Causes of the Vietnamese Brain Drain Syndrome
Bibliographic record
Abstract
In 2010, Vietnam had more than 2 million emigrants residing in countries such as: the United States, Australia, Canada, Germany, France, the Republic of Korea, Japan, and the United Kingdom (World Bank). This number of emigrants accounted for 2.5% of the whole domestic population. Also according to this date, the emigration rate of tertiary-educated population was 27.1% in 2000. Due to relatively high number of emigrants, Vietnam has experienced rapid growth in receipts of remittances recently. Hernandes-Cross (2005) reports that the amount of remittances sent to Vietnam from other countries reached USD $1.2 billion in 1999. By 2003, this number has grown to $2.6 billion. In terms of Gross Domestic Product (GDP), the increase in remittances represents a growth from 4.4 percent of GDP in 1999 to 7.4 percent of GDP in 2003. Since 2000, foreign remittances to Vietnam have been larger than official development assistance and at a comparable level to foreign direct investment (Donald 2008). Despites benefits from remittances, emigration imposes a substantial cost on Vietnam in terms of lost talent and human resources, or brain drain. The term “brain drain” is normally used to describe the outflow of highly skilled workers from developing to developed counties. In ofher words, i refers to the departure of the mos talented individuals at an appreciable rate in a way that is thought to be detrimental for sending countries (Bushnell and Choy 2001). Although it might be argued that the loss in human capital can be offset by the “amount of remittances sending home, Taylor (1996) showed an overreliance on labor exporting as a strategy for economic development generally produces disappointing results. In countries with relative labor surplus like Vietnam, policies that facilitate emigration to capture a significant share of the remittances, may provide a valuable supplement to, but not a substitute for, a well-designed and carefully implemented national development policy (Taylor 182). It is true that incomes from remittances can be invested in human capital for long-term economic growth, but inefficient policies to retain high skilled workers within Vietnam will counter that effort. This leads to the argument that overall brain drain has negative effects on the development of Vietnam and the government should intervene, possibly restricting emigration to protect the economy's growth. Although, there have been previous studies about causes of low skilled workers emigration (Dang 2008, Pham 2011), there has been hardly any study about the emigration of high skilled workers. Lacking such data, we cannot determine appropriate policies to retain those workers. Therefore, this study aims to provide a model about causes leading to brain drain in Vietnam at micro, meso, and macro-level. Its results suggest possible policies for the Vietnamese government to preserve the stock of high skilled workers within the country. The paper is organized as follows. Section 2 reviews previous literature on cause and consequences of brain drain. Using that information, Section 3 develops hypotheses about the impacts of different factors on the emigration decision and the returning decision. Section 4 provides detailed description of methods used to collect data. Section 5 presents data, Section 6 analyzes results of this study and Section 7 concludes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.000 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".