Estimación y pronóstico de la tasa de crecimiento del Producto Interno Bruto de Ecuador: una visión a corto plazo
Bibliographic record
Abstract
Ecuador is the seventh largest economy in Latin America. From 2000 to 2012, the country has been expanding at an average rate of 1,15 % on a quarter over quarter basis, mostly due to a rise in exports. Ecuador´s economy is highly dependent on oil exports. In order to reach its full growth potential, the country needs to reduce its dependence on oil revenue; increase the tax base; achieve political stability and reduce the levels of poverty and inequality. The main objective of this research is specifically marked in estimate and forecast the Gross Domestic Product´s Growth Rate in Ecuador, applying for this Box – Jenkins´ Methodology for ARIMA models. It was obtained a forecast of 3,96 % approximately, that represents a logical result according with the time series.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".