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Record W4404820678 · doi:10.17645/pag.8920

The European Central Bank: From a Price Stability Paradigm to a Multidimensional Stability Paradigm

2024· article· en· W4404820678 on OpenAlexafffund
L. Quaglia, Amy Verdun

Bibliographic record

VenuePolitics and Governance · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of VictoriaUniversité du LuxembourgUniversity of Florida
KeywordsParadigm shiftStability (learning theory)Price of stabilityEconomicsPolitical scienceComputer scienceMacroeconomicsEpistemologyMonetary policyPhilosophy

Abstract

fetched live from OpenAlex

This article maps and explains the shift in economic thinking at the European Central Bank (ECB), i.e., its “ideational” evolution over the past two decades. When the ECB was set up in 1999 its institutional design and epistemic outlook were very much inspired by the legacy of the German central bank, the Bundesbank. Thus, the ECB embraced a “price stability” paradigm that prioritized inflation control. However, over time, policy learning in response to economic shocks (first and foremost, a series of consecutive financial and economic crises from 2008 onwards) and the internal organic evolution of the ECB have led to a shift of economic thinking at the Bank, which has also been reflected by its policy actions. The new paradigm can be characterized as a “multidimensional stability” paradigm. By relying on inter alia secondary literature, speeches, semi-structured elite interviews, and data we collected concerning the previous experience at national central banks of senior ECB staff, we identify a novel causal mechanism for ideational change at the Bank: the change in the composition of senior managerial staff from 1999 onward.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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 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

Citations10
Published2024
Admission routes2
Has abstractyes

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