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Record W3147406886

Magnitude X on the Richter Scale: Welfare Cost of Business Cycles in Developing Countries

2001· article· en· W3147406886 on OpenAlex
Stephane Pallage and Michel A. Robe

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

VenueComputing in Economics and Finance · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDeveloping countryEconomicsWelfareScale (ratio)Business cycleEconomies of scaleDeveloped countryMacroeconomicsMicroeconomicsEconomic growthMarket economyPopulationGeography
DOInot available

Abstract

fetched live from OpenAlex

Economic fluctuations are much stronger in developing countries than in the United States. Yet, while a large literature debates what constitutes a reasonable estimate of the welfare cost of business cycles in the US, it remains an open question how large that cost is in developing countries. Using several model economies, we provide such a measure for a large number of low--income countries. Our first main result is that the welfare cost of output fluctuations per se is far from trivial in those countries, and typically averages 15 to 30 times the corresponding estimate for the US. Our second major result is that, in many poor countries, that cost may in fact exceed the welfare cost of significantly lower growth.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.044
GPT teacher head0.220
Teacher spread0.176 · 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