Trends, Peaks, and Troughs: National and Regional Employment Cycles in Canada
Notice bibliographique
Résumé
When the 2008 global recession hit Canada and national unemployment rates began to rise, the federal government soon found itself under pressure to do something to help. That something ended up being the Economic Action Plan, a multi-billion-dollar spending initiative spread across the country. But, in at least one part of the country, no help was really needed at all. In New Brunswick, the recession had barely any impact on the state of the job market. Federal spending there would have been at best, unnecessary or, at worst, harmful, crowding out private investment while having an inflationary effect on the regional economy. Unfortunately, any informed assessment of how much stimulus is required in each province requires many months of data. Governments, impatient to show they are taking action, hastily create plans that may cause them to spend needlessly — or even harmfully — in some provinces while possibly coming up short in provinces facing the deepest economic crisis. In this report we show this problem is not unique to the most recent recession. Our analysis uses monthly data on labour market conditions to show that the timing and depth of employment recessions varies widely across provinces and that this has been so in every recession since 1976. These results suggest that, to be effective, spending “action plans” and tax cuts must be targeted to benefit only certain regions of the country at certain times. The time it takes to formulate such targeted responses, and the obvious political challenges they involve, beggars the question of whether a national strategy can ever be designed that takes into account the varying economic conditions of a country with such a wide variety of industries and economic variables. Examinations of the role played by governments in alleviating the recent recessions in Canada, the United States and elsewhere have emphasized the importance of relying instead on “automatic stabilizers” — pre-established mechanisms such as employment insurance, social assistance, and prescribed tax adjustments — to alleviate the impact of recessions. Before the next recession comes, the federal government — and provincial governments as well — would be wiser to prepare by investing resources in legislating well-designed automatic stabilizers so these processes are in place to naturally kick in precisely where and when they are needed. With the right formula of automatic stabilizers responding quickly and precisely to economic contractions, the main job left for politicians would be persuading the public that resorting to action plans and national strategies is something we are better off avoiding.
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.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 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 ».