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International business cycles and the relative price of investment goods

2011· article· en· W1557881391 on OpenAlexvenueno aff
Parantap Basu, Christoph Thoenissen

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsRelative priceEconomicsInvestment (military)Investment goodsTotal factor productivityShock (circulatory)Monetary economicsWelfare economicsProductivityProduction (economics)Macroeconomics

Abstract

fetched live from OpenAlex

Abstract Is the relative price of investment goods a good proxy for investment specific technology? We model this relative price in a flexible price international economy with two fundamental shocks, namely, the total factor productivity (TFP) shock and the investment-specific technology (IST) shock. We show that the one-to-one correspondence between the IST shock and the relative price of investment goods breaks down in an international economy because of the short-run correlation between the terms of trade and the relative price of investment goods. The data congruent negative correlation between the investment rate and the relative price of investment goods thus does not necessarily reflect decline in investment frictions (rise in IST), as suggested by many studies. A calibration experiment with the US data demonstrates that such an inverse relation between rate of investment and the relative price of investment goods basically reflects the positive effect of TFP on the terms of trade for a broad range of economies where the home bias in consumption exceeds investment and there is a sizable adjustment cost of investment.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.209
GPT teacher head0.184
Teacher spread0.026 · 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 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

Citations17
Published2011
Admission routes1
Has abstractyes

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