Determinants of secondary school dropouts in vietnam panel data evidence

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF SECONDARY SCHOOL DROPOUT IN VIETNAM: A PANEL DATA EVIDENCE BY LE ANH KHANG MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, JULY 2012 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS DETERMINANTS OF SECONDARY SCHOOL DROPOUT IN VIETNAM: A PANEL DATA EVIDENCE A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LE ANH KHANG Academic Supervisor: Dr LE VAN CHON HO CHI MINH CITY, JULY 2012 ACKNOWLEDGEMENT Joining classes of quantitative research project with STATA & VHLSS2008, hold by the Faculty of Development Economics of HCMC University of Economics and the applied econometrics seminar by Prof Dr Ardeshir Sepehri from University of Manitoba, Canada, have encouraged and yielded me confident to move this paper ahead I would like to express my thanks to Mr Phung Thanh Binh, Mr Truong Thanh Vu, Mr Nguyen Khanh Duy, Ms Ngo Hoang Thao Trang, and Mr Dang Dinh Thang and all other people participated for arranging and conducting the quantitative research project with STATA & VHLSS2008 I would like to express my appreciation to Dr Nguyen Hoang Bao who introduced the logistic regression model in explaining school dropout behavior at a “sharing experience in doing research” seminar on August, 2010, hold by the Faculty of Development Economics of HCMC University of Economics I would like to express my gratitude to Prof Dr Ardeshir Sepehri who has sparked the idea of analyzing VHLSS dataset by panel data methods to capture the unobserved heterogeneity I would like to express my sincere thanks to Dr Le Van Chon, my supervisor, who provides me directive suggestions during the thesis performing I would like to thank all professors in the teaching board of MDE program, who have helped me accumulate valuable knowledge to acquire this study To all my friends in MDE class 16, who give me emotional encouragements, I would like to express my thanks Finally, I would like to express my deeply appreciation to my parents, to my wife and my son, to my family for spiritual supports In particular, I dedicate this thesis to my father ABSTRACT This paper investigates the socioeconomic determinants of dropout behavior of Vietnamese children in secondary schools using the Vietnam Household Living Standard Survey for 2006 and 2008 and logistic regression model for Panel data Determinants are considered at individual, household, schooling, and regional levels 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 Furthermore, the results disclose that child gender, child age, child ethnic, child inactive days, household expenditure, household head gender, household head education, the number of children between and 17 years old, cost of school, urbanrural, and regions have statistically significant relationship with secondary school dropout Key Words: secondary school dropout; panel; logistic model; random effects; Vietnam TABLE OF CONTENTS CHAPTER 1:INTRODUCTION CHAPTER 2:LITERATURE REVIEW 2.1 A standard model of household schooling investment decision 2.2 Empirical studies of school dropout in the world 10 2.3 Empirical Studies of school dropout in Vietnam 12 CHAPTER 3:VIETNAMESE SECONDARY EDUCATION – AN OVERVIEW15 CHAPTER 4:RESEARCH METHODOLOGY 20 4.1 Data 20 4.2 Methodology 22 CHAPTER 5:THE RESULTS 29 5.1 Descriptive Statistics 29 5.2 Dropout rates and Children characteristics 31 5.2.1 Dropout rates and Household characteristics 32 5.2.2 Dropout rate and School characteristics 35 5.2.3 Dropout rates and Regional characteristics 36 5.3 Regression Results 37 CHAPTER 6:CONCLUSION 45 REFERENCES 47 APPENDIX 52 LIST OF TABLES Table 4.1: Description of the variables 26 Table 5.1: Descriptive statistics 30 Table 5.2: Regression results of the Random-effects models 37 Table 5.3: The estimation of dropout probability, given initial probalibity P0 38 LIST OF FIGURES Figure 3.1: Secondary school dropout rates 15 Figure 3.2: Gross enrollment rate by urban-rural 16 Figure 3.3: Gross enrollment rate by gender 17 Figure 3.4: Gross enrollment rate by region 17 Figure 3.5: Average expense on secondary education per schooling person in the past 12 months by urban-rural 18 Figure 3.6: Average expense on secondary education per schooling person in the past 12 months by gender 18 Figure 3.7: Average expense on secondary education per schooling person in the past 12 months by gender 19 Figure 3.8: Average expense on secondary education per schooling person in the past 12 months by income quintile 19 Figure 5.1: Dropout rate and child age 32 Figure 5.2: Dropout rate and household expenditure quintile 32 Figure 5.3: Dropout rate and years of schooling of household head 33 Figure 5.4: Dropout rate and number of children between and 17 years old 34 Figure 5.5: Dropout rate and cost of school 35 Figure 5.6: Dropout rate and region 36 LIST OF ABBREVIATIONS GSO: General Statistics Office HH: Household LMP: Linear Probability Model MOET: Ministry of Education and Training MP: Maximum Likelihood NA: Not Applicable OR: Odds Ratio RE: Random-effects VHLSS: Vietnam Household Living Standard Survey CHAPTER 1: INTRODUCTION During the past two decades, Vietnam has achieved important results in education in terms of increased enrollment, improved school infrastructure and diversified schooling forms (MOET, 2006) However, Vietnam is still facing critics on the quality of education and struggling with the phenomenon of dropping out of school The net enrollment rates1 were 95.5% at primary level, 82.6% at lower secondary, and 56.7% at upper secondary level (GSO, 2011) The effects of school dropout are expounded in the costs of individual, community, and society Specifically, individual faces risk in finding jobs; country struggles low-skilled labor force; and society expands rich and poor gap These effects have raised concerns to many researchers around the world in examining factors affect school dropout, and from that appropriate policies are proposed to policy makers to find ways to mitigate the phenomenon There are many factors which could influence early dropping out of school Empirical studies point out four groups of influential factors: individual characteristics, household characteristics, school characteristics, and regional characteristics However, most of the empirical studies in Vietnam utilized the cross-sectional data to examine 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 Phuong, 2006) Cross-sectional data face the possible problem of heteroskedasticity, specifically the unobserved individual effects Panel data are advocated to control for this 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 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 determinants on the dropout behavior of pupils in secondary schools in Vietnam with the aid of logistic regression model My study is endeavored to achieve three main objectives: (1) To determine factors theoretically affecting the decision of dropping out of school; (2) To examine factors statistically explaining the dropout behavior in secondary schools in Vietnam; and (3) To implicate ways to reduce the secondary school dropout rates in Vietnam The main question of the research is: “What are the determinants of secondary school dropout in Vietnam?” To answer this question, I divide it into two subquestions: (1) What are the determinants theoretically influencing the decisions of dropping out of school? (2) Do these determinants statistically explain the dropout behavior in secondary schools in Vietnam? The first subquestion will be answered by recalling literature review and empirical studies in the world and in Vietnam Determinants obtained by the first subquestion will be used for the second one by applying econometric method to analyze the secondary data VHLSS The paper is continued with a set of sections Section II recalls the literature review and empirical studies in the world and in Vietnam Section III provides an overview of education system in Vietnam with a brief picture of dropout situation during 2000-2006 Section IV describes the dataset used and research methodology Section V presents the results based on descriptive statistics and econometric models Section VI comes up with main conclusions and policy implications The difference in socio-economic development among regions leads the regional factor to be a must considered element in most of dropout researches The estimation reveals that, compared to the Red River Delta as reference, most of other regions have higher dropout probalibity, except the South Central Coast with negative sign Notably, Mekong Delta suffers the highest dropout probability with 3.25 times compared to the Red River Delta This is a huge disparity Given other things, by assuming an 10% initial dropout probability and the Red River Delta as reference, this number increases to 26.50% if children live in Mekong Delta; to 20.06% and 19.95% if living in 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 8.42% for South Central Coast However, in terms of statistical significance, only Mekong Delta, Southeast, and Northeast regions are subjected 44 CHAPTER 6: CONCLUSION 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 of school Empirically, there are four groups of factors significantly correlated with school dropout: individual characteristics, household characteristics, school characteristics, and regional characteristics In this paper, I am empirically applying a random effects logit model to investigate determinants influencing dropout behavior at secondary school level By using a panel data from VHLSS2006 and VHLSS2008, I found that there is somewhat difference in using a two-year panel data compared to a cross-sectional data since the intra-class correlation was found with 17% correlation within a child’s propensity to drop out in different years 2006 and 2008 The reason is because there is not much change within a child in two-year periods Fixed-effect model is the first choice for panel data but it is not sufficient as it just concerns on 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 results confirms that child gender, child age, child ethnic, child inactive days, 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 regions are associated with the likelihood of dropping out of secondary schools These relationships are all statistically significant at 0.1% level, except child inactive days and rural-urban are at 5% level Interestingly, the paper found that boys are more 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 significant role that we should consider, especially for children living in Mekong Delta with a very high dropout probability compared to children living in other regions Basing on research outcomes, policies implications are obviously Since boys are more likely to drop out than girls, then the government should consider appropriate 45 policies to support boys Since children living in rural area and from non Kinh Hoa ethnic are more likely to be dropped out, then the government should focus on them to expand more supports Since the increasing in cost of school will cause more dropout probability, then the government should extend fee subsidies, fee exemptions to poor children Since household head educations support to reduce dropout rates, then the government should think about policies to improve household head education and of course this is a long-term policy as children education obtained today is household head education in the future Since the higher the number of children aged from to 17 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 suffers more dropout probability than other regions, then the government should pay special attention to this region to have appropriate policies to eliminate dropout disparity with other regions For a developing country like Vietnam, the data in this study is quite high in quality However, there are remaining some limitations in common data at levels of characteristics: (1) we are expecting that, at the level of children characteristics, factors measure children’s knowledge, malnutrition status, playful tendency, or child marriage have some effects on dropout behavior But the fact is that these information are not available in VHLSS; (2) Similarly for household characteristics with factors measure parental interest in their children’s education, asking for help from parents or others; (3) for school characteristics with factors capture teacher quality, teacher experience, 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 an unique research on this region only as this region is suffering very high dropout rate Additionally, inflation adjustment for household expenditure and costs of school and the problem of causality between school dropout and child work are not dealt in this paper These issues are suggested for further study 46 REFERENCES Admassie, A (2002) Allocation of children’s time endowment between schooling and work ZEF Discussion paper on development policy No 44, Berlin Alderman, H., Behram, J.R., & Lavy, V (2001) Child Health and School Enrollment: A Longitudinal Analysis The Journal of Human Resources- XXXVI, 36(1):185-205 Al-Samarrai, S., & Peasgood, T (1998) Educational attainments and household characteristics in Tanzania Economics of Education Review, 17(4), 395–417 Becker, G.S (1967) Human capital and the personal distribution of income W.S.Woitinsky lecture no.1, University of Michigan, USA Behrman, J.R., & Knowles, J.C (1999) Household income and child schooling in Vietnam World Bank Economic Review, Vol 13, No.2, pp211-256 Ben-Porath, Y (1967) The production of human capital and the life cycle of earnings Journal of Political Economy, 75, pp.352-365 Bilquees, F., & Saqib, N (2004) Drop-Out Rates and Inter-School Movements: Evidence from Panel Data Islamabad: Pakistan Institute of Development Economics Brown, P., & Park, A (2002) Education and poverty in Rural China Economics of Educational Review, 21, 523–541 Cameron, C & Trivedi, P (2009) Microeconometrics Using Stata College Station TX: Stata Press Chernichovsky, D (1985) Socioeconomic and demographic aspects of school enrollment and attendance in rural Botswana Economic Development and Cultural Change, 33(2), 319–332 Coleman, J et al (1966) Equality of educational Opportunities Washington DCUS GPO Dostie, B., & Jayaraman, R (2006) Determinants of school enrollment in Indian Villages Economic Development and Cultural Change, 54(2), 405–421 47 Duncan, G J., Yeung, W J., Brooks-Gunn, J., & Smith, J.R (1998) How much does child poverty affect the life chances of children? 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The roles of income, parental schooling, sex, residence and family size Economics of Education Review, 3(3), 231–245 Zimmerman, F J (2001) Determinants of school enrollment and performance in Bulgaria: The role of income among the poor and rich Contemporary Economic Policy, 19(1), 87–98 MOET (2006) Current Situation of Vietnamese Education Retrieved June 17, 2011, from http://en.moet.gov.vn/?page=6.1&view=3451 MOET (2011) Education Statistics from academic year 1999-2000 to 2010-2011 Retrieved February 7, 2012, from http://www.moet.gov.vn/?page=11.10&view=3544 50 GSO (2004) Result of the Vietnam household living standards survey 2004 Available from http://www.gso.gov.vn/ GSO (2006) Result of the Vietnam household living standards survey 2006 Available from http://www.gso.gov.vn/ GSO (2008) Result of the Vietnam household living standards survey 2008 Available from http://www.gso.gov.vn/ GSO (2010) Result of the Vietnam household living standards survey 2010 Available from http://www.gso.gov.vn/ GSO (2011) Vietnam Population and housing census 2009 - Education in Vietnam: An analysis of key indicators Available from http://www.gso.gov.vn/default_en.aspx?tabid=515&idmid=5&ItemID=11080 The Education Law (2005) Available from http://en.moet.gov.vn/?page=8.8&view=5101 51 APPENDIX Appendix 1: Dropout rates in General education (%) Year Lower secondary Upper secondary 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 Source: MOET (2011) Appendix 2: Gross enrollment rates by urban-rural, gender, and region (%) 2006 Year 2008 2010 Lower secondary Upper secondary Lower secondary Upper secondary Lower secondary Upper secondary Urban Rural 96.7 95.8 85.7 70.1 96.9 95.6 86.9 70 96.4 93.3 84.4 67.6 Male Female 96.9 95 72.6 74.6 96.4 95.3 69.6 78.3 94.2 93.9 67.6 76.4 Region Red River Delta North East North West North Central Coast South Central Coast Central Highlands South East Mekong River Delta 101.4 104.7 92.8 99.3 98.2 91.9 91.9 86.8 87.1 78.6 53.6 83.5 78.7 63.2 72.1 55.7 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 Rural-Urban Gender Source: GSO (2006, 2008, 2010) 52 Appendix 3: Average expenses on secondary education per schooling person in the past 12 months by urban-rural, gender, region, and income quintile 2004 Lower Upper secondary secondary Year 2006 Lower Upper secondary secondary Unit: VND 1,000 2008 Lower Upper secondary secondary Rural-Urban Urban Rural 1,031 427 1,471 909 1,425 519 2,148 1,142 2,169 716 3,176 1,450 Male Female 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 1,522 382 493 647 1,046 1,356 831 968 1,158 1,767 2,191 531 687 869 1,282 2,535 1,085 1,303 1,578 1,998 3,634 Gender 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 Source: GSO (2004, 2006, 2008) 53 Appendix 4: Between variation and within variation Variables Year Dropout Child gender Child age Child ethnic Child work Child ill Child inactive days Household expenditure Household head gender Household head marital status Household head education Number of children (1~17) 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 Mean 2007 0.069 0.499 14.554 0.838 1.324 0.110 0.506 28,347 0.820 0.906 7.774 2.083 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 54 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 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 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 Cost of school Distance to school Urban-rural Region overall between within overall between within overall between within overall between within 10.700 1.803 0.221 4.274 12.003 9.476 7.370 2.274 2.022 1.041 0.415 0.413 0.042 2.523 2.523 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 Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 55 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 Appendix 5: Bivariate relationships between dropout factors and dropout rates Variables Gender Child age (years old) Child ethnic Household expenditure5 Household head gender Household head education (years of schooling) Male Female 11 12 13 14 15 16 17 18 Kinh Hoa Not Kinh Hoa Quintile Quintile Quintile Quintile Quintile Male Female 10 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 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 Number of children (1~17) Cost of school (VND) Distance to school Rural-Urban Region 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 57 Appendix 6: Check Sensitivity of Quadrature Approximation by Quadchk command Dropout: 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 Fitted quadrature 12 points 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 Relative difference Comparison quadrature Comparison quadrature points 16 points 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 -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 Source: Author’s calculation using panel data from VHLSS2006 & VHLSS2008 Page 11, in the book “Longitudinal-Data/Panel-Data Reference Manual, Release 11” by Stata Press, quoted “Quadchk is intended as a tool to help you know whether you have a good quadrature approximation As a rule of thumb, if the coefficients not change by more than a relative difference of 10-4 (0.01%), the choice of quadrature points does not significantly affect the outcome, and the results may be confidently interpreted However, if the results change appreciably – greater than a relative difference of 10-2 (1%) – then the quadrature is not reliably approximating the likelihood.” 58 ... in Vietnam; and (3) To implicate ways to reduce the secondary school dropout rates in Vietnam The main question of the research is: “What are the determinants of secondary school dropout in Vietnam? ”... Thanh and Trinh Quang Long (2005) identify the underlying determinants of the schooling dropout in Vietnam by separately using data from three Vietnam s Living Standard Surveys conducted in 1992/93,... on the same individual at different points in time are called panel data or longitudinal data In this research, I am using panel data to examine the school dropout phenomenon at secondary level