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Record W2127262836 · doi:10.1142/s0219622005001684

FINANCIAL LIBERALIZATION AND EFFICIENCY IN TUNISIAN BANKING INDUSTRY: DEA TEST

2005· article· en· W2127262836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Information Technology & Decision Making · 2005
Typearticle
Languageen
FieldDecision Sciences
TopicEfficiency Analysis Using DEA
Canadian institutionsYork University
Fundersnot available
KeywordsLiberalizationFinancial systemFinancial crisisBusinessFinancial sectorBanking industryEconomicsFinanceInternational economicsMarket economyMacroeconomics

Abstract

fetched live from OpenAlex

IMF policies have been widely criticized in the aftermath of the Asian crisis. Key critics questioned the appropriateness and the sequencing of financial liberalization programs which, along with insufficient monitoring and inadequate prudential regulations, left the financial sectors of the affected countries highly leveraged and exposed. This paper examines the impacts of similar reforms on the efficiency of the banking system in Tunisia, a country whose economy has been reshaped by the IMF/World Bank prescribed economic adjustment plans since 1987. Using various DEA models and panel data covering the period 1992–1997, we evaluate the individual effects of each component of the reforms on the banking industry overall. Meanwhile, we compare the effects on banks because of the different ownership structures over time. We also pay particular attention to specific factors that have kept the financial sector in Tunisia relatively stable in the midst of the global market turmoil caused by the Asian crisis.

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.

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)0.004
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.002
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0020.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.349
Teacher spread0.330 · 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