Reexaminando la hipótesis de convergencia a la economía líder regional en México: un análisis de cointegración en panel
Bibliographic record
Abstract
In this study the hypothesis of regional convergence in Mexico with\nthree definitions of leading economy, National, Distrito Federal and the\nUnited States, is reviewed through several methods of integration and\npanel cointegration for the period 1970-2012. The results of the panel\nunit root tests show evidence of convergence of gdp per capita of the\nstates of Mexico with regard to the Distrito Federal and the United States\nin the sub-period 1970-1985, and not with regard to the national average,\nwhich is more evident for the period 1985-2012. Paradoxically to the\nresults of the unrestricted version, we found evidence of convergence in\nthe restricted version of the test through the estimate mean group (mg)\nin the second period compared to the national average and the United\nStates. Regarding the Distrito Federal, the evidence for the first period\nwas very flimsy since the Hausman test could not withstand it
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".