Cars, Congestion and Costs: A New Approach to Evaluating Government Infrastructure Investment
Notice bibliographique
Résumé
The existing debate about the cost of traffic congestion in Canadian cities has been limited to estimating the value of time lost by people sitting in traffic. However, there are broader costs of congestion that should be taken into account. This Commentary offers a decision-making framework for governments seeking to include these broader, social welfare costs in selecting which infrastructure investments merit public subsidy, and which ones should be handled by the private sector. In general, the social returns from infrastructure can be substantial and governments are missing a large portion of the economic benefits of infrastructure when they do not estimate them. In particular, economic externalities – which arise when an individual’s use of infrastructure affects someone else – can be quite large. Governments should assess the full range of social costs and benefits of externalities and include them in building a consistent economic case for investment. With regard to transportation in particular, this report provides a new way of estimating the cost of congestion. To date, governments have made the case for transportation investment based on the estimated economic cost of time lost due to congestion. In the Greater Toronto and Hamilton Area, the commonly used estimate is that congestion costs the economy about $6 billion per year. However, the existing studies provide underestimates of the costs of congestion. The reason: they ignore the positive effects of relationships among firms and people that are among the main benefits of urban living. These urban agglomeration benefits range from people accessing jobs that better match their skills, sharing knowledge face-to-face, and creating demand for more business, entertainment and cultural opportunities which, in turn, benefit other people. When congestion makes urban interactions too costly to pursue, these benefits are foregone, adding significantly to the net costs of congestion. For the Greater Toronto and Hamilton Area this report estimates the additional costs to be at least $1.5 billion and as much as $5 billion per year. For Canadian governments, the framework for comparing the private and social returns of investments can apply to a wide range of investments, ranging from transportation to education to health and much more. In cases in which there is a substantial private return, the economically efficient option is for pure private provision. With such a framework in hand, Canadian governments can make better choices about their investment needs.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 source (Gemma direct ou Codex distillé), 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 ».