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Record W2312024505 · doi:10.5539/ijef.v8n4p289

Sudden Stops and Capital Controls: When to Apply in Turkey

2016· article· en· W2312024505 on OpenAlexvenueno aff
Cenk Gökçe Adaş, F. Yeşim Kartallı

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsSudden stopCapital outflowVolatility (finance)EconomicsCapital (architecture)Monetary economicsCapital controlCapital flowsFinancial crisisEmerging marketsCapital flightShock (circulatory)Foreign direct investmentFinancial capitalCurrent accountFinancial marketCapital marketCapital accountCapital formationFinanceMacroeconomicsMarket economyExchange rateIncentiveGeography

Abstract

fetched live from OpenAlex

Emerging market countries need capital inflows to finance their current account deficits since their domestic savings are not at desired levels. Foreign direct investment is the appreciated form of capital inflows. However, indirect capital inflows can also boost growth if used in a proper manner. If a country has weak fundamentals and institutional structures or there exists an external shock, speculative foreign capital can easily and rapidly fly away while leaving a financial crisis behind. In this study, we summarize the theoretical background of sudden stops, and then try to identify the sudden stops in Turkey for 1996-2009 period and question the reasons of such disruptions. We particularly focus on periods just before and after the global financial crises. To identify a sudden stop period we use “means” and “volatilities” as well as changes in capital inflows/GDP ratios. Finally, we attempt to find out inflow control mechanisms to minimize the volatility of capital movements.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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 designNot applicable
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
Published2016
Admission routes1
Has abstractyes

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