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Record W173180920

Why Growth Performance Differed across Countries in the Recent Crisis: the Impact of Pre-crisis Conditions

2011· article· en· W173180920 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of Economics and Finance · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsOpenness to experienceEconomicsFinancial crisisPer capita incomePosition (finance)Real gross domestic productGross domestic productSample (material)Emerging marketsMonetary economicsDevelopment economicsMacroeconomicsInternational economicsFinance
DOInot available

Abstract

fetched live from OpenAlex

The growth performance of countries proved to be very different during the recent financial crisis. The objective of the paper is to investigate why, despite the fact that the crisis hit countries simultaneously, the length and depth of the crisis turned out to be very different across countries. We apply principal component analysis to derive a single indicator for growth performance which includes different aspects of GDP dynamics before and after the crisis. Then we apply multivariate regressions analysis to analyze whether pre-crisis economic conditions and/or structural characteristics can explain the differences in growth performance in a sample of 37 countries. We focus primarily on industrialized countries but also include dynamic emerging economies. The pre-crisis conditions we investigate include the fiscal situation, trade competitiveness, output and credit growth; the structural characteristics we selected were country size, openness, the share of specific sectors and per capita income. The three indicators which proved to explain most robustly the cross country differences in the recent crisis and thus could also be used as predictors for future crises are the current account position, credit growth and GDP growth in the run-up period. Trade competitiveness improved the performance in the crisis. Past credit and GDP growth impaired country performance.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.249
Teacher spread0.221 · 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