INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM VIETNAM -NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE IMPACT OF EDUCATION ON UNEMPLOYMENT INCIDENCE: MICRO EVIDENCE FROM VIETNAM BY LE THI YEN THANH MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, DECEMBER 2012 UNIVERSITY OF ECONOMICS HO em MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM -NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE IMPACT OF EDUCATION ON UNEMPLOYMENT INCIDENCE: MICRO EVIDENCE FROM VIETNAM A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LE THI YEN THANH Academic Supervisor: Dr PHAM KHANH NAM HO em MINH CITY, DECEMBER 2012 CERTIFICATION "I certify that the work of this thesis has not already been submitted for any degree and has not been currently submitted for any other degree I certify that to the best of my knowledge and any help received in preparing this thesis, and all sources used, have been acknowledged in this thesis." LE TID YEN THANH ACKNOWLEDGMENTS Firstly, I would like to send my deep gratitude to my supervisor, Dr Pham Khanh Nam for his kindest help to my thesis I thought I might have given up due to the busy activity at work Thank to his motivation, patience and enthusiasm, I could continue and complete my thesis on time He spent his precious time helping me search for materials, books and studies related to my thesis My thesis could not have been completed without his support, guidance, advice and comments With all my heart, I gratefully send my sincere thanks for all he did to help me to complete this thesis Besides my supervisor, my best gratitude also goes to Dr Nguyen Van Chon who provided me with valuable advice and comments during the time I wrote the thesis I also take this chance to express my sincere thanks to Dr Nguyen Trong Hoai who tightly monitored my thesis schedule and encouraged me to complete this thesis on time In addition, I would like to thank my friends, Anh Khang, Huyen, Binh, Hong and all classmates of MDE 16 for their kind help and assistance during my thesis Finally, I would like to thank my parents, my boyfriend and my young sister for all their support and encouragement during the time I was doing my research Le Thi Yen Thanh December 2012 • ABSTRACT Unemployment is one of the major challenges which lead to the unsustainability in our economy and society To deal with high unemployment, education is considered as one of the best solutions because it reduces the unemployment probability by preparing knowledge and skills for people before they participate in the labor market This thesis aims to analyze the link between education and unemployment by examining the impact of educational attainment on unemployment probability when considering other control variables at the micro level such as gender, age, marital status, health status, regional level and family economic condition, using the secondary data from Vietnam Household Living Standards Survey 2008 (VHLSS2008) The analysis is conducted by running logit model The findings confirm that educational attainment has a significantly negative effect on unemployment risk The thesis also points out that women are more likely to enter unemployment spell than men at the same educational level In addition, age, ethnic, health status, marriage, being household head, geographic location, household expenditure and number of young children also play a statistically important role on unemployment From the results, the study gives some policy recommendation ABBREVIATIONS VHLSS Vietnam Household Living Standards Survey FDI Foreign Direct Investment GSO General Statistics Office MOLlS A Ministry of Labor - Invalids and Social Affairs OR Odds Ratio TABLE OF CONTENTS CHAPTER ONE: INTRODUCTION ! - 1.1 Problem Statement ! 1.2 Research Objectives 1.3 Research Questions 1.4 Research Scope 1.5 Structure of the Thesis CHAPTER TWO: LITERATURE REVIEW 2.1 Theoretical Background 2.2 Review of Empirical Studies 2.3 Chapter Summary 17 CHAPTER THREE: RESEARCH METHODOLOGY 18 3.1 Conceptual Framework 18 Data Source 19 3.3 Variables Description 19 3.4 Econometric Model 22 3.5 Chapter Summary 24 CHAPTER FOUR: EMPIRICAL ANALYSIS 25 4.1 Labor Force and Unemployment Situation of Vietnam 25 4.1.1 Labor Force in Vietnam 25 4.1.2 Unemployment in Vietnam 28 4.2 Descriptive Statistics 33 4.3 Regression Results 41 4.4 Interpretation and Discussion 42 4.5 Chapter Summary 5! • CHAPTER FIVE: CONCLUSION AND RECOMMENDATION 53 5.~ Conclusion 53 5.2 Policy Recommendation 54 5.3 Research Limitations and Further Research Suggestions 55 REFERENCES 56 APPENDIX 62 LIST OF TABLES Table 3.1 Summary of dependent and independent variables 20 Table 4.1: Structure of unemployed population by the highest educational attainments and by gender in 2010 and 2011 (%) 31 Table 4.2: Regression results of the logit models 41 Table 4.3 The estimation of unemployment probability, given initial probalibity Po .42 Table 4.4 Odds ratio and unemployment probability of women at different educational attainments with initial probability at 10%, 50% and 90% 44 Table 4.5 Odds ratio and unemployment probability of men at different educational attainments with initial probability at 10%, 50% and 90% .45 Table 4.6 Odds ratio and unemployment probability of men and women with initial probability at 10%, 50% and 90% at the same educational attainment 45 LIST OF FIGURES Figure 3.1 Conceptual framework of the study 18 Figure 4.1: The share of labor force by residence from 2000 to 2011 (%) 25 Figure 4.2: The share of labor force by gender from 2000 to 2011 (%) 26 Figure 4.3: Age structure of labor force by residence in 2011 (%) 26 Figure 4.4: Share of labor force by education/training levels in 2011 by residence 27 Figure 4.5: Rate of trained labor force by gender in 2011 (% ) 27 Figure 4.6: Structure of trained labor force by regions in 2011 (%) 28 Figure 4.7: Unemployment rate by age groups in 2010 and 2011 (%) 29 Figure 4.8: Age structure of unemployed population by gender in 2011 (%) 29 Figure 4.9: Age structure of unemployed population by residence in 2011 (%) 30 Figure 4.10: Unemployment rate by the educational attainment in 2010 and 2011 31 Figure 4.11: The unemployment rate by regions during the period of 2008-2011 32 Figure 4.12: Unemployment rate by educational attainment in 2008 (%) 33 Figure 4.13: The share of Labor force by educational attainment interacted with gender in 2008 (%) 34 Figure 4.14: Unemployment rate by educational attainment interacted with gender in 2008 (%) 35 Figure 4.15: Unemployment rate by age groups in 2008 (%) 36 Figure 4.16: Unemployment rate by gender in 2008 (%) 36 Figure 4.17: The share of labor force by regions in 2008 (%) 37 Figure 4.18: Unemployment rate by regions in 2008 (%) 37 Figure 4.19: Unemployment rate by urban/rural residence in 2008 (%) 38 Figure 4.20: Unemployment rate by married status in 2008 (%) 38 Figure 4.21: Unemployment rate by ethnic in 2008 (%) 39 Figure 4.22: Unemployment rate by household head status in 2008 (%) 39 Figure 4.23 Unemployment rate by number of children aged below 16 in 2008 (%) .40 LIST OF APPENDICES Appendix 1: The share of labor force by gender and by residence from 2000-2010 62 Appendix 2: Age structure of labor force in urban/rural residence by gender in 2011 62 Appendix 3: Structure of labor force by level of education and vocation training in 2011 (%) 63 Appendix 4: Rate of trained labor force by residence and gender in 2011(%) 63 Appendix 5: Rate of trained labor force by education levels in 2011 (%) 63 Appendix 6: Unemployment rate by age groups in 2010 and 2011 (%) 63 Appendix 7: Age structure of unemployed population by residence and by gender in 2011 (%) 64 Appendix 8: Unemployment rate by the educational attainment in 2010 and 20 11 64 .Appendix 10: Descriptive statistic ' ; Variable Dependent variable Mean Std Dev Min unemployment Impendent variables Educational variables 0.081 0.273 Secondary level 0.405 0.491 Professional vocation level 0.072 0.259 University level or above 0.062 0.242 Primary vocation level Interaction variables: 0.007 0.084 Male*secondary 0.217 0.412 Male*profession vocation 0.033 0.178 Male*university or above 0.042 0.202 Male*primary vocation Individual characteristics 0.004 0.067 Male 0.506 0.500 Age30-39 0.275 0.446 Age40-49 0.299 0.458 Age50+ 0.183 0.386 Married 0.807 0.394 Illness 0.143 0.350 Ill days 0.674 9.089 365 Inactive days 2.129 15.853 365 KinhHoa 0.835 0.371 Household head Household characteristics 0.375 0.484 Household expenditure 34.171 26.589 2.13 399.88 Log of household expenditure Regional characteristics 3.329 0.618 0.76 5.99 Urban 0.271 0.445 Red River Delta 0.196 0.397 Northwest 0.053 0.224 North Central 0.097 0.296 South Central Coast 0.091 0.288 Central Highlands 0.066 0.249 Southeast 0.139 0.346 Mekong Delta 0.211 0.408 Sample 18,640 Source: Author's calculation from the data VHLSS 2008 (N=18,640) 65 Max Alppend"IX 11 T esf m2 reI a f Ionsh"lp bet ween unempJI oyment and ed uca1ona f IIevel Educational level Employed Unemployed Total Secondary level Professional Vocation University level& above Primary Vocation 7,827 6,845 1,239 1,083 130 17,124 92.68% 90.60% 92.19% 93.12% 97.74% 91.87% 1,516 Count % within level Total Primary level & less Count 618 710 105 80 % within level 7.32% 9.40% 7.81% 6.88% 2.26% 8.13% Count 8,445 7,555 1,344 1,163 133 18,640 % within level 100% 100% 100% 100% 100% 100% Pearson chi2(4) = 32.4657 Pr = 0.000 Ho: there is no relationship between unemployment probability and educational level Pearson Chi-Square=32.4657, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and educational level Appendix 12: The relationship between gender and education (%) Education attainment Gender Female Male Total Count %within level Count %within level Count %within level Primary level or less Secondary level Professional vocation University or above Primary vocation 4,540 3,509 553 550 50 9,202 49.34% 38.13% 6.01% 5.98% 0.54% 100% 3,905 4,046 791 613 83 9,438 41.38% 42.87% 8.38% 6.50% 0.88% 100% 8,445 7,555 1,344 1,163 133 18,640 45.31% 40.53% 7.21% 6.24% 0.71% 100% Total Pearson chi2 (4) = 136.6969 Pr = 0.000 Ho: there is no relationship between gender and educational level Pearson Chi-Square=136.6969, Pr=O.OOO < 5% => Rejecting Ho => There 1s no relationship between gender and educational level 66 Appendix 13: Testing relationship between unemployment and gender interacted with education (%) Female Employed Count %within level Unemployed Count %within level Total Count %within level Male*Education attainment Total All levels Primary level or less Secondary level Professional vocation University or above Primary vocation 8,302 3,740 3,697 730 573 82 17,124 48.48% 21.84% 21.59% 4.26% 3.35% 0.48% 100% 900 165 349 61 40 1,516 59.37% 10.88% 23.02% 4.02% 2.64% 0.07% 100% 9,202 3,905 4,046 791 613 83 18,640 49.37% 21% 22% 4% 3% 0% 100% Pearson ch12 (5) = 122.1905; Pr = 0.000 Ho: there is no relationship between unemployment and interaction variable between gender and educational level Pearson Chi-Square=122.1905, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and interaction variable between gender and ii educational level Appendix 14: The share of labor force by Gender and educational attainment in 2008 (%) Educational attainment Secondary Professional university level level vocation Gender Primary level Female 24.36% 18.83% 2.97% 2.95% 0.27% Male 20.95% 21.71% 4.24% 3.29% 0.45% primary vocation Source: Author's calculatiOn from VHLSS 2008 Appendix 15: Unemployment rate by Gender and educational attainment (%) Unemployment by Gender By educational attainment(%) Primary Secondary Professional Level Vocation Level 7.96% 10.29% 9.98% Female 7.71% 8.63% 4.23% Male Source: Author's calculatiOn from VHLSS 2008 67 University Level 7.27% 6.53% Primary Vocation 4.00% 1.20% Appendix 16: Testing relationship between unemployment and age groups • Age groups Employed Age22-29 Age30-39 Age40-49 Age50+ Total 3,877 4,895 5,332 3,020 17,124 85.57% 95.59% 95.52% 88.67% 91.87% 654 226 250 386 1,516 14.43% 4.41% 4.48% 11.33% 8.13% Count 4,531 5,121 5,582 3,406 18,640 %within age 100% 100% 100% 100% 100% Count %within age Unemployed Count %within age Total Pearson chi2(3) = 482.0451 Pr = 0.000 Ho: there is no relationship between unemployment probability and age group Pearson Chi-Square=482.0451, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and age groups Appendix 17: testing relationship between unemployment and gender By Gender Female Male Employed Count 8,302 % within gender 48.48% Unemployed Count 900 % within gender 59.37% Count Total 9,202 % within gender 49.37% Pearson chi2 (1) = 66.0165 Pr = 0.000 8,822 51.52% 616 40.63% 9,438 50.63% Total 17,124 100% 1,516 100% 18,640 100% Ho: there is no relationship between unemployment probability and gender Pearson Chi-Square=66.0165, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and gender 68 - Appendix 18: testing relationship between unemployment and regions By Regions • Employed Count %within region Unemployed I Count %within region Total Count %within region Red River Delta North East North West North Central South Central Coast Central High lands South East Mekon g Delta Total 3,394 2,609 957 1,660 1,554 1,165 2,251 3,534 17,124 19.82% 15.24 % 5.59% 9.69% 9.07% 6.80% 13.15% 20.64% 100% 261 138 28 143 146 72 336 392 1,516 17.22% 9.10% 1.85% 9.43% 9.63% 4.75% 22.16% 25.86% 100% 3,655 2,747 985 1,803 1,700 1,237 2,587 3,926 18,640 19.61% 14.74 % 5.28% 9.67% 9.12% 6.64% 13.88% 21.06% 100% Pearson chi2(7) = 186.3118; Pr = 0.000 Ho: there is no relationship between unemployment probability and regions Pearson Chi-Square=186.3118, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and regions Appendix 19: Relationship between unemployment and rural/urban residence By Residence Rural Urban 12,788 4,336 Employed Count 25.32% % within residence 74.68% 720 796 Unemployed Count 47.49% % within residence 52.51% 13,584 5,056 Count Total 27.12% % within residence 72.88% Pearson chi2(1) = 346.3649; Pr = 0.000 Total 17,124 100% 1,516 100% 18,640 100% Ho: there is no relationship between unemployment probability and urban/rural residence Pearson Chi-Square=346.3649, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and residence 69 A-ppendix 20: Testing the relationship between unemployment and married • status By Marital Status Married Others 14,198 2,926 82.91% 17.09% 852 664 56.20% 43.80% 15,050 3,590 80.74% 19.26% Count % within marital status Unemployed Count %within marital status Count Total % within marital status Employed Total 17,124 100% 1,516 100% 18,640 100% Pearson chi2(1) = 639.0625; Pr = 0.000 Ho: there is no relationship between unemployment probability and marital status Pearson Chi-Square=639.0625, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and marital status Appendix 21: Testing the relationship between unemployment and ethnic • By Ethnic Kinh Hoa Others 14,157 Count Employed 2,967 % within ethnic 82.67% 17.33% 1,410 Unemployed Count 106 % within ethnic 93.01% 6.99% 15,567 Count 3,073 Total %within ethnic 83.51% 16.49% Pearson chi2(1) = 108.0338; Pr = 0.000 Total 17,124 100% 1,516 100% 18,640 100% Ho: there is no relationship between unemployment probability and ethnic Pearson Chi-Square=108.0338, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and ethnic 70 Appendix 22: Testing the relationship between unemployment and being household head • Count % within household head Unemployed Count % within household head Count Total % within household head Employed Household head Household Others head 6,691 10,433 60.93% 39.07% 1,219 297 80.41% 19.59% 11,652 6,988 62.51% 37.49% Total 17,124 100% 1,516 100% 18,640 100% Pearson chi2(1) = 225.5792; Pr = 0.000 Ho: there is no relationship between unemployment probability and being household head Pearson Chi-Square=225.5792, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and being household head Appendix 23: Testing the relationship between unemployment and number of children below 16 Number of Children below 16 Employed Unemployed Total Count % within number of children Count % within number of children Count % within number of children Total 8,193 5,224 2,877 664 142 22 17,124 47.85% 30.51% 16.80% 3.88% 0.83% 0.13% O.Dl% 100% 998 363 132 18 1,516 65.83% 23.94% 8.71% 1.19% 0.26% 0.07% 0.00% 100% 9,191 5,587 3,009 682 146 23 18,640 49.31% 29.97% 16.14% 3.66% 0.78% 0.12% 0.01% 100% Pearson chi2(6) = 201.7513; Pr = 0.000 Ho: there is no relationship between unemployment probability and number of children below 16 years old Pearson Chi-Square=201.7513, Pr=O.OOO < 5% => Rejecting Ho => There is no relationship between unemployment and number of children below 16 years old 71 Appendix 24: Descriptive statistics • Dependent variable unemployment 18640 0.0813305 0.2733493 18640 18640 18640 18640 0.4053112 0.0721030 0.0623927 0.0071352 0.4909653 0.2586653 0.2418739 0.0841704 0 0 1 1 Independent variables Educational attainments Secondary level Professional vocation level University level or above Primary vocation level Interaction variable between gender and educational attainment Male*secondary Male*profession vocation Male*university or above Male*Erimary vocation 18640 18640 18640 18640 0.2170601 0.0424356 0.0328863 0.0044528 0.4122549 0.2015863 0.1783437 0.0665823 0 0 1 1 18640 18640 18640 18640 18640 18640 18640 18640 18640 18640 0.5063305 0.2747318 0.2994635 0.1827253 0.8351395 0.8074034 0.1428112 0.6736588 2.1286480 0.3748927 0.4999733 0.4463910 0.4580353 0.3864515 0.3710646 0.3943494 0.3498896 9.0890460 15.8526100 0.4841082 0 0 0 0 0 1 1 1 365 365 18640 18640 18640 18640 18640 18640 18640 18640 18640 18640 10.2370000 0.7704936 0.2712446 0.1960837 0.0528433 0.0967275 0.0912017 0.0663627 0.1387876 0.2106223 0.6178310 0.9171416 0.4446140 0.3970432 0.2237266 0.2955942 0.2879035 0.2489216 0.3457340 0.4077615 7.663424 0 0 0 0 12.89893 1 1 1 1 Control variables ~ Male Age30-39 Age40-49 Age50+ KinhHoa Married illness ill days Inactive days Household head Log of household expenditure Number of young children Urban Red River Delta Northwest North Central South Central Coast Central Highlands Southeast Mekong Delta 72 ' • IJnemployment Secondary level 0.038 I Professional vocation level -0.003 -0.230 pniversity level or above -0.012 -0.213 frimary vocation level -0.018 -0.070 -0.024 -0.022 I 0.010 0.638 -0.147 -0.136 -0.045 ~ale*secondary ale*profession vocation -0.003 -0.174 0.755 -0.054 -0.018 -0.111 Male*university or above -0.011 -0.152 -0.051 0.715 -0.016 -0.097 -0.039 1'-fale*primary vocation -0.017 -0.055 -0.019 -0.017 0.789 -0.035 -0.014 Male -0.060 0.048 0.046 0.011 0.020 0.520 0.208 -0.084 -0.043 -0.077 -0.018 0.016 -0.052 -0.064 I Age30-39 ~ge40-49 -0.087 0.030 -0.001 -0.031 -0.017 0.005 -0.001 ~ge50+ 0.055 -0.017 0.029 -0.015 -0.009 0.029 0.040 ~Hoa 0.076 0.144 0.045 0.081 0.022 0.084 0.031 -0.185 -0.006 -0.031 -0.066 -0.004 -0.008 -0.023 lmness 0.051 -0.042 -0.016 -0.041 0.007 -0.042 -0.016 Ill! days 0.109 -0.001 -0.007 -0.008 -0.002 0.004 -0.007 Inactive days 0.151 -0.010 -0.019 -0.022 -0.001 -0.009 -0.016 !Household head Log of household I expenditure -0.110 0.022 0.000 -0.049 0.015 0.251 0.049 0.106 0.074 0.160 0.293 0.024 0.049 0.116 Number of young children -0.100 -0.077 -0.098 -0.094 -0.016 -0.055 -0.074 0.136 0.016 0.133 0.237 0.006 -0.014 0.085 0.033 :Married I urban Red River Delta -0.018 0.230 0.036 0.036 0.008 0.125 INorthwest -0.046 -0.076 0.006 -0.024 -0.006 -0.039 0.010 INorth Central -0.002 0.096 0.004 -0.015 -0.011 0.059 -0.002 I • -0.072 South Central Coast I Central Highlands Southeast Delta , Urban I ' Red River Delta 0.005 -0.013 -0.007 0.037 -0.007 0.004 -0.008 -0.023 -0.028 -0.013 -0.018 0.003 -0.017 -0.019 0.071 -0.054 -0.015 0.045 0.023 -0.038 -0.015 0.035 -0.201 -0.072 -0.052 0.003 -0.110 -0.051 -0.044 -0.117 I Northwest -0.072 I North Central -0.061 -0.162 -0.077 I 0.058 -0.157 -O.o75 -0.104 I 0.014 -0.132 -0.063 -0.087 -0.085 0.196 -0.198 -0.095 -0.131 -0.127 -0.107 -0.048 -0.255 -0.122 -0.169 -0.164 -0.138 i South Central Coast Central Highlands I Southeast I Mf'lRejecting Ho =>coefficients of the regressors are not all zero 79 ...UNIVERSITY OF ECONOMICS HO em MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM -NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE IMPACT OF EDUCATION ON UNEMPLOYMENT. .. research focuses on investigating the impact of education on unemployment incidence using the cross-section data from VHLSS2008 while considering gender and the other control variables at the individual... the impact of education on unemployment incidence and evaluate the role of educational attainment on unemployment for different individuals according to their gender •!• To examine the relationship