The Trans Pacific Partnership for Vietnam: a good thing for Vietnam?
Bibliographic record
Abstract
To study the consquences of the Trans Pacific Partnership on the Vietnamese economy Using a five product econometric modelto measure the impact of individual elements, then synthetize the full set of measures. Vietnam, along with 11 other countries having a Pacific coast (including the USA and Canada), is now finalizing negotiations on an agreement, which will change profoundly the conditions of trade in the region. Our goal is to understand the consequences of the agreement, and test if it will have favorable consequences for Vietnam, considering that, as all treaties of this kind, we have to measure the balance of both positive and negative individual decisions. For this we shall use a five product model, developed for the Vietnamese Ministry of Planning and Investment. The products are: Agriculture, Manufacturing, Construction, Non-Financial Services and Financial Services. The model will use annual data for the period 1995-2012, built especially for the project by the General Statistical Office. Its structure can be described as short term Keynesian, with long term classical features. Its uses a Cobb-Douglas production function, and it features a price-wage loop, with a WS-PS wage determination. Its equations follow globally an error correction framework. It identifies Foreign Direct Investment, through its motivations and its impact on structural parameters of the economy. It has been estimated using a system method, and the process mostly met with success, in spite of the volatility of data and the ongoing transition process, which questions the stability of formulations. In our study, we shall start from a reasonable 10 year forecast, and shock in success the elements of the agreement: tariffs rates, quotas, local subsidies. Then we will use the actual decisions, or what we know of them at the time of the study, to summarize the outcome of the actual agreement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".