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Record W6946689713 · doi:10.34989/swp-2023-5

Gazing at r-star: A Hysteresis Perspective

2023· article· en· W6946689713 on OpenAlexaff

Bibliographic record

VenueEconstor (Econstor) · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsBank of Canada
Fundersnot available
KeywordsNucleofectionTSG101Gestational periodHyporeflexiaFusible alloyDysgeusiaLiquationTubulopathy

Abstract

fetched live from OpenAlex

Many explanations for the decline in real interest rates over the last 30 years point to the role that population aging or rising income inequality plays in increasing the long-run aggregate demand for assets. Notwithstanding the importance of such factors, the starting point of this paper is to show that the major change driving household asset demand over this period is instead an increased desire—for a given age and income level—to hold assets. We begin by presenting a simple explanation for this pattern that relies on integrating retirement and intertemporal substitution motives in saving decisions. We then show how the interaction of these two saving motives can have profound implications in terms of the shape of asset demands, the possibility of multiple steady state real interest rates, and a potential role for monetary policy to influence the long-run evolution of real rates. The framework highlights how an inflationary episode followed by a strong monetary response, as we are currently witnessing, can have long-term implications for real interest rates.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0250.002

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.

Opus teacher head0.026
GPT teacher head0.251
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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