FOMC forecasts: Is all the information in the central tendency? Federal Reserve Bank of St. Louis Working PaperNo
Bibliographic record
Abstract
Since 1980, there has been a substantial improvement in the performance of monetary policy among most of the industrialized countries. Bernanke et al. (1998) attribute this success to the adoption of inflation targeting, but they are somewhat vague in defining what it means to have an inflation target. Even countries that do not have numerical inflation targets are said to be inflation targeting if they focus on a long-term objective for price stability (low inflation) and publish inflation forecasts. By this broad definition, even the Federal Reserve may be considered to have an inflation target. This article describes and documents 23 years of FOMC forecasts. Congress required the Fed to begin preparing and reporting forecasts in 1979. Section 108 of the Humphrey-Hawkins Act explicitly required the Fed to submit “written reports setting forth (1) a review and analysis of recent developments affecting economic trends in the nation; (2) the objectives and plans…with respect to the monetary and credit aggregates…; and (3) the relationship of the aforesaid objectives and plans to the shortterm goals set forth in the most recent Economic Report of the President. ” In order to satisfy the third item, the Federal Reserve Chairman began reporting a summary of Fed policymakers ’ forecasts to Congress in July 1979. 1 Since then, similar summaries of forecasts have been reported every February and July. Forecasts are made of annual, fourthquarter-over-fourth-quarter growth rates for nominal gross domestic product (GDP), real GDP, and inflation. 2 Fed policymakers also forecast the average level of unemployment for the fourth quarter of
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.046 | 0.027 |
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".