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Enregistrement W2733086276 · doi:10.55016/ojs/sppp.v10i1.42626

Policy Interventions Favouring Small Business: Rationales, Results and Recommendations

2017· article· en· W2733086276 sur OpenAlexaffabout
John Lester

Notice bibliographique

RevueThe School of Public Policy Publications · 2017
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueEconomic Growth and Productivity
Établissements canadiensUniversity of Calgary
Organismes subventionnairesAustralian Government
Mots-clésPsychological interventionBusinessPublic economicsEconomicsMedicineNursing

Résumé

récupéré en direct d'OpenAlex

Small business has a well-deserved reputation as the driver of job growth and as a key contributor to innovation. In the 12 years ending in 2013, small and medium-sized enterprises (SMEs) accounted for about 90% of private sector job growth in Canada. What is less well-recognized, however, is that a small fraction of SMEs account for most of the job growth and innovation. As a result, governments have offered broad-based support for small businesses, rather than focusing on high-impact entrepreneurs. This approach is wasteful: firms that do not grow or innovate receive most of the benefits. Further, this approach can harm economic performance by promoting the expansion of smaller, lessefficient firms at the expense of larger ones. The federal government elected in 2015 is focussing new initiatives on innovative and growth-oriented businesses. Legislated reductions in the small business tax rate were reversed and targeted support for innovative SMEs was increased. While the change in direction is welcome, almost 85% of the $7 billion yearly funding for small business continues to provide broad-based support. The largest program is the special low rate of tax for small businesses, implemented to improve access to financing for capacity-expanding investment. This measure is harming economic performance because the cost of shifting capital and labour from large to smaller, less-efficient businesses outweighs the benefit from improving access to capital. Large subsidies for small business financing are also provided by the Business Development Bank of Canada (BDC). With access to cheap government funding, the BDC is profitable, but evaluated using a more realistic cost of financing, the bank operates at a substantial loss. This loss exceeds the benefit from improving access to capital, particularly for the bank’s direct-lending program. While there is a solid argument for supporting R&D, subsidies provided to small firms are so generous that they are harming economic performance. The federal government provides a 35% tax credit for R&D performed by small firms. Provincial tax credits raise the subsidy rate to about 42%. And those firms receiving support from the federal Industrial Research Assistance Program can have almost 60% of their project costs paid by the government. By way of contrast, large firms performing R&D receive subsidies from federal and provincial tax credits amounting to under a quarter of their costs, an intervention which improves economic performance. Canada has had what could be described as a small business policy – broad-based support for all small businesses. The newish federal government is moving to an entrepreneurship policy: new initiatives emphasize support for the high-impact firms and individuals that make an outsized contribution to Canada’s innovation and prosperity. Making the transition to the new framework will require overhauling legacy small business policies to free up resources for new initiatives and to secure fiscal savings. Three changes would pay big dividends: • Eliminate the small-business corporate income tax deduction. • Reduce the enhanced R&D tax credit rate to the same level as the regular credit. • Replace the BDC’s direct loan program with a loan guarantee program.

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)0,002
score de la tête « metaresearch » (Gemma)0,017
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
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 enseignants0,941
Score d'incertitude au seuil0,992

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,017
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,002
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 Opus0,149
Tête enseignante GPT0,316
Écart entre enseignants0,167 · 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.

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

Citations6
Publié2017
Routes d'admission2
Résumé présentoui

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