International Trade and Macroeconomic Dynamics with Labor Market Frictions
Bibliographic record
Abstract
This paper studies how labor market frictions affect the consequences of trade integration in a two-country, stochastic, general equilibrium model of trade and macroeconomic dynamics with heterogeneous firms, endogenous producer entry, and frictional labor markets. The model successfully reproduces important empirical regularities that characterize trade integration both in the long run and over the business cycle. Two key results emerge. First, trade integration is always beneficial for welfare by inducing higher productivity, but unemployment can temporarily rise as trade barriers are lowered. Gains from trade are smaller in countries with more rigid labor markets, as production gradually shifts toward more flexible economies. Second, trade integration has important business cycle consequences. In contrast to traditional international business cycle models, but consistent with the data, the model correctly predicts that stronger trade linkages lead to increased business cycle synchronization. However, the strength of this effect and the consequences for output volatility depend on the labor market characteristics of integrating partners.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".