Bibliographic record
Abstract
Several economists, including Cover (1992), Ammer and Brunner (1995), Macklem, Paquet, and Phaneuf (1996), have worked over the past few years to determine whether monetary policy shocks have asymmetric effects on output. These authors have generally found that negative monetary shocks tend to reduce output growth significantly, and that positive shocks generally have a weaker or even negligible impact. The goal of this study is to determine whether asymmetric reactions can be observed in the Canadian labour market. Because employment is an important factor in the output process, discovering how this variable reacts to monetary policy shocks could lead to a better understanding of where asymmetric effects on output originate. I have estimated the model in two stages, using the generalized moments method, and have made correction to the variance-covariance matrix of estimators proposed by Newey (1984) in order to take into account the generated regressors. Overall, the results agree with those of previous output studies, except for employment defined as the number of hours worked per person in each period. The asymmetric effects observed, however, diminish or disappear altogether when other real variables are added to the model.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".