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Record W3145106468

Macroeconomic Effects of Oil Price Fluctuations in Colombia

2016· article· es· W3145106468 on OpenAlexaboutno aff
Leonardo Quero-Virla

Bibliographic record

VenueDocumentos de Trabajo CIEF · 2016
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsOil priceQuarter (Canadian coin)EconomicsInflation (cosmology)EconometricsUnemploymentVector autoregressionImpulse responseMonetary economicsMathematicsMacroeconomicsGeographyPhysics
DOInot available

Abstract

fetched live from OpenAlex

This research aims to study the effects of oil price changes on the Colombian economy during 2001:Q1 to 2016:Q2. A structural vector auto-regression model in the spirit of Blanchard and Galí (2010) is estimated under a recursive identification scheme, where unexpected oil price variations are exogenous relative to the contemporaneous values of the remaining variables. Drawing on impulse-response estimates, a 10% increase in the oil price generates the following accumulated orthogonalized responses: i) a contemporaneous 0.4% increase in GDP growth, later on the effect reaches its maximum in the first quarter (1.7% increase) and starts to decay after two quarters; ii) a contemporaneous 1.2% decrease in unemployment, then the effect remains slightly negative and reaches its maximum after ten quarters (5.1% decrease); iii) a contemporaneous 0.9% decrease in inflation, followed by an 0.2% increase by quarter three, and thereafter the effect remains slightly negative

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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 designSimulation or modeling
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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