MétaCan
Menu
Back to cohort
Record W2341928985 · doi:10.15353/rea.v8i1.1431

Business Cycle Dynamics of Economic Growth in the OECD Countries: Evidence from Markov-Switching Model

2016· article· en· W2341928985 on OpenAlexvenueaboutno aff
Tarlok Singh

Bibliographic record

VenueReview of Economic Analysis · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsStylized factEconomicsBusiness cycleRecessionInflation (cosmology)Monetary economicsNew Keynesian economicsMacroeconomicsMonetary policyStabilization policyFiscal policyKeynesian economics

Abstract

fetched live from OpenAlex

This study estimates the Markov-switching model and examines the Keynesian business cycle dynamics ofeconomic growth for a comprehensive set of eight OECD countries. The estimated duration of regime one is (i)shorter for Denmark, Sweden and Switzerland, (ii) moderate for France and (iii) longer for Belgium, Spain andthe U.S. The persistence of regime two is observed to be (i) shorter for Belgium, Canada, Spain, Sweden andthe U.S., (ii) moderate for Denmark and France, and (iii) longer for Switzerland. The stylized evidence for thepersistence of a given state has important implications for Keynesian policy activism and the formulation ofmacroeconomic stabilization policies. The monetary and fiscal policies are used to reduce the amplitudes andtime-durations of the economic growth cycles and, thus, stabilise the output around its long-run natural ratelevel and the inflation around its target level. The short-run downward rigidities in prices in the goods marketsand in nominal wages in the factor markets tend to impinge upon the clearance of markets and the accelerationof economic growth during recessions, thereby leading to the pathologically longer durations of lower regimes.While the longer durations of upper regimes support the sustainability of the expansionary economic policies,the adequate precautions need to be taken for the inflationary implications of these policies.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.046
GPT teacher head0.260
Teacher spread0.215 · 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 teacher head, not a consensus.

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
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueReview of Economic AnalysisSame topicMonetary Policy and Economic ImpactFrench-language works237,207