Thick and Thin Borders in the European Union: How Deep Internal Integration is Within Countries, and How Shallow Between Them
Why this work is in the frame
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Bibliographic record
Abstract
type="main" xml:id="twec12242-abs-0001"> The existence of large border effects is one of the main puzzles of international macroeconomics. The seminal paper by McCallum found that trade between any two Canadian provinces was (on average) 22 times greater than trade between any Canadian province and any US state. Although various authors have estimated internal and external border effects for the whole European Union and some specific European countries, none has done so in the manner that McCallum's seminal paper, stymied by lack of data on region-to-region international trade flows. This study uses a novel data set that captures intra and international truck shipments between Spanish regions and regions in seven European countries during the period 2004–11. It computes internal and external border effects, offering novel results for aggregate flows and the importing countries, and estimates several specifications of the gravity equation, so as to tackle such issues as the multilateral resistance term, heteroscedasticity, and zero flows and non-linear relation between trade and distance. The paper also adds a detailed analysis on the external border effect for each Spanish exporting region and each of the seven European countries considered. By means of this analysis, we shed new light on the relative integration between regions of these seven countries and Spanish exporting regions. Finally, we conduct an extrapolation exercise, computing the ‘trade potentials’ that would be expected in a fully integrated Europe and estimating how long full integration would take to achieve between each Spanish exporting region and each European importing country. To this regard, two alternative scenarios are considered: one using the growth rates of the Spanish exports before the crisis (2001–08) and other considering the post-crisis growth rates (2011–13).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it