Trade, skill-biased technical change and wages in Mexican manufacturing ∗
Bibliographic record
Abstract
This paper analyses and quantifies the effects of trade liberalisation and skill-biased technical change, both exogenous and trade-induced, on the skill premium and real wages of unskilled and skilled workers in the Mexican manufacturing sector, using industry- and firm-level data for 1984-1990 from the Encuesta Industrial Anual. The novelty of the paper lies in its strategy for identifying causality, which uses differences across industries over time in the relative price of machinery and equipment in the US as an instrument for skill-biased technical change. The effect of trade-induced SBTC on wages, and especially on wage inequality, appears substantial. The regressions show that trade liberalisation and changes in the relative price of equipment in the US, which induce exogenous SBTC in Mexico, explain one quarter of the increase in relative skilled wages between 1984 and 1990. This rise in the skill premium due to SBTC and trade liberalisation mainly reflect a rise in real skilled wages, although with some specifications it was amplified by a fall in the real wages of unskilled workers.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".