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Record W1544072652

Real Business Cycles with Capital Maintenance

2011· preprint· en· W1544072652 on OpenAlexaboutno aff
Alice Albonico, Sarantis Kalyvitis, Evi Pappa

Bibliographic record

VenueEconstor (Econstor) · 2011
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
FundersMinisterio de Ciencia e InnovaciónUniversità degli Studi di PaviaAthens University of Economics and Business
KeywordsDepreciation (economics)EconomicsCapital (architecture)EconometricsBusiness cycleMonetary economicsIdentification (biology)Bayesian probabilityEstimationMicroeconomicsCapital formationMacroeconomicsStatisticsFinancial capitalMathematics
DOInot available

Abstract

fetched live from OpenAlex

We develop a stochastic general equilibrium model in which maintenance endogenously affects the capital depreciation rate. The model performs well in generating maintenance series that match closely existing survey-based measures for Canada. Maintenance is procyclical and comoves almost always with output. Investmentspecific shocks are the only disturbances that induce a negative correlation between output and maintenance. This feature is crucial for the identification of such shocks in the short run. We use Bayesian estimation to obtain the time profile of equipment capital depreciation in Canadian manufacturing. The depreciation rate has been quite volatile and procyclical over the last 50 years.

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)0.007
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.043
GPT teacher head0.213
Teacher spread0.169 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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