Una prueba empírica del modelo de Newby en la economía mexicana
Bibliographic record
Abstract
Trade relations between Mexico and the United States have grown in the interests of North America Free Trade (NAFTA), under which Mexico has become the second largest trading partner of the United States, after Canada, the total trade between Mexico and the United States exceeded $ 260 billion dollars in 2000. In addition, much has been said in studies conducted by various international financial institutions, on the positive or negative role exerted by the economic performance of the United States on Mexico. This influence of the U.S. economy over Mexican economy can be seen mostly from 2000, as the U.S. economy has made an erratic economic growth and has been reflected in the performance of the Mexican financial market. Unfortunately, although there has been a moderate strengthening of the international capital market and the existence of an optimal environment for private investment, Mexican Stock Exchange (BMV) continues showing a closely relationship with the United States financial market behavior. Therefore it is considered necessary to study the high dependence between the economic and financial performance of the United States and Mexico, which is the aim of this work, the application of the Newby´s model, to determine if it is an efficiency estimator of the risk premium on the IPC for the Mexican Stock Exchange over the period 2001 to 2006. To perform this empirical test, data were taken from Mexican and U.S. macroeconomic environment, considering the strong dependence that exists between Mexico and the U.S. economy. The results showed no sufficient evidence to test the research hypothesis, stating that the Newby´s model was an efficient estimator of the risk premium of the IPC for the period of study, but opens the possibility to develop a model that includes itself other variables that could have a significant impact on the Canadian stock market.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".