An International Comparison of Tax Assistance for Research and Development: Estimates and Policy Implication
Notice bibliographique
Résumé
Business spending on research and development (R&D) is generally recognized as a private activity providing broader economic benefits that justify government support. But subsidizing R&D has costs as well as benefits, and governments need to exercise judgement to ensure that subsidies are set at a level that results in a net economic benefit for society as a whole, not just for the recipients of the assistance. A key finding of the international comparison undertaken in this paper is that Canada and nine other of the 36 countries in the comparison group are providing R&D subsidies that are likely too high to generate a net economic benefit. Subsidy rates in this group of countries range from 25 to 45 per cent. The risk of excessive subsidization is confined to small firms in Canada, which receive a subsidy of almost 41 per cent through the tax system. Canada’s subsidy rate for small firms is the third highest, behind Chile and France. Other countries providing subsidy rates close to 40 per cent are Spain and India. This paper also assesses several design features of tax assistance measures, including enhanced benefits for small and young firms, refundability of benefits and incentives based on increases in R&D spending above a base level. While the best policy for R&D subsidies may be a uniform rate for all businesses regardless of age or size, the case for favouring young firms is somewhat stronger than for favouring all small firms. Focusing on young firms avoids providing benefits to small firms that are not growth-oriented; but, it is difficult to design a program that can be completely restricted to young firms since entrepreneurs would have an incentive to create new firms to avoid losing higher benefits. Even with this “leakage”, however, an age-dependent incentive could be more cost-effective than size-dependent enhanced benefits. There is a particularly strong case for providing refundability to young firms, which are unlikely to have taxable income while the first round of R&D is undertaken While refundability for large firms has the advantage of increasing the effective subsidy rate on R&D to its target level, it runs the risk of revenue losses as multinational firms have less incentive to ‘book’ taxable income in Canada. A reasonable compromise would be to adjust the value of unused credits and deductions to maintain their present value. International comparisons of tax assistance for R&D typically highlight country rankings and express satisfaction with the most generous regimes. This paper draws attention to the possibility of providing too much of a good thing, a warning that governments in Canada should keep in mind when preparing next year’s budgets.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».