Short-Run Market Access and the Construction of Better Transportation Infrastructure in Mexico
Bibliographic record
Abstract
We calculate the short-run effect that the construction of the Durango-Mazatlán highway in late 2013 and the Mexico City-Tuxpan highway in early 2014 produced on welfare in every municipality and on market access in every location of Mexico. Our estimates suggest that the former highway produced benefits not only in the region where the new highway is located, but in vast areas in the north of the country. Analogous estimates show that the latter highway mostly benefited regions near Tuxpan, but these focalized benefits were larger than any of the benefits derived from the construction of the Durango-Mazatlán highway. The municipalities in the south of the country have net short-run losses from the infrastructure construction due to losses in competitiveness. Our model is consistent with the observed sectoral growth in Sinaloa, Durango, and Veracruz in 2014. Qualitatively, market access and welfare change in the same direction and magnitudes. We thus recommend using the market access approach for shortrun analysis of infrastructure, because it is much less computationally intensive. JEL Codes: R1, R4, F15
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".