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Inflation targets and the yield curve: New Zealand and Australia versus the US

2000· article· en· W2013875071 on OpenAlexafffund
Pierre L. Siklos

Bibliographic record

VenueInternational Journal of Finance & Economics · 2000
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsWilfrid Laurier University
FundersSocial Sciences and Humanities Research Council of CanadaOesterreichische NationalbankUniversity of SydneyReserve Bank of New Zealand
KeywordsEconomicsInflation (cosmology)Yield curveYield (engineering)EconometricsMonetary economicsMonetary policyReal interest rateDeflationInterest rateMacroeconomics

Abstract

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This study considers whether the slope of the yield curve for New Zealand contains useful economic information. In order to provide some perspective, the present study also contrasts the New Zealand experience with evidence based on US and Australian data. The principal findings of this study are as follows: (1) At short horizons, typically 2 years or less, the term structure for New Zealand behaves as in the expectations hypothesis of the term structure. (2) Nevertheless, there are departures from the expectations hypothesis, especially in the period when inflation objectives in New Zealand were on a declining path. Moreover, the policies of the US had a critically important impact around 1993–1994. (3) Some evidence was found of an effect from the spread to future inflation but only when the headline CPI is used to measure inflation; the links disappear entirely once CPI ex-credit costs are employed. The study argues that such results are consistent with a credible inflation targeting regime, so that the term structure serves possibly to signal changes in real interest rates rather than inflation in New Zealand. (4) There is good evidence that the spread helps predict future output in New Zealand, although the effect seems to dissipate after 1 year. Once we distinguish between periods of positive versus negative growth rates in real gross domestic product (GDP), the spread influences output up to 2 years into the future. Also, when output growth is measured asymmetrically, rising inflation expectations depress output growth. Copyright © 2000 John Wiley & Sons, Ltd.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.062
GPT teacher head0.256
Teacher spread0.194 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2000
Admission routes2
Has abstractyes

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