MétaCan
Menu
Back to cohort
Record W3125318500

Political Competition and Convergence to Fundamentals: With Application to the Political Business Cycle and the Size of Government

2006· preprint· en· W3125318500 on OpenAlexaboutno aff
J. Stephen Ferris, Soo‐Bin Park, Stanley L. Winer

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsCompetition (biology)EconomicsConvergence (economics)Government (linguistics)Business cycleContext (archaeology)Public policyPublic choicePublic economicsPolitical scienceMacroeconomicsEconomic growthLaw
DOInot available

Abstract

fetched live from OpenAlex

We address the problem of how to investigate whether economics, or politics, or both, matter
\nin the explanation of public policy. The problem is first posed in a particular context by
\nuncovering a political business cycle (using Canadian data for 130 years) and by taking up the
\nchallenge to make this fact meaningful by finding a transmission mechanism through actual
\npublic choices. Since the cycle is in real growth, and it is reasonable to suppose that public
\nexpenditure would be involved, the central task then is to investigate the role of (partisan and
\nopportunistic) political factors, as opposed to economic fundamentals, in the evolution of
\ngovernment size.
\nWe proceed by asking whether the data allow us to distinguish between the convergence and
\nthe nonconvergence hypotheses. Convergence means that political competition forces public
\nspending to converge in the long run to a level dictated by endowments, tastes and
\ntechnology. Nonconvergence is taken to mean that political factors other than the degree of
\npolitical competition prevent convergence to that long run. The general idea here, one that
\nmay be applied in any situation where the key issue is the role of economics versus politics
\nover time, is that an overtly political factor can be said to play a distinct role in the evolution
\nof public choices if it can be shown to lead to departures from a dynamic path defined by the
\nevolution of economic fundamentals in a competitive political system.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.738

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations21
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicFiscal Policy and Economic GrowthFrench-language works237,207