Surge pricing on a service platform under spatial spillovers: evidence from Uber

Ride-sharing platforms employ surge pricing to match anticipated capacity spillover with demand. We develop an optimization model to characterize the relationship between surge price and spillover. We test predicted relationships using a spatial panel model on a dataset from Ubers operation. Results reveal that Ubers pricing accounts for both capacity and price spillover. There is a debate in the management community on the ecacy of labor welfare mechanisms associated with shared capacity. We conduct counterfactual analysis to provide guidance in regards to the debate, for managing congestion, while accounting for consumer and labor welfare through this online platform.First author draf

Charging the polluters: A pricing model for road and railway noise

This study outlines a method to estimate the short run marginal cost (SRMC) for road and railway noise. It is based on standardized calculation methods for total noise levels and monetary cost estimates from well established evaluation methods. Here official calculation methods and monetary values are used for Sweden, but the estimation method for the SRMC outlined can be directly applied using other standardized noise calculation methods and monetary values. This implies that the current knowledge regarding the calculation of total noise levels and the evaluation of the social cost of noise can be extended to estimate the marginal effect as well. This is an important finding since it enables policy makers to price noise externalities in an appropriate way. Several sensitivity tests run for the SRMC show that: (i) increasing the total traffic on the infrastructure has only a minor influence, (ii) estimates are quite sensitive to the number of exposed individuals, and (iii) to the monetary values used. Hence, benefits transfer, i.e. using monetary values elicited based on road noise for railway noise, should be done with caution or not at all. Results also show that the use of quiet technology can have a significant effect on the SRMC. The fact that this model is able to differentiate not only modes of transport, but also vehicles and even technologies is an important finding. It is essential that the noise charges give the operators the right incentives to choose their optimal allocation.Externalities; Marginal cost; Noise; Railway; Road

A cost-benefit analysis of tunnel investment and tolling alternatives in Antwerp

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).

Capacity and Price Competition in Markets with Congestion Effects

We study oligopolistic competition in service markets where firms offer a service to customers. The service quality of a firm - from the perspective of a customer - depends on the congestion and the charged price. A firm can set a price for the service offered and additionally decides on the service capacity in order to mitigate congestion. The total profit of a firm is derived from the gained revenue minus the capacity investment cost. Firms simultaneously set capacities and prices in order to maximize their profit and customers subsequently choose the services with lowest combined cost (congestion and price). For this basic model, Johari et al. (2010) derived the first existence and uniqueness results of pure Nash equilibria (PNE) assuming mild conditions on congestion functions. Their existence proof relies on Kakutani's fixed-point theorem and a key assumption for the theorem to work is that demand for service is elastic (modeled by a smooth and strictly decreasing inverse demand function). In this paper, we consider the case of perfectly inelastic demand, i.e. there is a fixed volume of customers requesting service. This scenario applies to realistic cases where customers are not willing to drop out of the market, e.g. if prices are regulated by reasonable price caps. We investigate existence, uniqueness and quality of PNE for models with inelastic demand and price caps. We show that for linear congestion cost functions, there exists a PNE. This result requires a completely new proof approach compared to previous approaches, since the best response correspondences of firms may be empty, thus standard fixed-point arguments are not directly applicable. We show that the game is C-secure (see McLennan et al. (2011)), which leads to the existence of PNE. We furthermore show that the PNE is unique, and that the efficiency compared to a social optimum is unbounded in general.Comment: A one-page abstract of this paper appeared in the proceedings of the 15th International Conference on Web and Internet Economics (WINE 2019

Infrastructure Topology Optimization under Competition through Cross-Entropy

International audienceIn this article, we study a two-level non-cooperative game between providers acting on the same geographic area. Each provider has the opportunity to set up a network of stations so as to capture as many consumers as possible. Its deployment being costly, the provider has to optimize both the number of settled stations as well as their locations. In the first level each provider optimizes independently his infrastructure topology while in the second level they price dynamically the access to their network of stations. The consumers' choices depend on the perception (in term of price, congestion and distances to the nearest stations) that they have of the service proposed by each provider. Each provider market share is then obtained as the solution of a fixed point equation since the congestion level is supposed to depend on the market share of the provider which increases with the number of consumers choosing the same provider. We prove that the two-stage game admits a unique equilibrium in price at any time instant. An algorithm based on the cross-entropy method is proposed to optimize the providers' infrastructure topology and it is tested on numerical examples providing economic interpretations

Optimal Carbon Taxes for Emissions Targets in the Electricity Sector

The most dangerous effects of anthropogenic climate change can be mitigated by using emissions taxes or other regulatory interventions to reduce greenhouse gas (GHG) emissions. This paper takes a regulatory viewpoint and describes the Weighted Sum Bisection method to determine the lowest emission tax rate that can reduce the anticipated emissions of the power sector below a prescribed, regulatorily-defined target. This bi-level method accounts for a variety of operating conditions via stochastic programming and remains computationally tractable for realistically large planning test systems, even when binary commitment decisions and multi-period constraints on conventional generators are considered. Case studies on a modified ISO New England test system demonstrate that this method reliably finds the minimum tax rate that meets emissions targets. In addition, it investigates the relationship between system investments and the tax-setting process. Introducing GHG emissions taxes increases the value proposition for investment in new cleaner generation, transmission, and energy efficiency; conversely, investing in these technologies reduces the tax rate required to reach a given emissions target

Separation and Volatility of Locational Marginal Prices in Restructured Wholesale Power Markets

This study uses an agent-based test bed ("AMES") to investigate separation and volatility of locational marginal prices (LMPs) in an ISO-managed restructured wholesale power market operating over an AC transmission grid. Particular attention is focused on the dynamic and cross-sectional response of LMPs to systematic changes in demand-bid price sensitivities and supply-offer price cap levels under varied learning specifications for the generation companies. Also explored is the extent to which the supply offers of the marginal (price-determining) generation companies induce correlations among neighboring LMPs. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htmRestructured wholesale power markets; multi-agent learning; demand-bid price sensitivity; AMES Wholesale Power Market Test Bed; agent-based modeling; locational marginal prices (LMPs); LMP separation; LMP volatility; supply-offer price caps