Monetary Policy Report, July 2023
Bibliographic record
Abstract
In the second quarter of 2023, total annual infation fell to 12.1% and the rise of core infation halted and stood at 10.5%; both measures were lower than those forecasted in the April Report but remained well above the 3.0% target. The aggregate effects of monetary policy actions and the unwinding of certain shocks that affected prices will contribute towards bringing infation closer to the target in 2024. By component, the annual variations in the CPI for food and the CPI excluding food and regulated items have lessened more markedly than anticipated by the Central Bank’s technical staff, underlying the decline in annual infation. However, prices of regulated items and services continued to rise, nonetheless at a slower pace than expected, particularly in the case of services. For these two groups, price indexation mechanisms have resulted in the transmission of some transitory increases in certain CPI sub-components (e.g., food) to other items (e.g., rents, utilities, etc.), thus generating a greater persistence of already high infation. This is acerbated by the gasoline price increases required to correct the defcit of the Fuel Price Stabilization Fund (Fondo de Estabilización de los Precios de los Combustibles, FEPC). Consequently, the CPI for regulated items forecast increased going forward relative to the April Report given the higher gasoline price adjustments announced by the Government. For the remaining items (food, goods, and services), the forecasted trajectory declined due partly to the lower-than-estimated infation, a more notable reduction in the international prices of some food items and freight costs, lower exchange rate and cost pressures on prices, and a faster than anticipated decrease in excess demand. This occurs in a contractionary monetary policy environment that aims to reduce infation towards rates close to the 3.0% target by the end of 2024. Against this background, headline infation for yearend 2023 is forecast at 9.0% (formerly 9.5%) and 3.5% for yearend 2024 (previously 3.4%) (Graph 1.1). In the same timeframes, the core infation forecast has been revised downward from 8.9% to 7.9%, and from 3.9% to 3.7%, respectively (Graph 1.2). These projections are subject to high uncertainty, especially surrounding future behavior of international fnancing conditions and the exchange rate, fuctuations in domestic demand, the possible occurrence of the El Niño natural climate phenomenon, and future decisions regarding domestic fuel and electricity prices.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.126 | 0.172 |
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".