The Role of Production Sharing and Trade in the Transmission of the Great Recession
Bibliographic record
Abstract
The great recession of 2008-2009 resulted in a large fall in trade relative to output. Real trade fell roughly three times more than real GDP in the U.S. and Mexico, and by a factor of five in Canada. The decline in trade and output was particularly large in sectors with high levels of production sharing (goods produced in multiple, sequential stages in more than one country). Motivated by these observations, this paper asks two quantitative questions: 1) What was the role of trade in the transmission of the recession in North America? 2) What was the contribution of production sharing to the large fall in trade? To answer these questions this paper develops a quantitative open economy model of production sharing. The benchmark calibration can account for 72% of the fall in output in Canada, 19% of the fall in output in Mexico, and about two-thirds of the fall in trade for both countries. In the quantitative exercises production sharing can account for 40% of the fall in 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".