The role of the gravity forces on firms’ trade
Bibliographic record
Abstract
Abstract . This paper offers both a theoretical framework and empirical evidence on the role that the two gravity forces, namely market size and geographical distance, have indirectly through imports, on firms’ exports patterns. The model shows that sourcing from bigger and closer markets implies higher productivity gains that, in turn, increase firms’ ability to enter export market as well as their export value. Exploiting data on product‐ and destination‐level transactions of a large panel of Italian firms, the paper shows that, on average, the indirect effects of the gravity forces are about one third of their direct effects. Résumé . Rôle des forces de gravité sur le commerce des entreprises . Cet article offre à la fois un cadre théorique et des preuves empiriques sur le rôle que deux forces de gravité, à savoir la taille du marché et l’éloignement géographique, peuvent indirectement exercer sur les profils d’exportation des entreprise en fonction de leurs importations. Ce modèle montre que l’approvisionnement sur des marchés plus vastes et plus proches engendre de meilleurs gains de productivité, augmentant ainsi la capacité des entreprises à intégrer le marché d’exportation ainsi que la valeur de leurs exportations. En s’appuyant sur des données provenant d’un large panel d’entreprises italiennes et relatives aux transactions par type de produit et par destination, cet article montre qu’en moyenne, les effets indirects des forces de gravité représentent environ un tiers de leurs effets directs.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".