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ABSTRACT
Blue-collar employment growth increases schooling opportunities by raising incomes, but also reduces incentives for some students to advance beyond compulsory education. These contradictory influences may help to explain relatively slow and uneven growth of progression to upper-secondary schooling in Vietnam, which has experienced a foreign investment boom in mainly low-skill manufacturing industries. We use data on participation rates and scores in an upper-secondary school entrance exam to analyze variation due to demand-side and supply-side factors. The data come from less advanced provinces and so illuminate the challenges of deepening educational development at the extensive margin, especially among ethnic minority populations.
Acknowledgements
We are grateful to UNICEF-Hanoi and especially Ms. Le Anh Lan for framing conversations and access to data sources. We thank the editor and referees of this journal as well as Valerie Kozel and seminar participants at ERIA, IDE-JETRO (Tokyo), University of Economics Ho Chi Minh City, UNICEF-Hanoi, the Central Institute for Economic Management, and the University of Wisconsin–Madison for helpful comments on earlier drafts.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 Rankings from the recent World Economic Forum’s Readiness for the Future of Production report (WEF Citation2018) highlighted the challenges that Vietnam faces in transitioning to globalization. On an indicator called ‘drivers of production’, Vietnam is ranked 13th on global trade and investment among 100 countries, between Australia and France. On human capital, however, it is ranked 70th, between Sri Lanka and Georgia, and on technology and innovation it is ranked 90th, between Paraguay and Cameroon. The human capital index notably includes low rankings for Vietnam on key components such as the mean years of schooling (rank: 74), quality of universities (75), quality of vocational training (80), and on-the-job training (74).
2 Demand for skills has also grown. But skilled jobs are concentrated in government and state-owned enterprises whose activity levels have grown far slower than private-sector industries. The latter are subject to crowding-out in domestic capital markets and have much lower capital and skill-intensity (Phan and Coxhead Citation2013).
3 Findlay and Kierzkowski (Citation1983) note that when all individuals are identical, the equilibrium difference in lifetime earnings between skilled and unskilled workers is zero: higher earnings of skilled workers are exactly offset by additional schooling costs that they incur. It follows that a relative price change that favours unskilled labor will induce more children to quit school earlier, other things equal.
4 If services production is of intermediate factor intensity relative to sectors 1 and 2, then an expansion in their demand must reduce the skill premium. Suppose that the endowment point E represents factors available for tradable production after demand for non-tradable services (S) has been satisfied, so E(H,L) = E(HT–HS, LT–LS). Then, increased output of S will reduce E, moving it down and to the left from its original location. The new skill premium must be lower than its original value.
5 For a comparable finding from Mexico see Atkin Citation2016. In a global panel of countries, Blanchard and Olney (Citation2017) also found a negative relationship between growth in less skill-intensive exports and educational attainment.
6 In another uniquely Vietnamese dimension, low overall returns to private sector employment of skilled workers have been exacerbated by capital constraints due to crowding out by state sector enterprises (Phan and Coxhead Citation2013).
7 These estimates are lower than the widely accepted world average of 10% (Psacharopoulos and Patrinos Citation2004), but are comparable with those from similar regional economies. Tangtipongtul (Citation2015) estimated an average return to education in Thailand of about 13%, but this is highly convex, with estimated returns to primary schooling only 1.8%, and general secondary school only 5%; the majority of the labor force is educated to these levels or below. For Indonesia, overall returns are estimated in the medium–high single digits (Purnastuti, Miller, and Salim Citation2013; Newhouse and Suryadarma Citation2011; Coxhead Citation2014).
8 A low value of this parameter will also indicate approximate effects of present bias or hyperbolic discounting on a student’s schooling decision.
9 When test scores are the dependent variable, province fixed effects play an especially important role since the G10 exam is not nationally uniform. All exams are required to have math and literature sections, but individual provinces have the discretion to add other sections and to apply their own grading standards.
10 A more accurate count of the eligible population would come from counts of school enrolment by the same cohort in years preceding the test, e.g. Grades 7–8. Obtaining these data will be a post-Covid research task.
11 The provinces in our data set are poorer and more rural than the national average, so these test participation rates are also somewhat below the national average rate.
12 The VHLSS covers only a sample of districts in each province. These have been expanded to a full set of district-level SES data using small-area estimation techniques by Nguyen (Citation2016).
13 Several districts in our data report zero values for FDI employment. Seven district/year observations have very high values and the estimates are sensitive to these. To maintain the focus on relationships in the mass of the distribution rather than in its tails, we have dropped these.