT IN VIETNAM: A PANEL DATA EVIDENCE n va ll fu oi m at nh z z k jm ht LE ANH KHANG vb BY om l.c gm n a Lu MASTER OF ARTS IN DEVELOPMENT ECONOMICS n va y te re th HO CHI MINH CITY, JULY 2012 t to UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM ng INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS hi ep w n lo VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ad ju y th yi DETERMINANTS OF SECONDARY SCHOOL DROPOUT IN VIETNAM: A PANEL DATA EVIDENCE pl n ua al n va fu ll A thesis submitted in partial fulfilment of the requirements for the degree of m oi MASTER OF ARTS IN DEVELOPMENT ECONOMICS at nh z z k jm ht LE ANH KHANG vb By om l.c gm n Dr LE VAN CHON a Lu Academic Supervisor: n va y te re th HO CHI MINH CITY, JULY 2012 t to ACKNOWLEDGEMENT ng hi Joining classes of quantitative research project with STATA & VHLSS2008, ep hold by the Faculty of Development Economics of HCMC University of Economics w and the applied econometrics seminar by Prof Dr Ardeshir Sepehri from University n lo of Manitoba, Canada, have encouraged and yielded me confident to move this paper ad ahead y th ju I would like to express my thanks to Mr Phung Thanh Binh, Mr Truong Thanh yi Vu, Mr Nguyen Khanh Duy, Ms Ngo Hoang Thao Trang, and Mr Dang Dinh Thang pl ua al and all other people participated for arranging and conducting the quantitative research project with STATA & VHLSS2008 n n va I would like to express my appreciation to Dr Nguyen Hoang Bao who ll fu introduced the logistic regression model in explaining school dropout behavior at a oi m “sharing experience in doing research” seminar on August, 2010, hold by the Faculty nh of Development Economics of HCMC University of Economics at I would like to express my gratitude to Prof Dr Ardeshir Sepehri who has z z sparked the idea of analyzing VHLSS dataset by panel data methods to capture the ht vb unobserved heterogeneity k jm I would like to express my sincere thanks to Dr Le Van Chon, my supervisor, gm who provides me directive suggestions during the thesis performing I would like to thank all professors in the teaching board of MDE program, who om l.c have helped me accumulate valuable knowledge to acquire this study would like to express my thanks n a Lu To all my friends in MDE class 16, who give me emotional encouragements, I y thesis to my father te re wife and my son, to my family for spiritual supports In particular, I dedicate this n va Finally, I would like to express my deeply appreciation to my parents, to my th t to ng ABSTRACT hi ep This paper investigates the socioeconomic determinants of dropout behavior of Vietnamese children in secondary schools using the Vietnam Household Living w n Standard Survey for 2006 and 2008 and logistic regression model for Panel data lo ad Determinants are considered at individual, household, schooling, and regional levels ju y th My findings reveal that the unobserved individual characteristics account for 17% in propensity of dropping out of secondary schools in different years 2006 and 2008 yi pl Furthermore, the results disclose that child gender, child age, child ethnic, child al ua inactive days, household expenditure, household head gender, household head n education, the number of children between and 17 years old, cost of school, urban- va n rural, and regions have statistically significant relationship with secondary school ll fu dropout oi m at Vietnam nh Key Words: secondary school dropout; panel; logistic model; random effects; z z k jm ht vb om l.c gm an Lu n va ey t re th t to ng TABLE OF CONTENTS hi ep CHAPTER 1:INTRODUCTION CHAPTER 2:LITERATURE REVIEW w n 2.1 A standard model of household schooling investment decision lo Empirical studies of school dropout in the world 10 2.3 Empirical Studies of school dropout in Vietnam 12 ad 2.2 y th ju CHAPTER 3:VIETNAMESE SECONDARY EDUCATION – AN OVERVIEW15 yi pl CHAPTER 4:RESEARCH METHODOLOGY 20 al Data 20 4.2 Methodology 22 n ua 4.1 va n CHAPTER 5:THE RESULTS 29 fu Descriptive Statistics 29 5.2 Dropout rates and Children characteristics 31 ll 5.1 oi m nh 5.2.1 Dropout rates and Household characteristics 32 at z 5.2.2 Dropout rate and School characteristics 35 z Regression Results 37 jm 5.3 ht vb 5.2.3 Dropout rates and Regional characteristics 36 k CHAPTER 6:CONCLUSION 45 gm REFERENCES 47 l.c APPENDIX 52 om an Lu n va ey t re th t to ng LIST OF TABLES hi ep Table 4.1: Description of the variables 26 Table 5.1: Descriptive statistics 30 w n Table 5.2: Regression results of the Random-effects models 37 lo ad Table 5.3: The estimation of dropout probability, given initial probalibity P0 38 ju y th yi pl n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th t to ng LIST OF FIGURES hi ep Figure 3.1: Secondary school dropout rates 15 Figure 3.2: Gross enrollment rate by urban-rural 16 w n Figure 3.3: Gross enrollment rate by gender 17 lo ad Figure 3.4: Gross enrollment rate by region 17 ju y th Figure 3.5: Average expense on secondary education per schooling person in the past 12 months by urban-rural 18 yi pl Figure 3.6: Average expense on secondary education per schooling person in the past al ua 12 months by gender 18 n Figure 3.7: Average expense on secondary education per schooling person in the past va n 12 months by gender 19 fu ll Figure 3.8: Average expense on secondary education per schooling person in the past m oi 12 months by income quintile 19 nh Figure 5.1: Dropout rate and child age 32 at z Figure 5.2: Dropout rate and household expenditure quintile 32 z ht vb Figure 5.3: Dropout rate and years of schooling of household head 33 jm Figure 5.4: Dropout rate and number of children between and 17 years old 34 k Figure 5.5: Dropout rate and cost of school 35 gm Figure 5.6: Dropout rate and region 36 om l.c an Lu n va ey t re th t to ng LIST OF ABBREVIATIONS hi ep GSO: General Statistics Office HH: Household w n LMP: Linear Probability Model lo ad MOET: Ministry of Education and Training ju y th MP: Maximum Likelihood NA: Not Applicable yi pl OR: Odds Ratio ua al RE: Random-effects n VHLSS: Vietnam Household Living Standard Survey n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th t to CHAPTER 1: INTRODUCTION ng hi ep During the past two decades, Vietnam has achieved important results in education in terms of increased enrollment, improved school infrastructure and diversified w schooling forms (MOET, 2006) However, Vietnam is still facing critics on the quality n lo of education and struggling with the phenomenon of dropping out of school The net ad y th enrollment rates1 were 95.5% at primary level, 82.6% at lower secondary, and 56.7% at ju upper secondary level (GSO, 2011) The effects of school dropout are expounded in the yi costs of individual, community, and society Specifically, individual faces risk in pl ua al finding jobs; country struggles low-skilled labor force; and society expands rich and n poor gap These effects have raised concerns to many researchers around the world in va examining factors affect school dropout, and from that appropriate policies are n ll fu proposed to policy makers to find ways to mitigate the phenomenon oi m There are many factors which could influence early dropping out of school at nh Empirical studies point out four groups of influential factors: individual characteristics, household characteristics, school characteristics, and regional characteristics However, z z most of the empirical studies in Vietnam utilized the cross-sectional data to examine vb jm ht the effects of these factors on the dropout behavior (Behrman & Knowles, 1999; Vo Thanh Son et al., 2001; Vo Tri Thanh & Trinh Quang Long, 2005; Nguyen Linh k gm Phuong, 2006) Cross-sectional data face the possible problem of heteroskedasticity, l.c specifically the unobserved individual effects Panel data are advocated to control for om this an Lu By addressing above issues, in this research, I am aiming at using panel data, rather than cross-sectional data, to examine the influences of the socioeconomic n va th ey Net enrollment rate at z level is the number of pupils who in the ages of z level (according to the education law in 2005) and currently keep schooling at z level as a percentage of z level aged population Where, z is primary or lower secondary or upper secondary For example, if z is primary level then the net enrolment rate at primary level is a percentage of the number of pupils who aged from to 11 years old and currently keep schooling at primary level over the number of primary level aged population t re t to determinants on the dropout behavior of pupils in secondary schools in Vietnam with ng hi the aid of logistic regression model ep My study is endeavored to achieve three main objectives: (1) To determine factors w theoretically affecting the decision of dropping out of school; (2) To examine factors n lo statistically explaining the dropout behavior in secondary schools in Vietnam; and (3) ad To implicate ways to reduce the secondary school dropout rates in Vietnam The main y th ju question of the research is: “What are the determinants of secondary school dropout in yi Vietnam?” To answer this question, I divide it into two subquestions: (1) What are the pl ua al determinants theoretically influencing the decisions of dropping out of school? (2) Do these determinants statistically explain the dropout behavior in secondary schools in n n va Vietnam? The first subquestion will be answered by recalling literature review and ll fu empirical studies in the world and in Vietnam Determinants obtained by the first analyze the secondary data VHLSS oi m subquestion will be used for the second one by applying econometric method to nh at The paper is continued with a set of sections Section II recalls the literature z z review and empirical studies in the world and in Vietnam Section III provides an vb overview of education system in Vietnam with a brief picture of dropout situation ht k jm during 2000-2006 Section IV describes the dataset used and research methodology gm Section V presents the results based on descriptive statistics and econometric models om l.c Section VI comes up with main conclusions and policy implications an Lu n va ey t re th t to The difference in socio-economic development among regions leads the regional ng hi factor to be a must considered element in most of dropout researches The estimation ep reveals that, compared to the Red River Delta as reference, most of other regions have w higher dropout probalibity, except the South Central Coast with negative sign Notably, n lo Mekong Delta suffers the highest dropout probability with 3.25 times compared to the ad Red River Delta This is a huge disparity Given other things, by assuming an 10% y th ju initial dropout probability and the Red River Delta as reference, this number increases yi to 26.50% if children live in Mekong Delta; to 20.06% and 19.95% if living in pl ua al Northeast and Southeast respectively; to 17.50% and 16.89% if living in Northwest and Central Highlands correspondingly; to 14.46% for North Central; and a decrease to n n va 8.42% for South Central Coast However, in terms of statistical significance, only ll fu Mekong Delta, Southeast, and Northeast regions are subjected oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th 44 t to CHAPTER 6: CONCLUSION ng hi ep Dropping out of school is a classical issue which has being attracted many researchers who are looking for factors associated with the likelihood of dropping out w of school Empirically, there are four groups of factors significantly correlated with n lo school dropout: individual characteristics, household characteristics, school ad y th characteristics, and regional characteristics In this paper, I am empirically applying a ju random effects logit model to investigate determinants influencing dropout behavior at yi secondary school level By using a panel data from VHLSS2006 and VHLSS2008, I pl ua al found that there is somewhat difference in using a two-year panel data compared to a n cross-sectional data since the intra-class correlation was found with 17% correlation n va within a child’s propensity to drop out in different years 2006 and 2008 The reason is ll fu because there is not much change within a child in two-year periods Fixed-effect oi m model is the first choice for panel data but it is not sufficient as it just concerns on at nh within variation, then Random-effect model is second choice Hence, a Random-effect model is used to examine determinants of secondary school dropout The regression z z results confirms that child gender, child age, child ethnic, child inactive days, vb jm ht household expenditure, household head gender, household head education, number of children aged from to 17, cost of school, squared costs of school, rural-urban, and k gm regions are associated with the likelihood of dropping out of secondary schools These l.c relationships are all statistically significant at 0.1% level, except child inactive days om and rural-urban are at 5% level Interestingly, the paper found that boys are more an Lu likely to drop out of school than girls This finding is against empirical results where girls are more likely to drop out of school than boys Regional effect also plays va n significant role that we should consider, especially for children living in Mekong Delta 45 th more likely to drop out than girls, then the government should consider appropriate ey Basing on research outcomes, policies implications are obviously Since boys are t re with a very high dropout probability compared to children living in other regions t to policies to support boys Since children living in rural area and from non Kinh Hoa ng hi ethnic are more likely to be dropped out, then the government should focus on them to ep expand more supports Since the increasing in cost of school will cause more dropout w probability, then the government should extend fee subsidies, fee exemptions to poor n lo children Since household head educations support to reduce dropout rates, then the ad government should think about policies to improve household head education and of y th ju course this is a long-term policy as children education obtained today is household yi head education in the future Since the higher the number of children aged from to 17 pl ua al in a household is, the more the dropout probability the child suffers, then the government should encourage household to limit this number Since Mekong Delta n n va suffers more dropout probability than other regions, then the government should pay oi m disparity with other regions ll fu special attention to this region to have appropriate policies to eliminate dropout For a developing country like Vietnam, the data in this study is quite high in nh at quality However, there are remaining some limitations in common data at levels of z z characteristics: (1) we are expecting that, at the level of children characteristics, factors ht vb measure children’s knowledge, malnutrition status, playful tendency, or child marriage k jm have some effects on dropout behavior But the fact is that these information are not gm available in VHLSS; (2) Similarly for household characteristics with factors measure l.c parental interest in their children’s education, asking for help from parents or others; om (3) for school characteristics with factors capture teacher quality, teacher experience, an Lu teacher motivation of teaching (for money or others), teaching method, school quality, … ; and (4) for Mekong Delta region, the available observations are too little to set up n va an unique research on this region only as this region is suffering very high dropout rate 46 th paper These issues are suggested for further study ey the problem of causality between school dropout and child work are not dealt in this t re Additionally, inflation adjustment for household expenditure and costs of school and t to ng REFERENCES hi Admassie, A (2002) Allocation of children’s time endowment between schooling ep and work ZEF Discussion paper on development policy No 44, Berlin w n Alderman, H., Behram, J.R., & Lavy, V (2001) Child Health and School lo ad Enrollment: A Longitudinal Analysis The Journal of Human Resources- XXXVI, y th 36(1):185-205 ju Al-Samarrai, S., & Peasgood, T (1998) Educational attainments and household yi pl characteristics in Tanzania Economics of Education Review, 17(4), 395–417 ua al Becker, G.S (1967) Human capital and the personal distribution of income n W.S.Woitinsky lecture no.1, University of Michigan, USA va n Behrman, J.R., & Knowles, J.C (1999) Household income and child schooling in ll fu Vietnam World Bank Economic Review, Vol 13, No.2, pp211-256 oi m Ben-Porath, Y (1967) The production of human capital and the life cycle of at nh earnings Journal of Political Economy, 75, pp.352-365 Bilquees, F., & Saqib, N (2004) Drop-Out Rates and Inter-School Movements: z z Evidence from Panel Data Islamabad: Pakistan Institute of Development Economics vb jm ht Brown, P., & Park, A (2002) Education and poverty in Rural China Economics of Educational Review, 21, 523–541 k l.c gm Cameron, C & Trivedi, P (2009) Microeconometrics Using Stata College Station TX: Stata Press om Chernichovsky, D (1985) Socioeconomic and demographic aspects of school an Lu enrollment and attendance in rural Botswana Economic Development and Cultural Change, 33(2), 319–332 n va Coleman, J et al (1966) Equality of educational Opportunities Washington Villages Economic Development and Cultural Change, 54(2), 405–421 47 th Dostie, B., & Jayaraman, R (2006) Determinants of school enrollment in Indian ey t re DCUS GPO t to Duncan, G J., Yeung, W J., Brooks-Gunn, J., & Smith, J.R (1998) How much ng hi does child poverty affect the life chances of children? American Sociological Review, ep Vol 63, No pp 406-423 w Echevarria, C., & Merlo, A (1999) Gender Differences in Education in a n lo Dynamic Household Bargaining Model International Economic Review 40 (2), 265- ad 286 y th ju Ghuman, S., Behrman, J.R., & Gultiano, S (2006) Children’s Nutrition, School yi Quality and Primary School Enrollment in Philippines Working Paper Series, Volume, pl ua al 2006-24 Glick, P., & Sahn, D E (2000) Schooling of girls and boys in a West African n n va country: the effects of parental education, income and household structure Educations ll fu of Education review 19 (2000) 63-87 oi m Glewwe, P., & Jacoby, H.G (1995) An Economic Analysis of Delayed Primaryschool Enrolment in a Low-income Country: The Role of Early Childhood Nutrition nh at Review of Economics and Statistics, 77: 156-169 z z Grira, H (2001) Delayed School Enrolment in Bangladesh: Who Is Responsible vb Pantheon Sorbonne University and CNRS, Maison des Sciences Economiques ht k jm Gujarati, D (1995) Basic Econometrics, 3rd Edition Singapore: MacGraw-Hill, gm Inc.Press l.c Gujarati, D (2003) Basic Econometrics, 4rd Edition Singapore: MacGraw-Hill, om Inc.Press an Lu Hanum, E (2003) Poverty and basic education in Rural China: Villages, households, and girls’ and boys’enrollment Comparative Educational Review, 47(2), ey Quality? Determinants of Dropout Behavior in Developing Countries National Bureau t re Hanushek, E A., Lavy, V., & Hitomi, K (2006) Do Students Care about School n va 141–159 th of Economic Research 48 t to Le Thi Nhat Phuong (2008) Determinants of dropping out of school: the case of ng hi Vietnam Unpublished Master thesis Kansas State University Manhattan, Kansas ep McCaul, E (1989) Rural public school dropouts: Finding from high school and w beyond Research in Rural Education n lo Ngo Hoang Thao Trang (2010) Determinants of secondary school dropout in ad Vietnam Unpublished Master thesis University of Economics, HCMC Fulbright y th ju economics teaching programe yi Nguyen Linh Phuong (2006) Effects of social class and school conditions on pl ua al educational enrollment and achievement of boys and girls in rural Vietnam International Journal of Educational Research Vol 45, pp 153-175 n n va Oakland, T (1986a) Meeting adolescent need Four effective middle schools ll fu Chicago Panel on Public Policy and Finance oi m Oakland, T (1986b) Where's room 185? How schools can reduce their dropout problem Chicago Panel on Public Policy and Finance nh at Ono, H (2000) Are sons and daughters substitutable? A study of intra household z z allocation of resource in contemporary Japan Institution of Japanese studies vb Parish, W.L and Willis, R.J (1993) Daughters, education and family budgets: ht k jm Taiwan experiences Journal of Human Resources, Vol 28 pp.863 - 898 gm Pridmore, P (2007) Impact of health on education access and achievement: A l.c crossnational review of the research evidence CREATE Pathways to Access No 26 om Brighton: University of Sussex an Lu Psacharopoulos, G., & Arriagada, A.M (1989) The determinants of early age human capital formation:evidence from Brazil Economic Development and Cultural ey binary data” The Stata Journal 3, Number 1, pp 32-46 t re Rodriguez, G (2003) “Intra-class correlation in random-effects models for n va Change 37,683-708 th 49 t to Sabates, R., Hossain, A., & Lewin, K.M (2010) School Drop Out in Bangladesh: ng hi New Insights from Longitudinal Evidence CREATE Pathways to Access: Research ep Monograph No.49, University of Sussex w Schultz, P (1993) Returns to women’s education Yale University Economic n lo Growth Center Discussion Paper No 603 ad Sepehri, A., Sarma, S., & Simpson, W (2006) Does non-profit health insurance y th ju reduce financial burden? Evidence from the Vietnam living standards survey panel yi Health Economics 2006, 15:603-616 pl ua al STATA (2011) Longitudinal-Data/Panel-Data Reference Manual, Release 11 College Station TX: Stata Press n n va Tansel, A (1997) Schooling attainment, parental education, and gender in Cote ll fu D’Ivoire and Ghana Economic Development and Cultural Change, 45(4), 825–856 oi m Vo Tri Thanh & Trinh Quang Long (2005) Can Vietnam achieve one of its Millennium Development Goals? An analysis of schooling dropouts of children at nh William Davidson Institute z z Vo Thanh Son, et al (2001) School enrolments and dropouts Statistical vb Publishing House, Hanoi ht k jm Wolfe, B L., & Behrman, J R (1984) Who is schooled in developing countries? gm The roles of income, parental schooling, sex, residence and family size Economics of l.c Education Review, 3(3), 231–245 om Zimmerman, F J (2001) Determinants of school enrollment and performance in an Lu Bulgaria: The role of income among the poor and rich Contemporary Economic Policy, 19(1), 87–98 50 th Retrieved February 7, 2012, from http://www.moet.gov.vn/?page=11.10&view=3544 ey MOET (2011) Education Statistics from academic year 1999-2000 to 2010-2011 t re 2011, from http://en.moet.gov.vn/?page=6.1&view=3451 n va MOET (2006) Current Situation of Vietnamese Education Retrieved June 17, t to GSO (2004) Result of the Vietnam household living standards survey 2004 ng hi Available from http://www.gso.gov.vn/ ep GSO (2006) Result of the Vietnam household living standards survey 2006 w Available from http://www.gso.gov.vn/ n lo GSO (2008) Result of the Vietnam household living standards survey 2008 ad Available from http://www.gso.gov.vn/ y th ju GSO (2010) Result of the Vietnam household living standards survey 2010 yi Available from http://www.gso.gov.vn/ pl ua al GSO (2011) Vietnam Population and housing census 2009 - Education in Vietnam: An analysis of key indicators Available from n n va http://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=11080 ll fu The Education Law (2005) Available from oi m http://en.moet.gov.vn/?page=8.8&view=5101 at nh z z k jm ht vb om l.c gm an Lu n va ey t re th 51 t to ng APPENDIX hi ep Appendix 1: Dropout rates in General education (%) Year Lower secondary Upper secondary w n 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 8.51 7.3 5.91 5.9 5.72 5.12 7.68 6.35 8.18 7.19 7.71 8.29 lo ad Source: MOET (2011) ju y th Appendix 2: Gross enrollment rates by urban-rural, gender, and region (%) Lower secondary yi Year 2006 pl 2010 Upper secondary Lower secondary Upper secondary Lower secondary Upper secondary 85.7 70.1 96.9 95.6 86.9 70 96.4 93.3 84.4 67.6 72.6 74.6 96.4 95.3 69.6 78.3 94.2 93.9 67.6 76.4 99.1 99.5 93.5 101.9 100.2 87.7 93.4 89.1 87.6 72.7 51.6 82.5 78 63 72.8 58.6 96.7 95.8 n Urban Rural ua al Rural-Urban 2008 101.4 104.7 92.8 99.3 98.2 91.9 91.9 86.8 oi m Region Red River Delta North East North West North Central Coast South Central Coast Central Highlands South East Mekong River Delta ll 96.9 95 fu Male Female n va Gender at nh z z k jm ht vb 87.1 78.6 53.6 83.5 78.7 63.2 72.1 55.7 gm Source: GSO (2006, 2008, 2010) om l.c an Lu n va ey t re th 52 t to Appendix 3: Average expenses on secondary education per schooling person in the ng hi past 12 months by urban-rural, gender, region, and income quintile ep w 2004 Lower Upper secondary secondary n Year lo 2006 Lower Upper secondary secondary Unit: VND 1,000 2008 Lower Upper secondary secondary ad Rural-Urban Gender 1,031 427 1,471 909 1,425 519 2,148 1,142 2,169 716 3,176 1,450 552 550 1,032 1,086 725 712 1,347 1,472 1,037 1,108 1,936 1,947 720 453 266 579 680 726 1,360 575 1,371 882 782 1,128 1,602 1,537 2,466 1,085 1,153 676 316 734 882 820 2,306 751 1,895 1,336 891 1,471 2,018 1,775 3,543 1,522 831 968 1,158 1,767 2,191 531 687 869 1,282 2,535 1,085 1,303 1,578 1,998 3,634 ju y th Urban Rural yi pl Male Female n ua al n va ll fu oi m at nh z z jm ht om l.c gm Source: GSO (2004, 2006, 2008) k 382 493 647 1,046 1,356 vb Region Red River Delta North East North West North Central Coast South Central Coast Central Highlands South East Mekong River Delta Income Quintile Quintile Quintile Quintile Quintile Quintile an Lu n va ey t re th 53 t to ng hi ep Appendix 4: Between variation and within variation Variables w n lo Year ad ju y th Dropout yi 0.069 0.499 14.554 n ua al Child age Mean 2007 pl Child gender va om an Lu n va ey t re th 54 Observations N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 l.c 2.083 gm 7.774 Max 2008 2007 2008 0.5 0.569 1 0.499 18 17.5 16.054 1 0.838 33 20.54 17.824 1 0.610 30 18.5 15.506 309,501 257,319 257,319 1 1.320 1 1.406 19 19 13.774 7 3.583 k 0.906 jm 0.820 ht 28,347 vb Number of children (1~17) 0.506 Min 2006 2007 2006 0 -0.431 0 0.499 11 11.5 13.054 0 0.838 0 -15.176 0 -0.390 0 -14.494 4,097 5,996 -82,659 0 0.320 0 0.406 0 1.774 0.5 0.583 z Household head education z Household head marital status 0.110 at Household head gender oi Household expenditure 1.324 m Child inactive days ll Child ill fu Child work 0.838 n Child ethnic Std Dev 1 0.254 0.173 0.186 0.5 0.5 1.938 1.665 0.992 0.369 0.369 4.006 2.932 2.730 0.314 0.234 0.209 2.731 1.974 1.887 18,923 17,147 8,008 0.384 0.376 0.079 0.291 0.279 0.085 3.710 3.623 0.802 1.021 0.953 0.365 nh Variation overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within overall between within t to ng Cost of school hi ep Distance to school w n lo Urban-rural ad ju y th Region overall between within overall between within overall between within overall between within 10.700 12.003 9.476 7.370 2.274 2.022 1.041 0.415 0.413 0.042 2.523 2.523 1.803 0.221 4.274 0 -143.425 0 -8.697 0 -0.279 1 4.274 321.250 167.125 164.825 23.400 20.488 12.303 1 0.721 8 4.274 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 N = 3,738 n = 1,869 T=2 yi pl Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 n ua al n va ll fu oi m at nh z z k jm ht vb om l.c gm an Lu n va ey t re th 55 t to Appendix 5: Bivariate relationships between dropout factors and dropout rates ng hi ep Variables w Gender n lo ad ju y th Child age (years old) yi pl n ua al n va Child ethnic ll fu at nh z k jm ht vb om l.c gm Household head education (years of schooling) oi Household head gender m Household expenditure5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 z an Lu n va Male Female 11 12 13 14 15 16 17 18 Kinh Hoa Not Kinh Hoa Quintile Quintile Quintile Quintile Quintile Male Female 10 11 Dropout rate (%) 2006 2008 (n=1,869) (n=1,869) 57.53 42.47 4.35 4.6 7.59 14.33 20.97 17.35 16.94 11.75 24.75 27.23 16.02 14.89 12.61 6.65 14.5 10.95 26.92 29.63 36.76 27.17 14.46 18.38 14.85 22.68 16.83 10.96 4.35 2.27 ey t re Mean of summary of household expenditure (in VND): Quintile_1= 12,147,520; Quintile_2=18,171,225; Quintile_3=23,832,820; Quintile_4=31,865,265; Quintile_5=55,748,624 56 th t to ng hi ep w n lo ad ju y th Number of children (1~17) yi pl n ua al n va ll fu Cost of school (VND) oi m at nh k jm ht vb an Lu n va ey t re Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 om Region z Rural-Urban z Distance to school 4.36 0 11.65 12.63 12.79 15.19 20.29 30 33.33 100 1.16 4.35 6.04 16.57 15.27 11.45 25.1 23.53 11.37 10.44 14.08 17.43 15.73 7.38 8.33 16.36 17.28 11.67 9.52 15.98 15.83 20.52 l.c 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 gm 12 15 17 19 200,000 300,000 500,000 600,000 700,000 800,000 1,000,000 1,300,000 1,800,000 3,600,000 Less than Km From Km to Km More than Km Rural area Urban area Red River Delta North East North West North Central Coast South Central Coast Central Highlands South East Mekong River Delta th 57 t to Appendix 6: Check Sensitivity of Quadrature Approximation by Quadchk command ng hi ep Dropout: Fitted quadrature 12 points w n lo ad ju y th yi pl n ua al n va ll fu m at nh z z -3.250e-06 -4.819e-06 -3.628e-06 -6.827e-06 -6.286e-06 -2.875e-06 -2.888e-06 -.0000861 -3.951e-06 -3.453e-06 -4.350e-06 -4.141e-06 -4.788e-06 -7.339e-06 -6.719e-06 -8.694e-06 -5.919e-06 -6.714e-06 -7.933e-06 -3.378e-06 -4.462e-06 vb 3.101e-09 4.580e-09 3.365e-09 6.117e-09 5.475e-09 2.611e-09 2.626e-09 6.477e-08 3.775e-09 3.183e-09 3.929e-09 3.725e-09 -9.215e-10 6.486e-09 5.873e-09 7.723e-09 5.082e-09 6.554e-09 6.587e-09 2.865e-09 4.042e-09 jm ht 0.5016 0.3867 -1.0437 -0.4972 0.0702 -1.1845 0.7577 -0.0140 -0.2052 0.4539 0.5520 -0.0124 0.0060 -0.6103 0.8149 0.6468 0.4194 -0.1896 0.6041 0.8075 1.1771 oi Child gender Child age Child ethnic Child ill Child inactive days Log of household expenditure Household head gender Household head marital status Household head education Number of children (1~17) Cost of school Squared cost of school Distance to school Urban-Rural Northeast Northwest North Central South Central Coast Central Highlands Southeast Mekong Delta Relative difference Comparison quadrature Comparison quadrature points 16 points k Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 gm Page 11, in the book “Longitudinal-Data/Panel-Data Reference Manual, Release 11” l.c by Stata Press, quoted “Quadchk is intended as a tool to help you know whether you om have a good quadrature approximation As a rule of thumb, if the coefficients not an Lu change by more than a relative difference of 10-4 (0.01%), the choice of quadrature va points does not significantly affect the outcome, and the results may be confidently n interpreted However, if the results change appreciably – greater than a relative ey th likelihood.” t re difference of 10-2 (1%) – then the quadrature is not reliably approximating the 58