Fiscal implications of interest rate normalization in the United States
Bibliographic record
Abstract
Abstract We study the fiscal implications of interest rate normalization from the zero lower bound (ZLB) in the United States. At the ZLB, falling tax revenues and real bond prices increase government debt accumulation. During normalization, interest payments remain above the path without the ZLB, and government debt can increase further despite the recovery of output and tax revenues. Against the yardstick of ability to pay, interest rate normalization is unlikely to threaten federal debt sustainability at the current net federal debt level about 100% of GDP. If the government fails to reform Social Security and major healthcare programs, sovereign default risk can rise more quickly when debt reaches 150% of GDP. Also, a more active monetary policy anchors inflation expectations better, generates a faster recovery and, hence, slows down debt accumulation more than a less active one does. An unexpected early liftoff, however, can prolong a recession and increase debt accumulation more at the ZLB and during normalization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".