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Record W3123388530

The Importance of Harmonious Monetary and Fiscal Policies: An Examination upon Credit Interest Rates of Banks in Turkey

2019· article· en· W3123388530 on OpenAlexaboutno aff
Mustafa Tevfik Kartal

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsInterest rateMonetary policyContext (archaeology)Order (exchange)Monetary economicsEconomicsQuarter (Canadian coin)Fiscal policyPoint (geometry)Economic policyFinanceGeography
DOInot available

Abstract

fetched live from OpenAlex

High bank interest rates have been one of the main problems in certain periods for Turkey. When the development trend of interest rates is examined, it is seen that interest rates were high in the past, they decreased between 2002 and 2010, and they have been increasing after the year 2011. In order to reach low bank interest rates, monetary and fiscal policies are the main tools that can be used. Therefore, the application of monetary and fiscal policies in a harmonious way has substantial importance. Within this context, this study is prepared to evaluate the recent experience of Turkey in terms of harmonious monetary and fiscal policies. In this context, the period after 2010 is included and the period after 2016 is focused especially. Hence, recent approaches and practices in Turkey in terms of the harmonious policy are examined. As a result of the study, it is determined in the study that tight monetary policy and loose fiscal policy are applied generally in Turkey. However, monetary and fiscal policies have begun to be harmonious with the last quarter of 2018. In this context, the credit interest rate of banks has been decreasing with the last quarter of 2018 which was increasing since 2017. This shows that harmonious policies are so important that low bank interest rates cannot be reached without the practice of harmonious policies. This is the most important point that should be stated. Therefore, if it is desired to reach a low credit interest rate of banks, it is highly recommended that Turkey should always adopt harmonious monetary and fiscal policies.

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)0.004
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.022
GPT teacher head0.233
Teacher spread0.211 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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