Bibliographic record
Abstract
Business confidence is a well-known leading indicator of future output. Whether it has \ninformation about future investment is, however, unclear. We determine how informative \nbusiness confidence is for investment growth independently of other variables using US \nbusiness confidence survey data for 1955Q1{2016Q4. Our main findings are: (i) business \nconfidence leads US business investment growth by one quarter, and structures investment \nby two quarters; (ii) business confidence has predictive ability for investment growth; (iii) \nremarkably, business confidence has superior forecasting power, relative to conventional \npredictors, for investment downturns over 1{3 quarter forecast horizons and for the sign of \ninvestment growth over a 2-quarter forecast horizon; and (iv) exogenous shifts in business \nconfidence reflect short-lived non-fundamental factors, consistent with the `animal spirits' \nview of investment. Our findings have implications for improving investment forecasts, \ndeveloping new business cycle models, and studying the role of social and psychological \nfactors determining investment growth.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".