The U.S. Economy. A Challenging Recovery. Sidestepping into the End of the Year
Bibliographic record
Abstract
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. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".