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Record W2900821528

Does Political Competition affect Fiscal Structure? What time series analysis says for Canada, 1870 - 2015

2017· article· en· W2900821528 on OpenAlexaboutno aff
J. Stephen Ferris, Stanley L. Winer

Bibliographic record

VenueCarleton University's Institutional Repository (MacOdrum Library, Carleton University) · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsPoliticsBusiness cycleCompetition (biology)Volatility (finance)Optimal distinctiveness theoryMonetary economicsFiscal policyCorporate governanceMacroeconomicsFinancePolitical science
DOInot available

Abstract

fetched live from OpenAlex

This paper asks whether political competition has played a role in moderating the governance issues that arise in relation to Canada’s fiscal structure. By fiscal structure we mean three distinct but interrelated fiscal dimensions of the state: financial stability, long run size and short run interventions into the private economy, particularly with respect to the business cycle. The distinctiveness of this paper is that it focuses on four different measures of the degree of political competition: the size of the seat majority of the governing party in the House; the distribution of the volatility adjusted winning margins of the governing party; the proportion of electorally marginal constituencies adjusted for asymmetry; and the Przeworski-Sprague measure of electoral competitiveness at the constituency level. The analysis accounts for the differing time series properties of the political and economic variables and the comingling of long and short term fiscal policies in the time series data while finding support for the hypotheses that greater political competition will enhance fiscal stability (maintain a non-accelerating debt to GDP ratio), that government size will converge from above on economic and structural fundamentals and that period deficits/surpluses will align better with the business cycle. The potential impact of greater political competition is analyzed by applying the deficit model to the period of fiscal instability that arose in the 198

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.005
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.176
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 teacher head, not a consensus.

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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCarleton University's Institutional Repository (MacOdrum Library, Carleton University)Same topicFiscal Policies and Political EconomyFrench-language works237,207