Intra-industry Trade of the EU, USMCA, and their Member States in the Period 2000–2022 – Does Economic Integration Matter?
Bibliographic record
Abstract
RESEARCH OBJECTIVE: The objective of this paper is to identify the similarities and differences between intra-industry trade (IIT) of European Union and IIT of United States-Mexico-Canada Agreement (USMCA) and their member states. Moreover, we answer the question if more advanced economic integration goes together with more intensive IIT. THE RESEARCH PROBLEM AND METHODS: We conducted an analysis of IIT disaggregated into 6-digit HS codes using the UN Comtrade database, and employed Grubel-Lloyd indices. We aggregated GL indices for selected countries and selected blocs of countries (here the EU and USMCA) and for the world. THE PROCESS OF ARGUMENTATION: We chose the EU and USMCA as examples of correlations between economic integration and intra-industry trade because they are some of the most important RTAs in the world and their members fulfil conditions for intensive IIT. We verify the hypothesis that sharing membership in such a grouping is an important factor intensifying bilateral IIT. RESEARCH RESULTS: We have shown that EU IIT shares were considerably higher than those in the case of the USMCA, and the advantage of the EU grew over time. Our empirical study confirms that sharing membership in RTA bloc is an important factor intensifying bilateral IIT. Also, more advanced integration of adjacent countries, especially those that differ little with respect to economic potential, wealth, and culture, helps to increase IIT shares. CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: We compare the IIT characteristics of the EU and its member states with those of the USMCA bloc and its members in a relatively long and turbulent period (2000–2022). To the best of our knowledge, there was no such analysis of world IIT during this period. Moreover, the correlation between the intensity of intra-industry trade and the advancement of economic integration has not been studied in literature very often.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".