Short-run and long-run effects of copper price on Junín’s economic growth
Bibliographic record
Abstract
Our research used a SVAR to analyze the underlying copper price shocks, that is, a commodity shock for the Junín department in Peru. The results of a short- and long-run SVAR were based on traditional matrix constraints that capture the fact that domestic shocks do not affect international prices. The main conclusion is that before the pandemic a shock in the international price of copper decreases economic growth and inflation in the department of Junín in Peru, after the pandemic the opposite happens. As a result of the model, the short and long-run effects of the international copper price on the main macroeconomic variables of Junín in Peru are statistically significant. Before the pandemic, the dynamics of the international copper price reflected the existence of the curse of mining resources in copper institutions. Before the pandemic, a percentage increase in the international price of copper decreased economic growth, reflecting the existence of the mining resource curse in copper institutions. After the pandemic, a percentage increase in the price of copper increases economic growth by up to 0.0488%, then decreases over time, noting the transitory effect of economic recovery and poor management of mineral resources.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".