UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM – THE NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS EDUCATION-OCCUPATION MISMATCH IN VIETNAM: DETERMINANTS AND EFFECTS ON EARNINGS BY PHAN THI THANH THAO MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, August 2016 UNIVERSITY OF ECONOMICS ERASMUS UNVERSITY ROTTERDAM HO CHI MINH CITY INSTITUTE OF SOCIAL STUDIES VIETNAM THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS EDUCATION-OCCUPATION MISMATCH IN VIETNAM: DETERMINANTS AND EFFECTS ON EARNINGS A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAN THI THANH THAO Academic Supervisor: Dr. TRUONG DANG THUY HO CHI MINH CITY, August 2016 CERTIFICATION “I certify that the substance of this thesis has not already been submitted for any degree and have not been currently submitted for any other degree. I certify that to the best of my knowledge and help received in preparing this thesis and all sources used have been acknowledged in this thesis.” PHAN THI THANH THAO ACKNOWLEDGEMENTS The process of writing a thesis is a collaborative experience involving the support and helps from many people. I want to express my gratitude to those who give me the tremendous support to complete this thesis.
I am deeply indebted to my parents for their invaluable supports and constant reminders. The sentence I hear every day is “lose weight and finish your thesis, daughter”. I really appreciate for their efforts in reminding a very lazy girl like me. And their boundless love are motivation for my endeavor in building up my life more interesting and valuable.
I wish to express my heartfelt gratitude to my supervisor Dr. Truong Dang Thuy for his valuable suggestions during the time I write this thesis. He has also encouraged and reminded me to pursue this topic from the initial ideas to the final completion. I am really thankful him for his guidance and patience.
Finally, after finishing this thesis, I realize that each success is a process of continuous effort. And more difficulties you overcome, more values you get for your life. Phan Thi Thanh Thao August, 2016 ABSTRACT We examine the education-occupation mismatch in horizontal and vertical respects; and their impacts on earnings of Vietnamese workers. We start by clarifying definitions and causal reasons of mismatch between education and occupation: in major and level.
Analyzing survey data from 267 workers, we find that the mismatch between schooling major and working field which is caused by unavailability of job in the schooling field (demand-related horizontal mismatch) has a negative effect on earnings. And the mismatch between schooling major and working field caused by remaining reasons (supply-related horizontal mismatch mismatch) has no statistically significant impact on earnings. Interestingly, a horizontal mismatch because of supply-related reasons for workers who learned science major has a positive effect on earnings. Furthermore, when examining the effect of vertical mismatch, a negative effect of under-education on wage is found whereas over-educated years have no significant effect on wage.
From policy perspective, we recommend that people should avoid major mismatch for best earnings. However, in case individuals learn science and work in mismatched career voluntarily, their earnings will be better than ones in adequate career. Moreover, students should avoid over-education to reduce the waste of resources unless they want to study more for their own preferences. Main research questions.
Organization of the study. Mismatch in major between career and schooling (horizontal education- occupation mismatch). Determinants of horizontal education-occupation mismatch. Over-education and under-education (Vertical education-occupation mismatch).
Determinants of vertical education-occupation mismatch. Effect of education-occupation mismatch on earnings. Mincer’s earnings model. Wage effect of horizontal education-occupation mismatch.
Wage effect of vertical education-occupation mismatch. 18 METHODOLOGY AND DATA. Horizontal mismatch and earnings. Vertical mismatched and earnings.
Horizontal education-occupation mismatch. Vertical education-occupation mismatch. Horizontal education-occupation mismatch. Determinants of horizontal education-occupation mismatch.
Effect of horizontal education-occupation mismatch on earnings. Vertical education-occupation mismatch. Determinants of vertical education-occupation mismatch. Effects of vertical education-occupation mismatch on earnings.
63 CONCLUSION AND POLICY IMPLICATION. 81 LIST OF TABLES Table 4. 1: Descriptive statistics of continuous variables. 2: Age among horizontal mismatched groups.
3: Schooling years among horizontal mismatched groups. 4: Experience in current firm among horizontal mismatched groups. 5: Experience in current working field among horizontal mismatched groups. 6: Reasons for mismatch among horizontal mismatched groups.
7: Education level among horizontal mismatched groups. 8: Schooling major group and horizontal mismatched groups. 9: Gender and horizontal mismatched groups. 10: Marital status among horizontal mismatched groups.
11: Number of children and horizontal mismatched groups. 12: Mobility status among horizontal mismatched groups. 13: Long-term health status among horizontal mismatched groups. 14: Firm type and horizontal mismatched groups.
15: Working place among horizontal mismatched groups. 16: Immigration status among horizontal mismatched groups. 17: Earnings level among horizontal mismatched groups. 18: Fulltime/part-time job and horizontal mismatched groups.
19: Age of vertical mismatched groups. 20: Schooling years among vertical mismatched groups. 21: Experience in current firm among vertical mismatched groups. 22: Experience in current field among vertical mismatched groups.
23: Gender and vertical mismatched groups. 24: Education level of vertical mismatched groups. 25: Schooling major group among vertical mismatched groups. 26: Marital status among vertical mismatched groups.
27: Number of children among vertical mismatched groups. 28: Firm type and vertical mismatched groups. 29: Fulltime/part-time job among vertical mismatched groups. 30: Mobility status among vertical mismatched groups.
31: Long-term health status among vertical mismatched groups. 32: Working place among vertical mismatched groups. 33: Immigration status among vertical mismatched groups. 34: Determinants of horizontal mismatched education: Ordinal logistic regression.
35: Marginal effect of determinants of horizontal mismatched education. 36: Effects of horizontal mismatched education on earnings. 37: The earnings effects of mismatch by schooling majors. 38: Determinants of over-educated years.
39: Effects of vertical mismatched education on earnings (Duncan and Hoffman model). 40: Effects of vertical mismatched education on earnings (Verdugo and Verdugo model). 69 LIST OF GRAPHS Graph 4. 1: Distribution of over-education (Duncan and Hoffman model).
2: Distribution of under-education (Duncan and Hoffman model). 3: Effects of vertical mismatched education on earnings. 4: Effects of vertical mismatched education on earnings for male and female. 68 LIST OF APPENDICES APPENDIX 1: t-test for determinants of horizontal mismatched education.
81 APPENDIX 2: Chi-squared test for determinants of horizontal mismatched education. 82 APPENDIX 3: t-test for determinants of vertical mismatched education. 83 APPENDIX 4: Chi-squared test for determinants of vertical mismatched education. Problem statement The last fifteen years have a rapidly increase in the number of students with high education level in Vietnam.
It can be demonstrated through the increase in proportion of college and university graduates over population which nearly doubled from over 25 graduates/10,000 people in 2005 to nearly 49 graduates/10,000 people in 2014 (GSO Vietnam, 2016). This great change is also found in rapid increase of master graduates which was only 0.66 graduates/10,000 people in 2005 and raised five times to nearly 3.5 graduates/10,000 people in 2014 (GSO Vietnam, 2016). One of the reasons explaining this dramatically increase in number of high educated graduate may be Spence’s (1973) job-screening model, which says that in an imperfect information labor market, employers use education as a signal to recognize individuals with higher ability and productivity. As a result, employees tend to overly invest in education for better job opportunity and future wage.
This large increase in highly educated labor force causes an unbalance in labor market where supply excess demand. This disequilibrium in labor market makes high educated workers accept unskilled job or a mismatched job to avoid to be unemployed. In an interview set up by Hiep Pham (2013), Le Duy Luong – the human resource director of a Japanese electronics company in Hoa Cam Industrial Zone – said that hundreds of blue- collar worker in his company had university degrees. Furthermore, Hiep Pham (2013) also noticed that over-education is rising in Vietnam.
The job employees are working does not require as much knowledge as they learned in school and it seems a waste when they are over-educated (a vertical education-occupation mismatch). Another result of supply excess in labor market is that employees have to work in an unrelated job to his schooling major (horizontal education-occupation mismatch). At the 1 time when individual chose university major, he expected that he could work in the field of that schooling major in the future. However, there are many indicators affecting his decision in choosing the studied major: expected wage, changes in labor market equilibrium, non-price orientations, and the probability of graduation of that major.
And it seems many young people do not know clearly what they want, what they can and what they should. So that this is also a reason for the mismatch between career they are working and the university major they learned. These education-occupation mismatches are not only a waste in money and human capital but also a reflection of labor market failure. There are many studies about mismatch in education grade and in schooling major including Tsang and Levin (1985), Sicherman (1990), Bauer (2002), Björklund and Kjellström (2002), Büchel and Mertens (2004), Robst (2007), Dolton and Silles (2008), Nordin, Persson and Rooth (2010).
Bender and Heywood (2011). However this research issue is quite new in Vietnam. As mentioned above, individuals have tendency to learn more because they believe in a higher future earnings. But is it true that wage will change with the change of education level? When considering the effect of over-education and under-education on earnings, it is found that employees with over-education earn less than ones with adequate education level (Kiker et al.
However, how much over-education or under-education affect earnings? It can be 35-40 percent declining in earnings for over-educated person as Dolton (2008) found from data of one large civil university in the UK. Furthermore, Kiker et al. (1997) examined a sample of 50,000 Portuguese individuals and found that over-educated workers earn approximately 8 percent less than similar workers with the same education level who are working in an adequate job. On the other hand, some studies found that the effect of an additional year of over- schooling is positive.
Duncan and Hoffman (1981) also revealed that return to an additional year of over education can be positive for US workforce. Nevertheless, they 2 also found that this estimated return to an additional year of over-education is only a half of return to an additional year of required education. According to Kiker et al. (1997), workers with less education than requirement for the job earn 16.3% more than those with the same education level who are working in an adequate job.
Bauer (2002) used a large panel data set of Germany in period 1984-1998 to examine workers with similar job but different education levels, and he concluded that under-educated employees bear a penalty for an additional year of deficit education is 6- 11 percent. The same result is also found by Duncan and Hoffman (1981) with 4.2% decrease in earnings for an additional year of deficit education. Furthermore, using data from National Survey of American College Graduates in 1993, he found that workers with mismatched between schooling major and career bear a decrease in earnings 10-12% depending on mismatched type (Robst, 2007). Another evidence comes from study of Nordin et al.
(2010) for Swedish people from 28-36 years old which indicates an earnings penalty of 12-20% for mismatched workers. Although the field is widely investigated, there are very few studies about this issue in Vietnam. This study will give a basic overview about horizontal and vertical mismatched education and their impacts on earnings.