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Record W2587329044 · doi:10.5539/ibr.v10n3p91

Excessive Debt or Excess Savings -- Transition Countries Sovereign Bond Spread Assessment

2017· article· en· W2587329044 on OpenAlexvenueno aff
Boris T. Petkov

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsMarket liquidityMonetary economicsBondDebtFinancial systemInternational economicsBusinessFinance

Abstract

fetched live from OpenAlex

We study the sovereign yield spreads determinants in transition – Central and Eastern Europe (CEE) and Caucasus and Central Asia (CCA) -- countries and try to provide an answer to the key question: was the narrowing of the spreads and their compression a result of improvement of CEECCA countries sovereign’s macroeconomic policy (implemented in early to mid 2000s), or was it due to global excess liquidity provision? If better domestic macroeconomic policy efforts and solid reforms implemented in this period have led to: i) improvement in sovereign debt management e.g., by increasing the average debt portfolio duration and reducing the stock of FOREX debt; ii) development of domestic financial markets with enlargement of the investor’s base and enhancement of the risk management techniques; iii) continuing financial liberalization; iv) sustainable fiscal adjustment, reserve accumulation and price stability; and v) adoption of the most conductive to prosperity institutional structure, then it would be expected that any tighter monetary policy environment in the developed economies should have only a tiny effect on spreads.The models are estimated on an individual basis -- country by country -- using a framework allowing for fractionally integrated variables (ARDL) as well as, by utilising panel data (cross-sectional-time-series) estimation whenever data availability allows.We utilise daily data over the period 2006-2012 and quarterly data over the period 2002-2011. These are the periods for which meaningful comparable data are available for Bulgaria, Croatia, Hungary, Kazakhstan, Poland, Russia, Serbia, and Ukraine (in various combinations).We are careful not to attempt to split the sample into (say two) potential segments for comparison of “normal” versus “crises” period estimates (as customary) as since 2002 / 2003 the transition economies have started to experience the powerful financial effect generated by the excess global liquidity, i.e., the entire period under consideration is constituted by two phases characterised by: i) excess liquidity (2002-2008); and, ii) the Great Depression Mark II (2008 – to present).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.099
GPT teacher head0.379
Teacher spread0.279 · 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.

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
Published2017
Admission routes1
Has abstractyes

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