MétaCan
Menu
Back to cohort
Record W2760102624 · doi:10.1515/sbe-2017-0019

Have Financial Stability Concerns Changed the Priority of the Central Bank of the Republic of Turkey?

2017· article· en· W2760102624 on OpenAlexaboutno aff
Ekrem Erdem, Ümit Bulut, Emrah Koçak

Bibliographic record

VenueStudies in Business and Economics · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsCointegrationStability (learning theory)EconomicsUnit rootFinancial stabilityQuarter (Canadian coin)Exchange rateKalman filterMonetary policyPrice of stabilityEconometricsFinanceMacroeconomicsFinancial systemMathematicsComputer science

Abstract

fetched live from OpenAlex

Abstract This paper aims at analysing whether the Central Bank of the Republic of Turkey (CBRT), designing a new monetary policy framework to achieve financial stability in the last quarter of 2010, tries to pursue financial stability by putting price stability on the back burner. To this end, a forward-looking reaction function that is extended with nominal exchange rate gap and nominal domestic credits gap is estimated for the CBRT. The paper first performs unit root and cointegration tests and finds that the variables become stationary at first differences and that there is a cointegration relationship among variables. Then, the paper conducts the Kalman filter to obtain time varying parameters. The findings show that the coefficients of all explanatory variables did not change too much after the new monetary policy framework of the CBRT in the last quarter of 2010. Therefore, this paper asserts that the CBRT continues to pursue price stability as its primary goal and tries to achieve financial stability by using macroprudential tools. Thus this paper concludes that financial stability concerns have not changed the priority of the CBRT.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.181
GPT teacher head0.279
Teacher spread0.098 · 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 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueStudies in Business and EconomicsSame topicMonetary Policy and Economic ImpactFrench-language works237,207