REGIONALIZATION AND INTRA-INDUSTRY TRADE. AN ANALYSIS OF AUTOMOBILE INDUSTRY TRADE IN NAFTA
Bibliographic record
Abstract
As was shown in some previous studies, the creation of the North American Free Trade American (NAFTA) has significantly increased trade and investment flows between member countries. Consequently, it seems appropriate to analyze the incidences of the free trade agreement on the nature of trade. In this paper, we study the intra-industry trade in the automobile industry within the NAFTA area. Our results highlight an increase in intra-industry trade since the beginning of the 1990s. The importance of intra-industry trade is evaluated with the Grubel and Lloyd indicator (1975). For final and intermediate goods, we distinguish those which are horizontally differentiated in quality (differences in unit values) from those in varieties (similar unit values). In NAFTA, intra- industry trade exists in most sectors and in two bilateral relations (United States-Canada and United States-Mexico). Therefore, we analyze the nature of that increase and more precisely, the determinants of intra-industry trade in this industry. Through a gravity model integrating some country-specific and sector variables, we found that economic distance and market size have a predominant influence on horizontal intra-industry trade. In this way, we also confirm the significant role of regional integration on the intensity of intra-industry trade.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".