El Impacto del Salario Mínimo Real en la Pobreza Laboral en México: en Análisis Econométrico con Arima (2018-2024)
Bibliographic record
Abstract
El presente artículo analiza el impacto del salario mínimo real sobre la pobreza laboral en México (2018–2024) mediante un modelo econométrico ARIMAX, utilizando el Índice de Tendencia Laboral de la Pobreza (ITLP) como variable dependiente, incorporando la inflación de alimentos y una intervención por la disrupción en el segundo trimestre del año 2020. El modelo de mejor ajuste utiliza por niveles el salario mínimo real (índice base 2018=100) con residuos que no muestran autocorrelación. Los resultados estimados indican un efecto inverso del salario real sobre el Índice de Tendencia Laboral de la Pobreza (ITLP), mientras que el efecto contemporáneo de la inflación en alimentos no resulta concluyente. El choque exógeno de la pandemia domina la dinámica a corto plazo. Se aplican pruebas de robustez para la validación del modelo, destacando la preferencia por la especificación en niveles. Con ello, la evidencia muestra que de manera gradual las trayectorias sostenidas del salario mínimo real contribuyen a contener la pobreza laboral
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".