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Record W2412874037 · doi:10.1111/caje.12510

Large and influential: Firm size and governments’ corporate tax rate choice

2021· article· en· W2412874037 on OpenAlexvenueno aff
Nadine Riedel, Martin Simmler

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsJurisdictionDistribution (mathematics)BusinessVariation (astronomy)Industrial organizationPublic economicsTax policyEconomicsTax reformPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract Theory suggests that large firms are more likely to engage in lobbying behaviour and are geographically more mobile compared with smaller entities. Conditional on jurisdiction size, policy choices are thus predicted to depend on the shape of a jurisdiction's firm size distribution, with more business‐oriented policies being enacted if jurisdictions host large firms. The paper empirically tests this prediction using local business taxation in Germany as a testing ground. Exploiting rich and exogenous variation in municipalities’ firm size structures, we find evidence for an inverse relationship between the size of hosted entities and municipalities’ local business tax choices. The effect is statistically significant and quantitatively relevant, suggesting that the rising importance of large businesses may trigger shifts towards a more business‐friendly design of (tax) 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 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)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.080
GPT teacher head0.174
Teacher spread0.094 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Economics/Revue canadienne d économiqueSame topicCorporate Taxation and AvoidanceFrench-language works237,207