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Enregistrement W3125655922 · doi:10.55016/ojs/sppp.v11i1.43144

Business Subsidies in Canada Comprehensive Estimates for the Government of Canada and the Four Largest Provinces

2018· article· en· W3125655922 sur OpenAlexaboutno aff
John Lester

Notice bibliographique

RevueThe School of Public Policy Publications · 2018
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueCanadian Policy and Governance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSubsidyGovernment (linguistics)GeographyBusinessEconomic growthPolitical scienceEconomics

Résumé

récupéré en direct d'OpenAlex

Business subsidies in Canada: the “winner” is Alberta; the loser is the taxpayer The federal government and the four largest provinces in Canada spend about $29 billion a year on business subsidies, delivered through program spending, the tax system, government business enterprises and direct investments by government. These subsidies represent almost half of the corporate income tax revenue collected by the five jurisdictions. Surprisingly, given its reputation as a bastion of free enterprise, Alberta is the most prolific subsidizer. In the 2014-15 fiscal year, per person subsidies were $640 in Alberta, about $100 ahead of the next most generous jurisdiction, Québec. Alberta has probably added to its “lead” through measures introduced in the October 2015 Fiscal Update and the 2016 budget. Alberta also stands out by having the least transparent public reporting of business subsidies. What motivates governments to subsidize business? Abstracting from cynical efforts to win votes, business subsidies have two broad objectives: to improve economic performance and to achieve a social objective by supporting specific firms, industries or regions. On average in the five jurisdictions, the split between the two categories is about 70-30 in favour of economic development measures. Assessing value for money from programs with a social objective is subjective, but measures intended to improve economic performance should be assessed on their ability to raise real income. Business subsidies can only raise real income if markets fail to allocate labour and capital to their best uses. The classic case is R&D. When a firm undertakes R&D, some of the knowledge created inevitably spills over to the benefit other firms. Firms are focused on their own benefits and costs when deciding how much to spend on R&D, not the benefits received by other firms, so society has an interest in encouraging additional R&D. While markets generally do a good job allocating capital to its most productive uses, governments express concern about the ability of small firms to access external financing. Just over half of business subsidies are intended to address these two issues. Governments also provide subsidies in order to create what are often described as “good jobs,” meaning employment in high-wage, high-productivity industries. There is ample evidence that wages differ by sector even after differences in worker skills and working conditions are taken into account. That opens up the possibility that subsidizing high-wage jobs will make us better off. Almost 10 per cent of government subsidies are pursuing “industrial policy” objectives. But real income won't necessarily go up, even in these circumstances. Benefit-cost analyses of key programs suggest that, at best, only a third of subsidies intended to raise real income achieve their objective. The main reason these subsidies are unsuccessful is that they have to be funded, either by raising taxes or cutting program spending, both of which harm economic performance. And avoiding the pitfall of excessive subsidization can be challenging. For example, small firms performing R&D get about 43% of their funding from governments, which is substantially beyond an effective level. Industrial policy measures are particularly tricky to get right. Governments have to identify sectors and firms that pay a premium for a given set of skills and working conditions, determine the subsidy that generates a social benefit net of the costs of providing assistance and avoid transferring income from low to high-wage taxpayers. With so much money at play, business subsidies should be reported more transparently and managed more effectively. For greater transparency, governments should prepare a comprehensive annual report on business subsidies delivered through program spending, the tax system and through the activities of government business enterprises. The report would describe the programs, state their objectives and report funding levels. When discussing program objectives, the report should set out in general terms the expected benefits and costs of government intervention and discuss who benefits from the measure and who is expected to pay for it. Making a commitment to set out the expected benefits and costs of all new business subsidies as they are introduced might prevent the worst offenders from being implemented in the first place.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,007
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,871
Score d'incertitude au seuil0,980

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,031
Tête enseignante GPT0,276
Écart entre enseignants0,246 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations3
Publié2018
Routes d'admission1
Résumé présentoui

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