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Record W2106247207

What Does the Philadelphia Fed's Business Outlook Survey Say About Local Activity? ∗

2008· article· en· W2106247207 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economic and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Value (mathematics)Stock marketSurvey data collectionVariety (cybernetics)BusinessMarketingEconomicsGeographyStatistics
DOInot available

Abstract

fetched live from OpenAlex

which solicits the views of local manufacturers about conditions at their companies. This survey, which has been conducted continuously since May 1968, provides a unique early view of U.S. economic activity each month. Consequently, economists, the media, and investors carefully watch the survey, and the survey is widely believed to have an influential impact on the stock market. The value of the survey as a signal is due to its unusual longevity and to the fact that manufacturing remains quite sensitive to – and central to — shifts in overall economic activity. As a result, even though the survey seeks the views of manufacturers only in the local area, it is useful in estimating how manufacturers and other businesses throughout the U.S. economy are performing. The survey asks several questions that have been shown to be useful in estimating quantitatively how the entire U.S. economy is doing along a variety of dimensions. These studies have been reported in the Philadelphia Fed’s Business Review, in the September/October 1998 issue and again in the Fourth Quarter 2003 issue. The Business Outlook Survey (BOS) receives nationwide attention because it is viewed as both a national and regional indicator. Oddly enough, it is easier to show that the BOS performs well in terms of predictive value at the national level than it is to show the same result at the local level. This is because many economic statistics are not available regionally, but they are available nationally; for example,

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.050
GPT teacher head0.218
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations6
Published2008
Admission routes1
Has abstractyes

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