Institutional Quality, Trade, and the Changing Distribution of World Income
Bibliographic record
Abstract
Conventional wisdom holds that institutional changes and trade liberalization are two main sources of growth in per capita income around the world. However, recent research (e.g., Rigobon and Rodrik 2004) suggests that the Frankel and Romer (1999) trade and growth finding is not robust to the inclusion of institutional quality. In this paper, the authors argue that this "trade and growth puzzle" can be explained once institutional quality is acknowledged as a determinant of the willingness to save and invest, and hence acknowledged as a determinant of long-run comparative advantage. The paper consists of two parts. First, the authors develop a theoretical model which predicts that institutions determine a country's underlying comparative advantage: countries that have good institutions will tend to export relatively more capital-intensive (or sophisticated) goods compared with countries that have poor institutions; trade can magnify the effect of institutional quality on income, leading to greater income divergence than if countries remain in autarky. Second, using a panel of over eighty countries and twenty years of data, the authors find empirical support for their hypotheses.
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 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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".