How Important are Financial Shocks for the Canadian Business Cycle
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.
Bibliographic record
Abstract
In this paper, we investigate the importance of financial shocks for the Canadian business cycle employing the financial friction DSGE framework following Bernanke, Gertler, and Gilchrist (1999) with an extension of a small-open economy feature. In particular, we explored the importance of an external finance premium shock and an aggregate net worth shock. In order to identify financial shocks in the model, we utilized financial data in estimating our model. Our variance decomposition results showed that the external finance premium shock to account about 7.5% and the aggregate net worth shock to account about 5.6% of the variance of the business fixed investment in Canada. Also, our historical decomposition results and smoothing of the various financial variables showed that data on corporate leverage ratio to be particularly useful in identifying the financial shocks in the model. Finally, when the financial shocks were present in the model, relative importance of the investment- specific technology shock was substantially subdued that it accounted for only 17% of the variance of the business fixed investment - much lower than the results reported in the former empirical studies.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it