Migrants and non migrants wage differentials in southeast provinces of vietnam

UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE TRE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS MIGRANTS AND NON-MIGRANTS WAGE DIFFERENTIALS IN SOUTHEAST PROVINCES OF VIETNAM A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAN THI HONG NHUNG Academic Supervisor: NGUYEN HUU DUNG HO CHI MINH CITY, June 2010 CERTIFICATION I hereby certify that the substance of this thesis has not been submitted for any degrees and is not being currently submitted for any other degrees I also certify that, to the best of my knowledge, and any help received in preparing the thesis and all sources used have been acknowledged in the thesis Phan Thi Hong Nhung Date: June, 2010 ACKNOWLEDGEMENT This research is impossible completed without the valuable guidance, encouragement and advice from numerous individuals including Vietnam-Netherlands program lecturers, friends and my family members I would like to express my special thanks to all people to what they have done for my thesis completion First of all, I would like to send my deepest gratitude to my supervisor, Dr Nguyen Huu Dung who always gives valuable instructions, advice and comments during my completion of the thesis I also send my special thanks to Associate Professor Nguyen Trong Hoai for his lectures in econometrics, Mr Truong Thanh Vu, the lecturers of Vietnam-Netherlands project, for their kind help and instructions in data analysis by Stata software and Mr Le Cong Tann — MDE 12, Phan Thi Lien — MDE 14 for their support in the process of data mining Many especially respectful thanks are sent to my family for encouraging and providing me with an opportunity to pursue my desires in higher learning And finally, I would like to express my special thanks to my friends in MDE class 14 for their supportive friendship from the beginning day I joined the VNP program, and their continuous support during my research completion Above all, please sympathize for me and know that I would be so grateful for those who support me a lot in this thesis completion if I forget to mention their names This study examines the wage differentials between migrant workers and non-migrant workers Based on data from Vietnam Migration Survey in 2004, earnings equations with and without Instrumental Variable (IV) are estimated for migrant workers and nonmigrant workers From these results, the study compares the wage structure for migrant workers and non-migrant workers Oaxaca decomposition of the wage differentials of the two groups workers are carried out Results, which are controlled for observed characteristics and selection bias, indicate some main points The wage differentials between non-migrant and migrant workers are mostly due to the difference in structural factors Besides, there are differences in endowment factors CONTENTS pJjj"jg;j iCin Acknowledgements ›i Abstract 111 Content table lY List of Tables vi:i List of Figures x List of Abbreviations xi CHAPTER 1: INTRODUCTION 1.1 Problem statement 1.2 Research objectives 1.3 Research questions .3 1.4 Thesis structure CHAPTER 2: LITERATURE REVIEW Definition of migration 2.2 Reviews of theoretical framework .6 2.2 Related to migration 2.2 1.1 Human capital theory 2.2 1.2 Harris — Torado model for migration 2.2.2 Related to wage determination and wage differentials .9 2.3 Previous empirical studies 12 2.4 Chapter remarks 18 CHAPTER 3: RESEARCH METHODOLOGY 3.1 Empirical model 19 1.I Earnings function .19 3.1.2 3.2 Earnings differentials measurement 21 Definition of variables used in study 22 3.2.1 Dependent variable 22 3.2.2 Independent variables 23 3.3 Datasource 27 3.3.1 Introduction of the data set 27 3.3.2 The reliability of the data set .28 3.3.3 Detail of data .28 3.4 Estimation strategy .30 3.5 Chapter remarks 31 CHAPTER 4: OVERVIEW OF MIGRATION IN HO CHI MINH CITY, BINH DUONG AND DONG NAI PROVINCE A profile of migrants and non-migrants in HoChiMinh City, Dong Nat and BinhDuong 32 4.1 Age structure .32 I Gender .33 4.1.3 Education level 34 I , ¶ , Earnings , 4.1.6 Duration of residence 38 4.1.7 Type of occupation .39 4.2 Earnings of workers 40 4.2.1 Monthly average income classified by gender and regions 40 4.2.2 Monthly average income classified by types of occupation and regions 41 4.2.3 Monthly average income classified by sectors and regions .42 4.2.4 Monthly average income classified by education levels and regions .43 4.2.5 Monthly average income classified by characteristics of migrant and non-migrant workers 44 4.3 Chapter remarks 46 CHAPTER 5: DETERMINANTS OF EARNINGS AND WAGE DIFFERENTIALS OF MIGRANTS AND NON-MIGRANTS Determinant of earnings .47 1.1 Estimation results of model with OLS and 2SLS 47 1.2 The effect of year since migration on migrant’s earnings (model 2) .50 l Determinants of earnings for migrants and non-migrants (model I) .52 5.2 Wage differentials with Oaxaca’s method 55 5.3 Charter remarks 57 CHAPTER 6: CONCLUSION AND POLICY IMPLICATION Conclusion .59 6.2 Policy implications 61 6.3 Limitation of the research 63 REFERENCES APPENDICES , LIST OF TABLES Table 3.1: Definitions and notations of variables Table 4.1 : Distribution of age structure by current residence, migrant status and gender % Table 4.2: Distribution of sex ratio by age structure current residence and migrant status Table 4.3: Distribution of the obtained highest education level by current residence, migrant status and gender (%) Table 4.4: Distribution of the types of activity by current residence and migrant status (%) Table 4.5: Monthly average earnings (thousand VND) by current residence, migration status, age group and gender Table 4.6: Distribution of duration residence of migrants in current residence by household registration status Table 4.7: Distribution of types of occupation by current residence, migrant status Table 4.8: Monthly average income classified by gender and regions Table 4.9: Monthly average income classified by types of occupation and regions Table 4.10: Monthly average income classified by sectors and regions Table 11: Monthly average income classified by education levels and region Table 12: Monthly average income classified by characteristics of migrant and non- migrant worker Table 5.1: Estimation results of model with OLS and 2SLS Table 5.2: Testing for endogeneity Table 5.3: The correlation matrix between the explanatory variable and its instrument Table 5.4: The effect of year since migration on earnings for migrants (model 2) Table 5.5: Estimating results of model for migrants and non-migrants Table 5.6: Earnings differentials between migrants and non-migrants by Oaxaca’s method Tuan, V (1996), “Rural — Urban Migration of Woman Labor in the Mekong Delta, Vietnam”, MDE thesis Wooldridge, J (2001), “Introduction Econometric”, MIT Press, Cambridge Yao, Y (2001a), “Social Exclusion and Economic Discrimination: The Status of Migrations in China’s Coastal Rural Area”, Working paper E2001005, China Center for Economic Research, Peking University APPENDICES APPENDIX 1: Distribution of monthly average earnings and correlation matrix Distribution of monthly average earnings (wage) before transforming into logarithm form Distribution of monthly average earnings (wage) after transforming into logarithm form -4- Correlation matrix of the variables in model e׿S gen OCCZ -0.3 8B2 -D.0019 0.9933 0.9689 0.1193 O DOO0 000D 0.1070 O.0001 1.00D0 0.3226 -0.1464 -0.1189 -0.0]30 0.0000 0.0000 0.0000 0.2274 1.0000 0.0109 0.6902 -0.0705 0.0098 -0.0B99 0.0019 0.0593 0.0299 0.1652 -0.D342 -0.03T1 0.0529 0.2262 0.0246 0.0000 0.2111 0.1742 0.0528 0.0000 0.3682 -0.1951 0.0000 1.D000 1.0000 According to correlation matrix table, correlation between variables is very weak The purpose of this statistical description is not to express completely the result but gain the insights into the nature of relationships APPENDIX 2: Descriptive statistic analysis 2.1 Mean of wage classified by gender Group Statistics Std Error N GEN WAGE Mean 695 646 • Std Deviation 1371640 1663745 1480684.343 1616212.617 Mean 56165.559 63589.035 Inrlependent Samples Test Levene’s Test for Equality of Variances Sig WAGE Equal variances assumed Equal variances not assumed 184 668 I-test for Equality of Means t df Sig (2-tailed) Mean Difference Std Error Difference 95% Confidence Interval of the étlCé Lower Upper -3.454 1339 001 -292104.29 84571.235 -45801 -126198 -3.443 1305.494 001 -292104.29 84841.825 -458546 -125663 -5- , ANOVA WAGE Between Groups Within Groups Sum of Squares 57E+1 3.14E+1 Total 3.23E+1 df Mean Square 189E-›13 348E‹-12 1337 1340 Sig .000 F 13.583 2.2 Mean of wage classified by occupations Multiple Comparisons “ Dependent Variable: WAGE LSD (I) OCCODE (J) OCCODE 1.00 2.00 3.00 1.00 3.00 1.00 3.00 Mean Difference -J) -47416.26 491298.54(*) 47416.26 538714.80(“) -491298.54(“) 2.00 -538714.80(”) Std Error Sig 212099.220 211530.278 212099.220 85705.246 211530.278 823 020 823 000 020 85705.246 000 95% Confidence Interval Lower Bound -463499.76 76331.15 -368667.24 370583.40 -906265.92 -706846.20 Upper Bound 368667.24 906265.92 463499.76 706846.20 -76331.15 -370583.40 * The mean difference is significant at the 05 level ANOVA WAGE Sum of Squares df Mean Square Between GroupS Within Groups 9.57E+13 3.14E+15 1337 Total 3.23E-›15 1340 3.189E+13 2.348E+12 F 13.583 Sig .000 2.3 Mean of wage classified by sectors Group Statistics WAGE SEC N 1217 124 Mean 1531380 1325637 -6- Std Deviation 1604084.343 907539.408 Std Error Mean 45981.370 81499.445 Independent Sam ples Test Levene’s Test for Equality of Variances I-test for Equality of Means 95% Confidence Interval of the F WAGE Equal variances assumed Equal variances not assumed Sig 016 792 t df Sig (2-tailed Mean Difference Std Error Difference Dlff éFlCé Lower Upper 1.405 1339 160 205743.35 146413.56 -81481 492968.3 2.199 211.599 029 205743.35 93575.883 1282.968 390203 2.4 Mean of wage classified by migration status (female) Group Statistics Std Error WAGE MIGRANT N Mean Std Deviation Mean 560 1503036 1603667.442 67767.318 135 826592.59 504917.849 43456.409 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95% Confidence F ’ WAGE Equal varia nces assumed Equal variances Sig 3›.474 000 not assumed df t Mean Sig (2-tailed) Difference Std Err / Difference Interval of the Difference Lower Upper 4.841 693 000 676443.12 139728.46 402101.2 950785.0 8.403 652.782 000 676443.12 80503.844 518365.4 834520.8 2.5 Mean of wage classified by migration status (male) Group Statistics WAGE MIGRANT Mean N Std Deviation Std Error Mean 482 1772488 1656776.593 75464.106 164 1344146 1448672.294 113122.3 Independent Samples Test Levene's Test for Equality of Variances t-test for Equalit of Means 95% Confidence F WAGE Equal variances assumed Equal variances not assumed 13.775 Sig .000 t df Sig (2-tailed) Mean Difference Std Error Difference Interval of the Difference Lower Upp r 2.949 644 003 428341.21 145242.33 143135.5 713547.0 3.150 318.954 002 428341.21 135983.40 160803.5 695879.0 2.6 Mean of wage classified by migration status (private sector) -7- Group Statistics Std Error - MIGRANT WAGE Mean 1664466 1105966 N 927 290 Mean 55719.323 68646.309 Std Deviation 1696468.098 1169004.515 Independent Samples Test Levene's Test for t-test for Equality of Means Equality of Variances 95% Confidence Interval of the F WAGE Equal varia • Sig 566 nces assu med I OOO Equal variances df Mean Std Err / Sig (2-tailed) Difference Difference Difference Lower Upper 231 215 000 558500.50 106776.81 349013 767987 317 700 373 000 558500.50 88413.566 384913 732087 not assu med 2.7 Mean of wage classified by migration status (public sector) Std Error WAGE MIGRANT N 115 Mean 1331122 Std Deviation 938066.004 Mean 87475.106 1255556 343187.671 114395.9 Independent Samples Test Levene's Test for Equality of Variances t-test for Equalit of Means 95%» Confidence ’ Mean F WAGE Equal variances assumed Equal variances not assumed Sig 3.495 t 064 df Std Err / Sig (2-tailed) Difference Difference Interval of the Difference Lower 240 122 811 75566.18 315338.22 -548677 699809.7 525 19.620 606 75566.18 144008.03 -225203 376335.1 2.8 Mean of wage classified by migration status (professionals occupation) Group Statistics MIGRANT WAGE Upper N 48 Mean 1868750 1011111 -8- Std Deviation 1294038.088 613278.983 Std Error Mean 186778.3 204426.3 Independent Samples Test Levene's Test for Equality of Variances I-test for Equality of Means 95%« Confidence Interval of the Mean F WAGE Equal variances assumed Sig 715 df I 034 Equal variances not assumed fference Std Error Sig (2-tailed) Difference Difference Lower Upper -29649 1744927 1.937 55 058 857638.89 442748 57 097 24 076 005 857638.89 276904 79 286230.8 1429047 2.9 Mean of wage classified by migration status (staffs occupation) Std Error N MIGRANT WAGE Mean 1902937 1292984 495 124 Std Deviation 2036586.919 1601078.894 Mean 91537.775 143781.1 Independent Sam ples Test Levene's Test for Equality of Variances I-test for Equality of Means 95% Confidence F WAGE Equal variances assumed Sig, t 000 14.4 Equal variances not assumed df 103 617 3.579 233.369 Sig (2-tailed) Mean Difference Std Err / Difference Interval of the Difference Lower Upper 002 609953 50 196578 98 223908.5 000 609953.50 274142 945765.0 170446 99 995998.5 2.10 Mean of wage classified by migration status (elementary job) Group Statistics WAGE MIGRANT 495 Mean 1330071 Std Deviation 1069312.677 Std Error Mean 48062.031 166 979518.07 654573.474 50804.755 N Independent Samples Test , Levene's Test for Equality of Variances t-test for Equality of Means 95º/« Confidence interval of the F WAGE Lqual variances assumed Equal variances not assumed 27.392 Sig .000 I df Sig (2-tailed) Mean Difference Std Error Difference DlJéFé00B Lower Upper 3.980 659 000 350552.63 88079.866 177601.6 523503.6 5.012 467.437 000 350552.63 69936.270 213124.2 487981.0 -9- 2.11 Mean of wage classified by migration status (HCMC ) Group Statistics MIGRANT WAGE Mean 1568249 1045306 N 346 98 Std Error Mean 71601.697 46841.812 Std Deviation 1331868.548 463710.281 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95%» Confidence Interval of the F ” WAGE Equal variances assumed Equal variances not assumed Sig .000 18 12 df I 3.819 6112 Dlfference Lower Upper Sig (2-tailed) Mean Difference Std Error Difference 000 522942.43 136923,39 253840,7 792044.2 , OOO 522942.43 85562.599 354765.0 691 119.9 442 425984 2.12 Mean of wage classified by migration status (Binh Duong province) Group Statistics MIGRANT WAGE N 310 57 Mean 2026661 1330702 Std Deviation 2300735.825 2348018.815 Std Error Mean 130673 311002 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95%» Confidence F WAGE Equal varia nce assumed Sig 4.388 t 037 Equal variances not assumed Mean Sig (2-tailed) Difference df Std Err / Difference Interval of the Difference Lower Upper 2.092 365 037 695959.54 332629.34 1849.061 1350070 2.063 77.082 042 695959.54 337339.75 4241.733 1367677 2.13 Mean of wage classified by migration status (Dong Nai province) Group Statistics , MIGRANT WAGE 386 Mean 1360518 Std Deviation 1082269.257 Std Error Mean 55086.055 144 1067639 663932.959 55327 747 N Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means WAGE Equal variances assumed 1.295 Equal variances not assumed Mean Difference Std Error Difference Lower Upper 528 002 292879.25 96343.579 103615.5 482143.0 3.751 415.408 000 292879.25 78074.535 139408.8 446349 I 001 Sig (2-taiIed 3.040 Sig df 95% Confidence Interval of the DOCUMENT 2.14 Mean of wage classified by migration status (illiterate + primary) Group Statistics MIGRANT WAGE N 103 §0 Mean Std Deviation 1220582.52 1021583.570 774000.00 Std Error Mean 100659.620 524135.829 74124.000 Independent Samples Test Levene's Test for Equality of Variances F WAGE Equal variances assumed t-test for Equality of Means Sig t 001 Equal variances not assumed df Sig (2-tailed) Mean Difference Std Error Difference 95º4 Confidence Interval of the fference Lower Uj›per 2.907 151 004 446582.52 153597.63 143104.5 750060.6 3.572 150.496 000 446582.52 125006.91 199587.3 693577 2.15 Mean of wage classified by migration status (secondary education) Group Statistics Std Error WAGE MIGRANT 331 Mean 1545498 Std Deviation 1570819.505 Mean 86340.049 126 987301.59 447217.911 39841.338 N Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means 95%» Confidence Interval of the Sig WAGE Equal variances assumed Equal variances not assumed 30.854 000 I df Sig (2-tailed) Mean Difference Std Enor Difference Difference Lower Upper 3.926 455 000 558196.90 142168.43 278808.7 837585 5.870 433.597 000 558196.90 95089 096 371304.0 745089.8 2.16 Mean of wage classified by migration status (high school) Group Statistics MIGRANT WAGE 552 Mean 1738332 Std Deviation 1767956.288 Std Error Mean 75249.217 109 1429633 1757523.472 168340 N Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means Sig WAGE Equal variances 5.1 16 assumed 024 Equal variances not assumed " df t Sig (2-tailed) Mean Difference Std Error Difference 95%« Confidence Interval of the éftCé Lower Upper 1.667 659 096 308698.49 185127.23 -54811.8 672208.8 1.674 154.265 096 308698.49 184393.26 -55563.2 672960.2 2.17 Mean of wage classified by migration status (college/university/higher) Group Statistics WAGE MIGRANT N 56 14 Mean 1771429 935714.29 Std Deviation 1391756.808 614700.856 Std Error Mean 185981.3 164285.7 Independent Samples Test Levene’s Test for Equality of Variances t-test for Equality of Means 95%« Confidence F WAGE Equal variances assumed 3.937 Sig .051 Equal variances not assumed t df Sig (2-tailed) Mean Difference Std Enor Difference 2.185 68 032 835714.29 382533.62 72380.332 1599048 3.368 48.748 001 835714.29 248150.86 336971.2 1334457 2.18 Frequency table of Ysm variable ² Interval of the D éTi6é Lower Upper Ysm Freq Percent Cum Total 37 42 39 71 85 12 286 12.94 14.69 13.64 24.83 29.72 4.20 100.00 12.94 27.62 41.26 66.08 95.80 100.00 -12- APPENDIX 3: Results of regression models 3.1 Regression model I without IV (n-1,341) reg In W school exp exp2 gen cccl occ2 sec, robust Linear regression 1341 49.69 1744 Number of obs — F( 7, 1333) — Prob > F — R— squared Root MSE = 61824 la ID School Exp Exp2 Gen Occ1 Occ2 5« cows Coef .0333081 0271899 -.0002411 1994539 4051597 3105636 - 1936372 12.98916 Std Err .0056l19 005541 000138 0346891 089649 0350806 0525437 0746244 T 5.94 4.91 -1.75 5.75 4.52 8.85 -3.69 174.06 P>t 0.000 0.000 0.081 0.000 0.000 0.000 0.000 0.000 [95% Conf .0222989 01632 -.00051l8 1314027 2292912 2417444 -.2967146 12.84277 Interval] 0443173 0380599 0000296 2675052 5810281 3793829 -.0905599 13.13555 3.2 Regression model 1with IV (n-1,341) ivreg In W (school —— edufather edumother) exp exp2 gen occl occ2 sec, robust Instrumental variables (2SLS) regression • • Coef In W S«6o»/ 0490209 E« 0282227 Exp2 -.0002294 Gen 1950938 feel 3364757 Pcc2 3074005 S'ec -.2104206 12.82821 cow Instrumented: school Std Err .0083781 0055865 0001398 0346545 0882617 0353177 0515749 1004505 Number of obs F( 7, 1333) Prob > F R-squared Root MSE t 5.85 5.05 -1.64 5.63 3.81 8.70 -4.08 127.71 Pit 0.000 0.000 101 0.000 0.000 0.000 0.000 0.000 = 1341 = 47.80 = 0.0000 = 0.1697 — 62 [95% Conf Interval] 0325853 0654566 0172634 039182 -.0005037 0000448 1271106 2630771 1633288 5096227 2381l61 3766849 -.3115975 - 1092437 12.63115 13.02527 Instruments: exp exp2 gen occl occ2 sec edufather edumother 3.3 Results of regression model 1for non-migrants ivreg In W tschool —— edufather edumother) exp exp2 gen occl occ2 sec if migrant—— ——0, robust Instrumental variables (2SLS) Numberofobs — 1042 regression F( 7, 1034) = 36.44 Prob > F = 0.0000 R-squared — 0.1721 Root MSE =.64013 lnW Coef Std Err t P>t [95% Conf School 0348226 0090647 3.84 0.000 0170352 J× 022941 0065401 3.51 0.000 0101075 Exp2 -.0000908 000l6l3 -0.56 0.574 -.0004074 Gen 1537358 0406935 3.78 0.000 0738846 P« / 4459725 0987967 4.51 0.000 2521077 Ocn l 7d27 0412234 7.71 0.000 2367358 S« -.2557655 0572307 -4.47 0.000 -.368067 « » 13.04659 1110216 117.51 0.000 12.82874 Instrumented: school Instruments: exp exp2 gen occ l occ2 sec edufather edumother Interval l 05261 0357745 0002258 233587 6398373 3985181 - 143464 13.26444 3.4 Results of regression model I for migrants ivreg In W (school—— edufather edumother] exp exp2 gen cccl occ2 sec if migrant — ——1, robust Instrumental variables (2SLS) regression Number of obs F( 7, 291) Prob > F R-squared Root MSE = 299 = 17.91 — 0.0000 — 0.2862 =.46349 lnW Coef Std Err t P>t [95% Conf Intervall School 0548046 0199791 2.74 0.006 0154827 094l266 Exp 0440211 008651 5.09 0.000 0269946 06 10475 Exp2 -.0008563 0002082 -4.11 0.000 -.001266 -.0004466 Gen 3828654 0541626 7.07 0.000 2762654 4894654 Oc«/ 0939477 1755666 0.54 0.593 -.251593 439489 O«2 1896443 0543328 3.49 0.001 0827093 2965794 Sec 1542538 0948772 1.63 105 -.0324787 3409863 cows 12.58281 2l61188 58.22 0.000 12.15746 13.00817 Instrumented: school Instruments: exp exp2 gen occl occ2 sec edufather edumother - 14 - ... and non- migrant workers in Ho Chi Minh, Binh Duong and Dong Nai •l• To investigate the determinants of earnings of migrants and non -migrants • To examine factors contributing to migrant and non. .. are extracted and used to provide a better understanding of a profile of migrants and nonmigrants in HCMC and Binh Duong and Dong Nat provinces In addition, out of a subdata set of 4,005 only... difference of earnings between migrants and non — migrants in HCMC and Dong Nai and Binh Duong is sufficiently large, with average earnings of migrants is equal to 2/3 average earnings of non- migrants