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Record W2567611565 · doi:10.6000/1929-7092.2017.06.01

Inflation Dynamics and Monetary Transmission in Turkey in the Inflation Targeting Regime

2016· article· en· W2567611565 on OpenAlexvenueno aff
Arzu Tay Bayramoğlu, Larry Allen

Bibliographic record

VenueJournal of Reviews on Global Economics · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInflation (cosmology)Monetary economicsInflation targetingMonetary policyTransmission (telecommunications)Keynesian economicsMacroeconomicsPhysicsComputer science

Abstract

fetched live from OpenAlex

This study aims to analyse the determinants of inflation and the effectiveness of the monetary transmission in Turkey. The study is covering the period 2003:Q2-2015:Q3 which consists of just an inflation targeting time before 2008, and inflation and financial stability targeting time after 2008 global financial crises. The autoregressive distributed lag model (ARDL) bound test is used for the long-run relationship and a VAR analysis for the short-run dynamics. The cointegration results reveal that the credit growth, US/TL exchange rate, real effective exchange rate, interest rate, and imported inflation are the determinants of inflation in Turkey in the long run. Also, our empirical findings indicate that exchange rate is the most effective factor in inflation. According to the VAR model’s impulse responses, the key drivers of inflation are the movements in the US/TL nominal effective exchange rate, real effective exchange rate, interest rate, GDP growth in the short-term, and credit growth is in the medium-term. ARDL cointegration and impulse responses also show that interest rate and credit growth are efficient instruments as a monetary policy for the inflation targeting and financial stability.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.041
GPT teacher head0.244
Teacher spread0.203 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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