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Enregistrement W4402288227 · doi:10.55016/ojs/sppp.v10i1.42621

Who Pays the Corporate Tax? Insights from the Literature and Evidence for Canadian Provinces

2017· article· en· W4402288227 sur OpenAlexaffabout
Kenneth J. McKenzie, Ergete Ferede

Notice bibliographique

RevueThe School of Public Policy Publications · 2017
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueCorporate Taxation and Avoidance
Établissements canadiensMacEwan UniversityUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésCorporate taxBusinessAccountingEconomicsValue-added taxTax avoidancePublic economics

Résumé

récupéré en direct d'OpenAlex

Who bears the burden, or incidence, of the corporate income tax (CIT)? This is an important, if not somewhat contentious, policy issue. In this paper we provide a discussion of the existing research on the question, viewing it through a Canadian policy lens. We also use some new results from a companion technical paper, which undertakes one of the few empirical investigations of the issue using Canadian data, to discuss the implications of increases in corporate taxes for wages in Canadian provinces. While it is clear that people, not corporate entities, ultimately bear the burden of corporate taxes, a key question is which people? The answer to this question has important implications for the equity, or fairness, of the tax system. Much of the recent focus in policy discussions concerns the allocation of the burden of the CIT between owners of capital and labour. Since income from capital tends to be concentrated with wealthier individuals, if the burden of the CIT falls mostly on the owners of capital, it increases the progressivity of the tax system. On the other hand, if the tax is borne mostly by labour through lower wages, the CIT is less progressive. Much of the research into the incidence of the CIT has employed theoretical simulation models. Early models of this type, which were based on a closed economy with fixed supplies of labour and capital, suggested that most of the burden of the CIT would be borne by the owners of capital throughout the economy, and not just the shareholders of firms in the corporate sector. Subsequent extensions of those models into a small open economy setting, where capital and goods are highly mobile between jurisdictions (countries, provinces), predict that most of the burden of the CIT will be borne by other inputs that are relatively inelastic in supply, such as labour. These small open economy models are particularly relevant for Canada. Viewing the results of these models through a Canadian lens, we conclude that there is good reason to expect that much of the burden of corporate taxes in Canada, particularly those levied by provincial governments, will fall on labour through lower wages. While useful, the predictions of these simulation models should be viewed with caution, largely because of the sensitivity of the results to the underlying assumptions. A nascent empirical literature has emerged that provides econometric-based estimates of the distribution of the burden of corporate taxes. While this research is relatively new, our reading is that the evidence is mounting that corporate taxes are indeed borne to a significant extent by labour through lower wages. However, there is very little empirical work done in an explicitly Canadian context. In a companion technical paper we employ Canadian data to examine the impact of provincial corporate taxes on wages. Our results suggest that, consistent with the predictions of the open economy simulation models, provincial corporate taxes adversely affect the capital/labour ratio, which lowers the productivity of labour which, in turn, lowers wages. Accounting for the shrinkage in the corporate tax base in response to an increase in the tax rate, we calculate that for every $1 in extra tax revenue generated by an increase in the provincial CIT rate, the associated long-run decrease in aggregate wages ranges from $1.52 for Alberta to $3.85 for Prince Edward Island. Applying our estimates to the recent 2 percentage point increase in the CIT rate in Alberta we calculate that labour earnings for an average two-earner household will decline by the equivalent of approximately $830 per year, which amounts to a $1.12 billion reduction in aggregate labour earnings for the province. By way of comparison, other research has estimated the impact of the recently imposed carbon tax in Alberta – the subject of considerable scrutiny – to be approximately $525 per household.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,027
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,162
Score d'incertitude au seuil0,973

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,027
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0080,024
Études des sciences et des technologies0,0090,004
Communication savante0,0060,002
Science ouverte0,0030,002
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0100,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,093
Tête enseignante GPT0,292
Écart entre enseignants0,199 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission2
Résumé présentoui

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