The Beige Book: Timely Information on the Regional Economy
Bibliographic record
Abstract
In making monetary policy, the Federal Open Market Committee (FOMC) relies in part on the Beige Book, a report on regional economic conditions released publicly about two weeks before each FOMC meeting. The Beige Book summarizes economic conditions in each of the twelve Federal Reserve districts and provides an overview of national conditions based on the regional reports. ; The Reserve Banks gather information for their regional summaries from a variety of sources, including telephone and written surveys, local news reports, and reports on current and expected economic conditions from the Reserve Banks' boards of directors. Some critics consider this type of anecdotal information too subjective to be of much value. However, recent research applying quantitative methods to Beige Book information shows that the reports provide a useful indicator of national and regional economic activity. ; This article evaluates the relationship between the Sixth District (Atlanta) Beige Book and regional and state per capita employment, real personal income, and real gross state product growth. The analysis also compares the Atlanta Beige Book to next-quarter estimates of economic activity and examines whether it contains information about regional economic activity in addition to that contained in the national Beige Book summary. The authors find that, despite the Beige Book's anecdotal nature, the report provides timely, reliable information when actual data are not yet available, giving policymakers an early indication of the direction of the economy that helps them make informed decisions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.046 |
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".