Anti‐dumping measures as a tool of protectionism: A mechanism design approach
Bibliographic record
Abstract
In this paper we explore the design of optimal incentive‐compatible anti‐dumping (AD) measures. When the weight given to the domestic firm's profit in the government's objective function is relatively small, it is shown that no AD duty should be imposed if the foreign firm reports its own costs, but a constant AD duty should be imposed if the domestic firm reports the foreign firm's cost. When this weight is large, in either case of reporting the AD duty is a prohibitive tariff. The optimal AD measures are modified in the presence of a GATT/WTO constraint. JEL Classification: F12, F13 Les mesures anti‐dumping en tant qu'outil de protectionnisme: une approche en termes de construction de mécanismes. Ce mémoire examine la construction de mesures optimaales anti‐dumping (AD). Quandla valence des profits de la firme domestique est faible dans la fonction objective du gouvernement, on peut montrer qu'aucune mesure AD ne devrait être imposée si l'entreprise étrangère révèle ses propres coûts, mais qu'un droit AD constant devrait être imposé si c'est la firme domestique qui révèle les coûts de l'entreprise étrangère. Quand la valence des profits de la firme domestique est grande, quelle que soit la source de l'information, la mesure AD qui s'impose est un droit de douane prohibitif. Les mesures optimales doivent évidemment être modifiées pour prendre en compte la contrainte engendrée par l'existence des règles du GATT/OMC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".