Determinants of the remittances sent to Mexico 1980-2022: was there a structural change?
Bibliographic record
Abstract
Objective: We identify a new long-term relationship between remittances, Mexico’s GDP, the United States Industrial Production Index, and the real exchange rate.Methodology: For a quarterly sample from 1980 to 2022, we identified a structural break on the 3rd quarter of 2002. We divided the initial sample into two subsamples in order to estimate the corresponding cointegration vectors.Results: The cointegration vector for the second subsample has two important changes as compared to that of the first subsample.Limitations and implications: It is implied that remittances can actually generate a stabilizing effect on the foreign exchange market.Originality and value: i) the sign of the estimated coefficient of the real exchange rate changes from negative to positive, ii) a time trend must be incorporated in the cointegration space.Conclusions: We identify a long-term relationship among remittances and the variables that determine them after the structural break.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".