Some Implications of the Zero Lower Bound on Interest Rates for the Term Structure and Monetary Policy
Bibliographic record
Abstract
In an economy where cash can be stored costlessly (in nominal terms), the \nnominal interest rate is bounded below by zero. This paper derives the implications of \nthis nonnegativity constraint for the term structure and shows that it induces a nonlinear \nand convex relation between short- and long-term interest rates. As a result, the long-term \nrate responds asymmetrically to changes in the short-term rate, and by less than \npredicted by a benchmark linear model. In particular, a decrease in the short-term rate \nleads to a decrease in the long-term rate that is smaller in magnitude than the increase \nin the long-term rate associated with an increase in the short-term rate of the same size. \nUp to the extent that monetary policy acts by affecting long-term rates through the term \nstructure, its power is considerably reduced at low interest rates. The empirical \npredictions of the model are examined using data from Japan.
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.
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 | 0.000 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".