Bibliographic record
Abstract
Almost 80 percent of capital goods production in the world is concentrated in 10 countries.Poor countries import most of their capital goods.We argue that international trade in capital goods has quantitatively important effects on economic development through two channels: (i) capital formation and (ii) aggregate TFP.We embed a multi country, multi sector Ricardian model of trade into a neoclassical growth model.Barriers to trade result in a misallocation of factors both within and across countries.We calibrate the model to bilateral trade flows, prices, and income per worker.Our model matches several trade and development facts within a unified framework.It is consistent with the world distribution of capital goods production, cross-country differences in investment rate and price of final goods, and cross-country equalization of price of capital goods and marginal product of capital.The cross-country income differences decline by more than 50 percent when distortions to trade are eliminated, with 80 percent of the change in each country's income attributable to change in capital.Autarky in capital goods results in an income loss of 17 percent for poor countries, with all of the loss stemming from decreased capital.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".