Does a Low Interest Rate Environment Affect Risk Taking in Austria
Bibliographic record
Abstract
It has recently been argued that a prolonged period of low interest rates under benign economic conditions tends to produce excessive risk taking in financial markets. The mechanism by which monetary policy affects investors’ risk positions has been called the “risk-taking channel” of monetary policy. We discuss this channel and compare it with the more traditional broad credit channel. Furthermore, we provide new evidence on the existence of this channel, using Austrian firm and bank data taken from the OeNB’s credit register. In particular, we show that the expected default rates within Austrian banks’ business-loan portfolios increased during the period of low refinancing rates from 2003 to 2005. This result is new and important in at least two respects: first, we construct a measure of Austrian banks’ portfolio risk on the basis of a matched lender and borrower dataset. Second, we specifically identify the effect of a monetary policy regime which is characterized by interest rates that are held at a low level for too long, as opposed to the more traditional effect of monetary policy “shocks, ” usually identified through quarter-on-quarter changes in short-term interest rates.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".