A cost-benefit analysis of tunnel investment and tolling alternatives in Antwerp
Notice bibliographique
Résumé
This paper presents and illustrates a comprehensive and operational model for assessing transport pricing and investment policies and regulatory regimes. The approach encompasses intra-modal as well as inter-modal competition, and could be used either by private operators or by the legislator for the purpose of evaluating market conduct. The model combines elements of contract theory, public economics, political economy, transportation economics and game theory. It incorporates a CES-based discrete-choice framework in which user charges and infrastructure investments are endogenously determined for two competing alternatives (air, rail or two parallel roads) that may be used for transportation of passengers and/or freight. The model includes separate modules for demand, supply, equilibrium and the regulatory framework. The demand module for passenger transport features a CES decision tree with three levels: choice between transport and consumption of a composite commodity, choice between peak and off-peak periods, and choice between the two transport alternatives. Elasticities of substitution at each level are parametrically given. Passengers can be segmented into classes that differ with respect to their travel preferences, incomes and costs of travel time. The demand module for freight transport also features three levels. The first level encompasses choice between transport and other production inputs, and the second and third levels are the same as for passenger transport. Freight transport can be segmented into local and transit traffic. The supply module specifies for each transport alternative travel time as a function of traffic volume and a rule for infrastructure maintenance. Operating, maintenance and investment costs are allowed to depend on the contractual form. Given the demand and supply functions, the equilibrium module computes a fixed-point solution in terms of prices and levels of congestion. Finally, the exogenous regulatory framework stipulates for each alternative the objective functions of the operators and infrastructure managers (public or private objectives), the nature of competition, procurement policies, the cost of capital, and the source and use of transport tax revenues. Possible market structures include: no tolls (free access), exogenous tolls, marginal social cost pricing, private duopoly and mixed oligopoly. Public decisions can be made either by local or central governments that may attach different welfare-distributional weights to agents (e.g. low-income vs. high-income passengers, or local vs. transit freight traffic) as well as different weights to air pollution and other (non-congestion) external transport costs. Primary outputs from the model are equilibrium prices, transport volumes, travel times, cost efficiency of operations, toll revenues and financial balances, travellers' surplus and social welfare. In the final section of the paper the methodology is illustrated with an example of competition in the market for long-distance passenger travel between high-speed rail and air. A simple procedure allows the calibration of the parameters when aggregate data are available. The model is used to evaluate policies (pricing, investment, taxes, inter alia).
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».