Decomposing episodes of large growth in international trade
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract I use bilateral trade data from a variety of countries to decompose the patterns of trade growth across various goods classifications during episodes of rapid growth in bilateral trade. I find that bilateral trade growth during these episodes is fragmented —less than 5% of goods classifications account for over 65% of overall bilateral trade growth. I quantitatively assess whether “Melitz‐style" trade models, with heterogeneous productivity firms, CES demand and fixed and variable costs of exporting, can match the observed fragmentation of bilateral trade growth. I find the standard model generates less than 40% of the observed fragmentation in the data, as measured by the share of total trade growth accounted for by various quantiles of goods classifications. However, by incorporating heterogeneous tariff and productivity changes imputed from US production and export data, I find that the model generates approximately 90% of the magnitude of fragmentation of trade growth across goods as in the data.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it