An estimation of the nominal exchange rate level that would eliminate the mexican currency misalignment: is it moving in the right direction in 2025?
Bibliographic record
Abstract
We estimate an approximation of the equilibrium real exchange rate to measure the Mexican currency overvaluation, which is approximately of 25.3% in the first quarter of 2024. The nominal exchange rate level that would return the real exchange rate to its equilibrium level would be $22.77 Mexican pesos per US dollar, in contrast to an average nominal exchange rate of $17.00 observed in first quarter of 2024 and an average nominal exchange rate of $19.51 in the second quarter of 2025. The National Institute of Statistics and Geography (INEGI) changed in 2023 the base year to measure real variables as GDP, private consumption, public consumption and exports from 2013 to 2018 chained pesos. It is essential to estimate the VAR and a VEC models for period 1995Q1-2024Q1 using the new time series provided by INEGI to obtain updated and subsequent estimates of the magnitude and how it changes the Mexican peso overvaluation. The fitted values of the cointegration equation provide us with the approximation of the equilibrium real exchange rate. Although the observed real exchange rate has risen from the local minimum reached in the first quarter of 2024, it is appreciating again starting in the second quarter of 2025. If this appreciation continues, there is a risk of a return to significant exchange rate overvaluation.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".