(Luận văn) impacts of migration and migrant’s gender on children’s school enrollment and child work in viet nam

t to UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES ng HO CHIMINH CITY THE HAGUE hi ep VIETNAM THE NETHERLANDS w n lo VIETNAM - NETHERLANDS ad PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ju y th yi pl ua al n IMPACTS OF MIGRATION AND MIGRANT’S GENDER ON CHILDREN’S SCHOOL ENROLLMENT AND CHILD WORK IN VIET NAM n va ll fu oi m at nh z z k jm VÕ THỊ THU HOÀI ht vb BY om l.c gm an Lu MASTER OF ARTS IN DEVELOPMENT ECONOMICS n va ey t re th HO CHI MINH CITY, APRIL 2014 i t to UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES THE HAGUE ng HO CHIMINHCITY hi ep VIETNAM THE NETHERLANDS w n lo ad VIETNAM - NETHERLANDS y th PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS ju yi pl n ua al n va ll fu IMPACTS OF MIGRATION AND MIGRANT’S GENDER ON CHILDREN’S SCHOOL ENROLLMENT AND CHILD WORK IN VIET NAM oi m at nh z A thesis submitted in partial fulfilment of the requirements for the degree of z vb k jm ht MASTER OF ARTS IN DEVELOPMENT ECONOMICS om an Lu VÕ THỊ THU HOÀI l.c gm By n va th ii ey Dr TRAN TIEN KHAI t re Academic Supervisor t to CERTIFICATION ng “I certify that the substance of this dissertation has not already been submitted for any hi ep degree and is not currently submitted for any other degree I certify that to the best of my knowledge and help received in preparing this dissertation w n and all source used, have been acknowledged in this dissertation” lo ad ju y th VO THI THU HOAI 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 iii t to ACKNOWLEDGEMENT ng This thesis would have not been fulfilled without special assistances from some hi ep individuals, group, family who have contributed to my studying process Foremost, I would like to express my sincere gratitude to my supervisor Dr w n Tran Tien Khai who continuously support of my M.A thesis by his patience, enthusiasm lo y th thesis ad and immense knowledge His guidance helped me all the time to research and writing the ju Secondly, I would like to thank Dr Truong Dang Thuy because of his dedicated yi pl support in research method during the time of this thesis All of his help strongly to find ua al the solution and improves this paper n Besides, my sincere thanks also go to Dr Nguyen Trong Hoai, Dr Pham Khanh Nam va who supervised and motivated the Class MDE 17 to finish the course on time n ll fu It is grateful to thank my classmates of MDE17 MDE18, VNP staffs for oi m stimulating discussions, for the fun time we had together at nh Last and not the least, I would like to express my grateful thank to my family who are always beside me, give me the birth and support me throughout my life z z April, 2014 jm ht vb VO THI THU HOAI Email: hoai.vtt@vnp.edu.vn k om l.c gm an Lu n va ey t re th iv t to ng hi ep ABSTRACT Accompany with development trend in over the world, migration flow plays important w n role in Vietnamese economy It contributes to the significant income and raises the living lo ad standard for household in the country, specially, in rural areas This paper tries to y th measure the impact of migration on children’s schooling enrollment and child work, ju addition to, determine how migrant’s gender matter in this impact The context is applied yi pl in rural areas in Vietnam with the dataset of VHLSS 2010 by Instrument variable method ua al to deal with the problem of endogeneity of migration From the first stage of migrant n indicator, it indicates that instrument historical migration network and number of male va n adults will impact on migrant indicator significantly and these instruments are the strong fu ll instruments The results show that the presence of migrant in the household will make the m oi children take part in school more, at the same time make children work less Besides, not at nh like others researches, gender of migrant and time of migrant using in household don’t have meaning with children’s welfare z z Keywords: migration, migrant’s gender, children’s school enrollment, child work k jm ht vb om l.c gm an Lu n va ey t re th v t to TABLE OF CONTENT ng hi ep ABSTRACT v CHAPTER 1: INTRODUCTION w 1.1 n Research Objectives lo 1.2 Problem statement ad Research question 1.4 Research scope 1.5 Structure of the research ju y th 1.3 yi pl CHAPTER 2: LITERATURE REVIEW al Definition of key concept 2.2 Theoretical literature 2.3 Empirical literature 12 2.4 Conceptual framework 16 n ua 2.1 n va ll fu oi m CHAPTER 3: METHODOLOGY 18 Endogeneity problem 18 3.2 Endogeneity of migration 18 3.3 Estimated equation 20 at nh 3.1 z z vb Validity of Instrument variable: 20 3.3.2 IVs methods 20 3.3.3 Estimated equation: 24 3.3.4 Method to run IVs regression 26 k jm l.c gm 3.4 ht 3.3.1 Data 28 om Source of data 28 3.4.2 Variables description and measurement: 29 an Lu 3.4.1 CHAPTER 4: OVERVIEW OF MIGRATION IN CASE OF VIETNAM 36 Socio-economic setting and migration in Vietnam 36 Internal migration 37 4.2 Characteristics of migrant 39 vi th 4.1.2 ey Migration aboard 36 t re 4.1.1 n va 4.1 t to ng 4.2.1 International migrant 39 4.2.2 Internal migrant 44 hi ep CHAPTER 5: EMPERICAL ANALYSIS 46 Descriptions of variables 46 5.2 Estimation results 51 5.1 w n Interpretation of results 57 lo 5.3 ad CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS 63 y th 6.1 Conclusions 63 ju yi 6.2 Recommendations: 64 pl 6.3 Limitations 65 al ua REFERENCE 67 n APPENDIX 70 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 vii t to LIST OF FIGURES ng hi ep Figure 2.1: Conceptual framework about impact of migration and migrant’s gender on children’s welfare 1717 Figure 3.1: Histogram of expenditure per capita a year 31 w n Figure 3.2: Histogram of natural logarithm of expenditure per capita a year 31 lo ad Figure 4.1: International migration trend from 2000 to 2010 (Department of oversea database) 40 y th Figure 4.2: Number of male and female international migrant from 2006-2010 (IOM) 41 ju yi Figure 4.3: Main destinations of international migrant from 2000-2010 (IOM) 42 pl n ua al Figure 4.4: Structure of international migration labor of Viet Nam from 2006-2010 (IOM, 2011) 43 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 viii t to ng hi LIST OF TABLES ep Table 3.1: Description and measurement of variables 32 w Table 5.1: T-test between household with non-migrant and household with migrant 48 n lo Table 5.2: T-test between household with male migrant and household with female migrant 50 ad ju y th Table 5.3: Factors affecting migration indicator in the household (results of first stage regression of Instrumental variables) 53 yi Table 5.4: Factors affecting children’s school enrollment and child work (results of second stage regression of Instrumental variables) 56 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 ix t to ABBREVIATIONS ng hi Best linear unbiased estimates DID: Difference in difference ep BLUE: w General statistic office n GSO: lo ad International Organization for Migration ju y th IOM: Instrumental variables OLS: Ordinary least square PSM: Propensity score matching methods yi IVs: pl n ua al n va ll fu VHLSS: Vietnam Household Living Standard Survey m United Nations UNDP: United Nations Development Programme US: United Stages oi UN: at nh z z k jm ht vb om l.c gm an Lu n va ey t re th x t to ng REFERENCE hi ep Acosta, P (2011) “Female Migration and Child Occupation in Rural El w Salvador”.Forthcoming in Population Research and Policy Review n lo ad Acosta, P (2006) “Labor Supply, School Attendance, and Remittances from y th International Migration: The Case of El Salvador”.World Bank Policy Research ju Working Paper 3903 yi pl Böcker A 1994 Chain Migration over Legally Closed Borders: Settled Migrants as al n ua Bridgeheads and Gatekeepers Netherlands' Journal of Social Sciences 30:87-106 va n Cox Edwards, A and M Ureta 2003 International Migration, Remittances and ll fu Schooling: Evidence from El Salvador Journal of Development Economics 72 (3): oi m 429–61 nh at Cuong,(2008).“ Do Foreign Remittances Matter to Poverty and Inequality? Evidence z from Vietnam.”Economics Bulletin, vol 15, No 1, p 1-11 z vb jm ht Dang, N.A (2001) “Rural labor out-migration in Vietnam: a multi-level analysis”, in migration in Viet Nam- Theoretical Approaches and Evidence from a Survey( k l.c gm Transport Communication Publishing House) Gujarati, D.N (2003) Basic Econometrics, 4thed, United States: Gary Burke om Mexico.” Mimeograph, University of California at San Diego n va IOM (2010) World Migration Report 2010, http://www.publications.iom.int an Lu Hanson, G H and C Woodruff 2003 “ Emigration and educational attainment in th 67 ey Impact Evaluation”, The World bank, Washington, D.C t re Khandker, S.R., Gayatri B.Koolwal and HussainA.Samad (2010), “Handbook on t to ng Lee, E (1966) “A theory of migration” Demography Journal of Political hi Economy,Vol 93, No 5, pp 901 - 918 ep Lewis, W A (1954) Economic development with unlimited supplies of labour.The w n manchester school, 22(2), 139-191 lo ad McKenzie, D., &Rapoport, H (2007) Network effects and the dynamics of migration y th and inequality: theory and evidence from Mexico Journal of development ju yi Economics, 84(1), 1-24 pl ua al Mansuri, G (2006) Migration, School Attainment and Child Labor: Evidence from n rural Pakistan Washington DC: World Bank va n Merrell J Tuck-Primdahl, and Indira Chand (2013) “Migration and Remittances” fu ll Retrieved May, 18th, 2013 from http://web.worldbank.org oi m nh Nguyen,T and Purnamasari, R (2011) “Impacts of international migration and re- at mittances on child outcomes and labor supply Indonesia.”Policy Research Working” z z Paper 5591, World Bank, Washington, D.C ht vb k jm Nguyen V.P (2011), “International remittances and household welfare in VietNam om l.c Netherlands Project for M.A in Development Economics gm from VHLSS 2006 and VHLSS 2008”, Unpublished M.A Thesis, Vietnam- Pfeiffer, L and J.E Taylor (2008).“Gender and the Impacts of International an Lu Migration: Evidence from Rural Mexico” in A Morrison, M Schiff, and M Sjoblom n va (eds) The International Migration of Women The World Bank, Washington, DC th 68 ey Systems.”London, New York: Routledge ISBN 978-0-415-48324-7 t re Rodrigue, J.-P., Comtois, C., Slack, B (2009) “The Geography of Transport t to ng Todaro, Michael P 1969 "A model of labor migration and urban unemployment in hi less- developed countries." The American Economic Review 59: 138-48 ep Todaro and Smith (2003)“ Economic development” 8th edition, 2003, Pearson w n Addsion Wesley lo ad UNDP, (2009) “Human Development Report 2009” Overcoming Barriers: Human y th Mobility and Development ju yi pl UN, (2010), “Internal migration: Opportunities and Challenges for socio-economic n ua al development in Vietnam” va UN, (2003) Millennium Development Goals: Closing the Millennium Gaps, The n United Nations inViet Nam, Ha Noi ll fu oi m WD Pfau and TL Giang (2006) “The growing role of international remittances in the nh Vietnamese economy: evidence from the Vietnam (Household) living standard at surveys” paper presented at the Conference on Global Movements in the Asia Pacific, z z Ritsumeikan Asia-Pacific University (APU), Oita, Japan, Nov 17-18, 2006 ht vb k jm IOM report, Retrieved June, 13th, 2013 from www.iom.int.vn Cameron, Instrumental variable” Retrieved 7th, 2013 from om http://cameron.econ.ucdavis.edu/e240a/ch04iv.pdf Oct, l.c gm World Bank, 2012, Brief on Global Migration and Remittances an Lu n va ey t re th 69 t to ng APPENDIX hi First stage: ep Source SS df MS w Number of obs F( 19, 3589) Prob > F R-squared Adj R-squared Root MSE n lo Model Residual ad y th Total 17.0210733 281.986962 19 3589 895845965 078569786 299.008035 3608 082873624 = = = = = = 3609 11.40 0.0000 0.0569 0.0519 2803 ju Coef Std Err pl al n n ll fu oi m at nh jm ht vb -.004203 0019505 -.0627564 -.0238989 -.0424796 2481605 -.0427951 0020147 -.108377 -.0022142 -.0213764 -.0000537 -.0530407 -.0802312 -.0232199 -.0721141 -.0139262 -.0025325 -.1697391 -.3551106 k 0014815 003921 -.0120194 0002662 -.0086988 404189 -.0119741 0401193 0022271 0056813 1003946 0000214 0704344 0796433 0166199 0686558 0541796 0478147 0319345 1120295 om l.c gm 0.348 0.000 0.004 0.055 0.003 0.000 0.000 0.030 0.060 0.389 0.203 0.400 0.782 0.994 0.745 0.962 0.247 0.078 0.180 0.308 [95% Conf Interval] z -0.94 5.84 -2.89 -1.92 -2.97 8.20 -3.48 2.17 -1.88 0.86 1.27 -0.84 0.28 -0.01 -0.32 -0.05 1.16 1.76 -1.34 -1.02 P>|t| z 0014497 0005025 012939 0061626 0086148 0397905 00786 0097175 0282063 0020135 0310541 0000192 0314887 0407713 01016 0358992 0173684 0128396 0514309 1191304 t va -.0013607 0029358 -.0373879 -.0118164 -.0255892 3261748 -.0273846 021067 -.0530749 0017336 0395091 -.0000161 0086968 -.0002939 -.0033 -.0017292 0201267 0226411 -.0689023 -.1215405 ua HH_school hh_age hh_gender h_csize h_child Migra_net No_male_ad ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons yi H_migrant an Lu Check the presence of endogeneity with indicator of migrant (Durbin Wu Hausman test) n va ey t re th 70 t to Source SS df MS ng Number of obs F( 21, 3587) Prob > F R-squared Adj R-squared Root MSE hi ep 45.930266 422.186564 21 3587 2.18715552 11769907 Total 468.11683 3608 129744132 Model Residual w = = = = = = 3609 18.58 0.0000 0.0981 0.0928 34307 n lo enroll ad Coef yi pl n ua al n ll fu oi m at nh 9525252 0180512 -.0043131 0827305 0510632 10286 0645079 0117468 -.4285404 0719557 2062645 -.0016974 3227044 -7.57e-06 1054682 1059238 0352139 0066722 0611475 0148439 350766 2768052 jm ht vb 4167667 0110812 -.006987 0192715 0205807 0587824 -.0847083 -.0220371 -.9612025 0240026 078231 -.0113944 1693179 -.0001 -.0457333 -.0896933 -.0132632 -.1655129 -.0227182 -.0476048 1002262 -.3012491 k om l.c gm 0.000 0.000 0.000 0.002 0.000 0.000 0.791 0.550 0.000 0.000 0.000 0.008 0.000 0.023 0.439 0.871 0.375 0.071 0.369 0.304 0.000 0.934 [95% Conf Interval] z 5.01 8.19 -8.29 3.15 4.61 7.19 -0.27 -0.60 -5.12 3.92 4.36 -2.65 6.29 -2.28 0.77 0.16 0.89 -1.81 0.90 -1.03 3.53 -0.08 P>|t| z 1366295 0017775 0006819 0161834 0077737 0112407 0380532 0086156 1358398 012229 0326512 0024729 0391167 0000236 0385595 0498864 0123627 0439108 0213875 0159257 0638928 1474158 t va 684646 0145662 -.00565 051001 0358219 0808212 -.0101002 -.0051451 -.6948715 0479791 1422478 -.0065459 2460112 -.0000538 0298674 0081153 0109753 -.0794204 0192147 -.0163804 2254961 -.0122219 ju y th H_migrant HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 u ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons Std Err an Lu n va ey t re th 71 t to Source SS df MS ng Number of obs F( 21, 3587) Prob > F R-squared Adj R-squared Root MSE hi ep 50.1827763 361.116415 21 3587 2.38965601 100673659 Total 411.299191 3608 11399645 Model Residual w = = = = = = 3609 23.74 0.0000 0.1220 0.1169 31729 n lo Coef ad c_labor yi pl n ua al n ll fu oi m at nh -.0663031 -.0062501 0063474 0238347 -.0550138 -.0600715 0478773 0181834 6208666 -.0450391 -.0362559 010917 -.3318168 00002 1342195 0771615 0112752 0529653 0370635 028227 -.0141498 1.38111 jm ht vb -.5617994 -.0126963 0038744 -.0348554 -.0832055 -.1008366 -.0901254 -.0130617 128234 -.0893886 -.1546677 0019487 -.4736763 -.0000654 -.0056192 -.103755 -.0335589 -.1062802 -.0404997 -.0295287 -.2458616 8464965 k l.c gm 0.013 0.000 0.000 0.713 0.000 0.000 0.548 0.748 0.003 0.000 0.002 0.005 0.000 0.298 0.071 0.773 0.330 0.512 0.931 0.965 0.028 0.000 [95% Conf Interval] z -2.49 -5.76 8.10 -0.37 -9.61 -7.74 -0.60 0.32 2.98 -5.94 -3.16 2.81 -11.13 -1.04 1.80 -0.29 -0.97 -0.66 -0.09 -0.04 -2.20 8.17 P>|t| z 1263618 0016439 0006307 0149672 0071895 0103959 0351935 0079681 1256315 01131 0301974 0022871 0361771 0000218 0356618 0461374 0114336 0406109 0197802 0147289 0590913 1363375 t va -.3140513 -.0094732 0051109 -.0055104 -.0691097 -.0804541 -.0211241 0025609 3745503 -.0672138 -.0954618 0064329 -.4027465 -.0000227 0643001 -.0132967 -.0111418 -.0266574 -.0017181 -.0006509 -.1300057 1.113803 ju y th H_migrant HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 u ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons Std Err om The coefficient of predicted residual u from the first stage is significant, it proves that H_migrant variable has endogeneity Test the weak instrument in endogeneity (F-test) Ho: Migra_net = No_adult=0 F( 2, 3589) = 41.56 Prob> F = 0.0000  (Prob>F) F R-squared Adj R-squared Root MSE w Model Residual n lo Total 45.8661925 422.250637 20 3588 2.29330962 117684124 468.11683 3608 129744132 = = = = = = 3609 19.49 0.0000 0.0980 0.0930 34305 ad y th enroll Std Err ju pl n ua al n ll fu oi m at nh jm ht vb 4300342 011055 -.0070047 0192444 0206381 0590034 -.4359151 -.1343681 0238045 0778707 -.0113889 1690457 -.0000997 -.0453697 -.0898549 -.0134636 -.1659132 -.0227501 -.047597 0997994 -.2985775 k 9647768 0180263 -.0043312 0826143 0511056 1030731 3485396 0419039 0717489 2058869 -.0016982 3224191 -7.34e-06 1058041 1057491 0349815 0062677 0611078 0148462 3503739 2794684 om l.c gm 0.000 0.000 0.000 0.002 0.000 0.000 0.827 0.304 0.000 0.000 0.008 0.000 0.023 0.433 0.873 0.384 0.069 0.370 0.304 0.000 0.948 [95% Conf Interval] z 5.11 8.18 -8.31 3.15 4.62 7.21 -0.22 -1.03 3.91 4.35 -2.65 6.28 -2.27 0.78 0.16 0.87 -1.82 0.90 -1.03 3.52 -0.06 P>|t| z 1363704 0017778 0006818 0161607 0077698 0112387 2000522 044953 0122268 0326468 0024713 0391134 0000236 0385524 0498831 0123545 0439097 0213855 0159243 0639017 1474137 t va 6974055 0145407 -.0056679 0509293 0358719 0810383 -.0436878 -.0462321 0477767 1418788 -.0065435 2457324 -.0000535 0302172 0079471 0107589 -.0798227 0191789 -.0163754 2250867 -.0095546 yi H_migranthat HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons Coef n ey t re th 73 va Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of enroll chi2(1) = 299.45 Prob> chi2 = 0.0000 an Lu Test heteoroskedasticity: t to ng hi ep  (Prob>chi2) F R-squared Root MSE lo ad ju y th Robust Std Err yi Coef al n n va fu t oi m at nh z ht vb 0.000 0.000 0.000 0.002 0.000 0.000 0.843 0.400 0.000 0.000 0.014 0.000 0.059 0.480 0.870 0.382 0.047 0.393 0.314 0.003 0.950 k jm 3609 19.72 0.0000 0.0980 34305 [95% Conf Interval] 4262109 0109009 -.0070937 0184156 0212377 0588553 -.4771682 -.1538566 0240817 077496 -.0117665 1748667 -.000109 -.0537337 -.0875927 -.0133593 -.1586861 -.0247961 -.0482427 0792042 -.3083962 om l.c gm 5.04 7.83 -7.79 3.07 4.81 7.16 -0.20 -0.84 3.95 4.32 -2.46 6.80 -1.89 0.71 0.16 0.87 -1.98 0.86 -1.01 3.03 -0.06 P>|t| z 1383205 0018564 0007272 0165834 007464 0113142 2210929 0548929 0120854 0328379 0026639 0361444 0000283 0428184 0487293 0123013 0402236 0224291 0162537 0744061 1524216 ll 6974055 0145407 -.0056679 0509293 0358719 0810383 -.0436878 -.0462321 0477767 1418788 -.0065435 2457324 -.0000535 0302172 0079471 0107589 -.0798227 0191789 -.0163754 2250867 -.0095546 ua H_migranthat HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons pl enroll = = = = = 9686001 0181804 -.0042422 0834431 050506 1032213 3897926 0613923 0714717 2062617 -.0013206 3165981 2.00e-06 114168 103487 0348772 -.0009594 0631539 015492 3709692 289287 an Lu n va 74 th Ho: Big_road = Electro = Market = Ele_school = Jun_school = high_school = h_migrant1 = h_migrant2 = ey t re Wald Test: t to ng F( 8, 3588) = 0.89 Prob> F = 0.5274  (Prob>F) >α, accept Ho, chosen restricted model hi ep w Restricted model of children school enrollment n lo Linear regression ad Number of obs F( 12, 3596) Prob > F R-squared Root MSE ju y th = = = = = 3609 32.06 0.0000 0.0962 34302 yi pl ua al Coef H_migranthat HH_school hh_age hh_gender h_csize h_child ln_exp_pc pro_females hh_work Com_agri Enterprise Health_cen~r _cons 6566228 0145136 -.0055998 050138 036233 0801911 0477566 1408543 -.0063986 2506184 -.0000545 2284622 -.0347447 Robust Std Err t P>|t| [95% Conf Interval] n enroll va n ll fu oi m at nh 0.000 0.000 0.000 0.002 0.000 0.000 0.000 0.000 0.016 0.000 0.053 0.002 0.802 z 4021242 0108974 -.0070167 017725 0216155 0581068 0241588 0767019 -.0116008 1804815 -.0001095 0808333 -.3070307 9111213 0181298 -.0041829 0825509 0508504 1022754 0713545 2050067 -.0011965 3207553 6.14e-07 3760911 2375413 k jm ht vb 5.06 7.87 -7.75 3.03 4.86 7.12 3.97 4.30 -2.41 7.01 -1.94 3.03 -0.25 z 1298049 0018444 0007227 016532 0074555 0112639 0120359 0327204 0026533 0357727 0000281 0752969 1388772 l.c gm Model of child work om an Lu n va ey t re th 75 t to Source SS df MS ng Number of obs F( 20, 3588) Prob > F R-squared Adj R-squared Root MSE hi ep 49.6334868 361.665704 20 3588 2.48167434 100798691 Total 411.299191 3608 11399645 Model Residual w = = = = = = 3609 24.62 0.0000 0.1207 0.1158 31749 n lo c_labor ad Coef yi pl n ua al n ll fu oi m at nh -.1103828 -.0061889 0063553 0229357 -.0548224 -.0600807 4625503 1385085 -.0444938 -.0349554 0109803 -.3311655 0000194 1346219 0778961 0111206 0541317 0370325 028142 -.0159315 1.376002 jm ht vb -.6052781 -.0126408 003881 -.0357122 -.0830195 -.1008664 -.2634493 -.0246283 -.0888655 -.1534323 0020117 -.47311 -.0000661 -.0052869 -.1031321 -.0337144 -.1052188 -.0405766 -.0296482 -.247834 8410303 k 0.005 0.000 0.000 0.669 0.000 0.000 0.591 0.171 0.000 0.002 0.005 0.000 0.285 0.070 0.785 0.323 0.530 0.929 0.959 0.026 0.000 [95% Conf Interval] z -2.84 -5.72 8.11 -0.43 -9.58 -7.74 0.54 1.37 -5.89 -3.12 2.84 -11.11 -1.07 1.81 -0.27 -0.99 -0.63 -0.09 -0.05 -2.23 8.13 P>|t| z 1262085 0016454 000631 0149564 0071909 0104012 1851449 0416033 0113157 030214 0022872 0361988 0000218 0356796 0461659 0114339 0406377 0197919 0147377 0591399 1364288 t va -.3578305 -.0094148 0051182 -.0063883 -.068921 -.0804735 0995505 0569401 -.0666796 -.0941939 006496 -.4021378 -.0000233 0646675 -.012618 -.0112969 -.0255435 -.001772 -.0007531 -.1318827 1.108516 ju y th H_migranthat HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons Std Err l.c gm om Test heteroskedasticity: an Lu Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of c_labor chi2(1) = 558.00 Prob> chi2 = 0.0000  (Prob>chi2) F R-squared Root MSE w n = = = = = 3609 25.24 0.0000 0.1207 31749 lo ad y th c_labor ju yi n ua al n va fu t oi m at nh z ht vb 0.006 0.000 0.000 0.676 0.000 0.000 0.665 0.305 0.000 0.002 0.007 0.000 0.283 0.054 0.757 0.325 0.482 0.929 0.960 0.057 0.000 [95% Conf Interval] -.614195 -.012617 0038365 -.0363139 -.0819916 -.1011085 -.3517202 -.0518123 -.0878502 -.1548179 0017662 -.4703847 -.0000658 -.0011028 -.0924904 -.0337811 -.0967536 -.0405954 -.0303579 -.2674612 8413827 -.101466 -.0062127 0063998 0235374 -.0558504 -.0598386 5508212 1656925 -.045509 -.0335698 0112258 -.3338908 0000192 1304379 0672544 0111873 0456665 0370514 0288517 0036957 1.37565 om l.c gm Electro= an Lu Market= n va Wald test: Ho: hh_gender=h_migrant1=h_migrant2=Enterprise= Ele_school= Jun_school= high_school=0 k jm -2.74 -5.76 7.83 -0.42 -10.34 -7.65 0.43 1.03 -6.18 -3.05 2.69 -11.55 -1.07 1.93 -0.31 -0.99 -0.70 -0.09 -0.05 -1.91 8.14 P>|t| z 1307565 0016332 0006537 0152633 0066665 0105247 2301667 0554682 0107979 0309208 0024124 0348088 0000217 0335456 0407382 0114679 03632 0198015 0150997 0691506 1362491 ll -.3578305 -.0094148 0051182 -.0063883 -.068921 -.0804735 0995505 0569401 -.0666796 -.0941939 006496 -.4021378 -.0000233 0646675 -.012618 -.0112969 -.0255435 -.001772 -.0007531 -.1318827 1.108516 pl H_migranthat HH_school hh_age hh_gender h_csize h_child h_migrant1 h_migrant2 ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r _cons Robust Std Err Coef t re ey F( 9, 3588) = 0.68 Prob> F = 0.7303  Accept Ho, chosen restricted model th 77 t to ng Restricted model of child work hi ep Linear regression Number of obs F( 11, 3597) Prob > F R-squared Root MSE w n = = = = = 3609 45.09 0.0000 0.1190 31739 lo ad y th c_labor Robust Std Err Coef t P>|t| [95% Conf Interval] ju yi n ua al 1176566 0016249 000642 0066309 0104337 0106842 030559 0023881 034157 0333571 069041 1285849 n va ll fu -2.76 -5.91 7.88 -10.40 -7.73 -6.52 -3.03 2.62 -11.79 1.89 -1.74 8.38 0.006 0.000 0.000 0.000 0.000 0.000 0.002 0.009 0.000 0.059 0.081 0.000 oi m -.5559466 -.0127834 0037983 -.0819729 -.1011276 -.0905788 -.1524646 0015781 -.4697065 -.0024015 -.2557373 8248416 -.0945859 -.0064117 0063158 -.0559715 -.0602145 -.0486835 -.032635 0109424 -.3357684 1284 0149896 1.329055 at nh -.3252663 -.0095975 005057 -.0689722 -.080671 -.0696312 -.0925498 0062602 -.4027374 0629992 -.1203738 1.076948 pl H_migranthat HH_school hh_age h_csize h_child ln_exp_pc pro_females hh_work Com_agri Big_road Health_cen~r _cons z z Check multicollinearity k jm ht vb om l.c gm an Lu n va ey t re th 78 t to H_migr~t female~t t_migr~t HH_sch~l ng hi ep w n lo ad ju y th yi n ua al 1.0000 0.4849 -0.0004 0.1043 -0.0181 -0.0520 -0.0713 0.0304 -0.0217 0.1173 -0.0038 0.0456 -0.0190 -0.0429 0.0508 -0.0013 -0.0087 0.0163 0.0459 0.0156 0.0194 0.0190 0.0069 n va ll fu 1.0000 -0.0010 0.0911 -0.0408 -0.0598 -0.0491 0.0421 -0.0286 0.1049 -0.0376 0.0301 -0.0148 -0.0605 0.0293 0.0251 0.0044 0.0157 0.0478 0.0214 0.0293 0.0317 -0.0131 m 1.0000 -0.1136 0.0183 -0.1359 -0.1251 -0.1413 0.1802 0.0732 -0.0163 0.4054 -0.0235 0.1491 0.0756 0.0264 0.0477 0.0655 0.0757 0.0779 0.0683 0.0793 0.0236 oi 1.0000 0.7170 0.6775 0.0130 0.1265 -0.0842 -0.0685 -0.0874 0.0467 -0.0199 0.1639 -0.0533 0.0776 -0.0004 -0.0452 0.0695 0.0051 0.0100 0.0302 0.0464 0.0338 0.0324 0.0338 -0.0227 pl H_migrant female_it t_migrant HH_school hh_age hh_gender h_csize h_child c_labor enroll Migra_net No_male_ad ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r hh_age hh_gen~r 1.0000 -0.1569 -0.0780 -0.1563 0.1564 -0.1394 0.1014 0.2706 0.0576 0.0206 -0.4328 -0.0217 0.0468 -0.0110 0.0522 0.0819 0.0309 0.0134 0.0073 -0.0120 1.0000 0.1128 0.0673 -0.0078 0.0328 0.0431 0.2637 -0.0782 -0.2001 0.1457 -0.0448 -0.0643 -0.0375 -0.0414 -0.0386 -0.0292 0.0065 -0.0296 0.0230 h_csize 1.0000 -0.1075 -0.0786 0.0007 -0.0790 0.0177 -0.2659 0.0164 0.0672 -0.0993 -0.0226 0.0008 -0.0834 -0.0700 -0.0745 -0.0272 -0.0344 0.0025 at nh z z k jm ht vb om l.c gm an Lu n va ey t re th 79 t to c_labor 1.0000 -0.0804 0.0679 -0.0502 -0.0071 -0.2577 0.0612 0.0265 -0.0104 -0.0105 -0.0079 -0.0498 -0.0494 -0.0367 -0.0355 0.0066 -0.0410 1.0000 -0.6217 -0.0338 0.1665 -0.1005 -0.0525 -0.0396 -0.2136 -0.0114 0.0144 -0.0123 -0.0254 -0.0249 -0.0163 -0.0113 -0.0358 enroll Migra_~t No_mal~d ln_exp~c pro_fe~s ng h_child hi ep w n lo ad 1.0000 -0.0135 -0.3435 -0.0575 -0.2264 -0.0112 -0.0308 -0.0139 0.0173 -0.0064 0.0015 0.0173 -0.0068 hh_work Com_agri Enterp~e Big_road Electro ju y th 1.0000 0.0392 -0.2206 0.1072 0.0587 0.0411 0.1589 -0.0493 0.0303 0.0211 0.0259 -0.0044 0.0226 0.0055 0.0596 1.0000 -0.0391 0.0714 0.0043 -0.0398 0.1637 -0.0011 0.0043 0.0814 0.1750 0.0880 0.0367 0.0010 -0.0234 yi pl al n ua n va ll fu h_child c_labor enroll Migra_net No_male_ad ln_exp_pc pro_females hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r 1.0000 -0.0380 0.0468 0.0741 0.1204 0.0301 0.1031 0.1178 0.1037 0.0329 0.0555 0.0087 1.0000 -0.0357 0.0132 -0.0080 0.0043 0.0257 -0.0236 0.0176 0.0065 0.0062 -0.0191 oi m Market Ele_sc~l 1.0000 0.4248 0.0555 -0.0138 om l.c gm an Lu 1.0000 -0.0479 k 1.0000 0.1011 0.0088 1.0000 0.1235 0.1465 0.1341 -0.0524 jm Jun_school high_school Health_cen~r ht Jun_sc~l high_s~l Health~r 1.0000 0.0913 -0.0179 0.0136 0.0473 0.0392 vb 1.0000 0.0901 0.0706 -0.0228 0.0285 0.0480 0.0458 z 1.0000 -0.0132 0.0316 0.0835 0.0371 0.0284 0.0458 -0.1366 z 1.0000 -0.0342 0.0066 0.0527 0.0499 0.0196 0.0081 -0.0319 0.0542 at 1.0000 -0.0274 -0.0001 0.0345 -0.0063 -0.0149 0.0083 0.0390 0.0264 -0.0176 nh hh_work Com_agri Enterprise Big_road Electro Market Ele_school Jun_school high_school Health_cen~r 1.0000 n va ey t re There is no big correlation between the variables in the data, so we exclude the impact of multicollinearity in the model th 80 t to ng hi ep w n lo ad 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 81