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Record W1146885184

The U.S. Economy. A Challenging Recovery. Sidestepping into the End of the Year

2013· article· en· W1146885184 on OpenAlexaboutno aff
Jack Malehorn

Bibliographic record

Venue˜The œjournal of business forecasting · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsAtlantaEconomic forecastingEconomicsState (computer science)EconomyEconomic historyFinancePolitical scienceMetropolitan areaHistory
DOInot available

Abstract

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PARTICIPANTS I Beacon Economics = Los Angeles, California; Conf. Board = Conference Board, New York, New York; Fannie Mae= Fannie Mae, Washington, D.C.; Global Insight = Global Insight, Eddystone, Pennsylvania; GSU - EFC = Georgia State University, Economic Forecasting Center, Atlanta, Georgia; Moody's Economy = Moody's Economy.com, Westchester, Pennsylvania; Mortgage = Mortgage Bankers Association, Washington, D.C.; NAM = National Association of Manufacturers, Washington, D.C.; Northern Tr = Northern Trust Company, Chicago, Illinois; Perryman Gp = The Perryman Group, Waco, Texas; Royal Bank of Canada, Toronto, Ontario, Canada; SP UBS = UBS Bank, Salt Lake City, Utah; US Bank = U.S. Bank & Nuveen Capital Asset Management, Minneapolis, Minnesota; US Chamber = U.S. Chamber of Commerce, Washington, D.C.; Wells Fargo = Wells Fargo Bank, San Francisco, California.The Economic Consensus Outlook for Fall 2013 has a little bit of everything in it. There are indeed some positive notes with respect to the nation's economy, but there exist several significant negative factors as well. Rajeev Dhawan, Director of the Economic Forecasting Center at Georgia State University's Robinson College of Business, in his Forecast of the Nation, paints a tentative picture of economic activity. On the positive side, he cites recent job growth, almost bullish auto sales, and reasonably strong housing data. But, on the negative side is poor income growth, an overabundance of consumer caution, and ongoing political uncertainty linked to the federal budget and upcoming public policy decisions. Dr. Dhawan provides a textbook analysis in his publication, citing the domino effect realized in the housing sector. From the initial request for building loans, the process incorporates the builder, suppliers, and the ultimate final consumer. However, the consumer, having made the commitment for a new home, looks out into the troubled world environment and sees unrest throughout the Middle East spilling over to domestic gas prices, lack of strong consistent job gains, and subsequent income growth. Under the circumstances, we may need to wait awhile before we make a commitment to go all the way, that is, for new furniture, new drapes, etc. As such, this veil of negativism spreads to corporate management decision makers, signaling we should wait until we pull the trigger on long-term investment plans. The last straw appears to be linked to Washington, D.C., where the political fray surrounding the federal budget deficit, health care reforms on the horizon, and the timing of the Fed finally withdrawing its easy money policy. For the most part, this scenario seems reflected across the board in the Consensus Outlook forecasts. Adding to this, Dr. Ray Perryman figures there to be little momentum building in the economy until several months down the road linked to the situation in Europe, as well as several of the factors already addressed.As such, the Consensus Economic Outlook calls for a continuation of the current relative lackluster economic performance, which has characterized this seemingly long recovery period. Real GDP is forecast to advance at a 2% rate over the forecast period. …

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0130.010
Open science0.0010.006
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.0440.012

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 head0.030
GPT teacher head0.197
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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