¿Pueden considerarse significativas las reformas fiscales de México? // Can the Tax Reforms in Mexico be Considered Significant?
Bibliographic record
Abstract
Se establece como objetivo general, analizar la significancia estadística de cambios en la recaudación del Impuesto Sobre la Renta (ISR) y del Impuesto al Valor Agregado (IVA), a partir del año 2000 y hasta el segundo trimestre del 2015, para afirmar o no la variación en la recaudación. Para lograrlo se aplican métodos clásicos con valor crítico significante a 0,05 de alfa, pero complementándolo parámetro delta para establecer el nivel de cambio en poco significante, medianamente significante o de gran significancia. En las conclusiones se deja antecedente que a pesar de lo que parecieran como impactantes cambios en materia fiscal que pudieron haber incidido positiva o negativamente en el pago del ISR e IVA, tales como el acotamiento del régimen de consolidación fiscal, gravámenes complementarios, hasta llegar a la homologación del IVA a tasa 16% para todo el país, en la mayoría de los casos, no se obtuvo evidencia para argumentar eficiencia en la recaudación nacional.------------------------------------It is the purpose of this work to analyze the significance of changes in average for the collection of value-added (VAT) and income taxes from year 2000 and up to the second quarter of 2015. To accomplish that, classic methods of significance will be applied, but contrasted with tests for the typified difference of the average, fundamental parameters of the meta-analysis Cohen's Delta. The main conclusions are that although there have been relevant changes in the tax collection process such as limits in the tax consolidation regime, complementary taxes e.g., flat rate business tax, substitute tax credit to wages, tax on cash deposits and the standardization of the VAT to 16%, there is no strong evidence to state an efficient national tax collection system.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".