Congestion Externalities Research Articles

The Impact of the U.S. Shale Boom on Agriculture: Evidence from North Dakota

Shale energy exploitation often occurs in rural areas. While agriculture dominates surface land use in these regions, energy development competes for inputs such as water and labor, and localized congestion externalities can create bottlenecks in transporting agricultural output. Additionally, well spacing, rights-of-way and chemical spillage potentially decrease the returns to surface land as greater numbers of oil wells are drilled. This study examines the impact of shale drilling on agriculture by estimating parcel rent differences as a function of energy industry activity for over 17,000 land rental transactions using State Trust Lands data from North Dakota. I find that, despite anecdotal evidence that the above-mentioned processes threaten farm profitability, surface renters in North Dakota do not significantly decrease their willingness to pay for parcels with nearby oil activity relative to parcels with no activity in the vicinity.

The Economics of Line-Sitting

This paper studies an emerging business model of line-sitting in which customers seeking service can hire others (line-sitters) to wait in line on behalf of them. We develop a queueing-game-theoretic model that captures the interaction among customers, the line-sitting firm, and the service provider to examine the impact of line-sitting on the service provider's revenue and customer welfare. We also contrast line-sitting with the well-known priority purchasing scheme as both allow customers to pay extra to skip the wait. Our main results are as follows. First, we find that both accommodating line-sitting and selling priority can bring in extra revenue for the service provider, although by different means---selling priority increases revenue mainly by allowing the service provider to practice price discrimination that extracts more customer surplus, whereas line-sitting does so through demand expansion, attracting customers who would not otherwise join. Second, the priority purchasing scheme tends to make the customer population worse off while line-sitting can be a win-win proposition for both the service provider and the customers. Nevertheless, having the additional option of hiring line-sitters does not always benefit customers as a whole because the demand expansion effect also induces negative congestion externalities. Finally, despite the fact that the service provider collects the priority payment as revenue but not the line-sitting payment, which accrues to the third-party line-sitting firm, we demonstrate that, somewhat surprisingly, accommodating line-sitting can raise more revenue for the service provider than directly selling priority.

Population Shifts and Discrete Public Services: Rationing Rules and the Support for Public Goods

Cities with declining populations face increasing per-capita costs to maintain discrete public goods—those with fixed costs that cannot be easily scaled to demand. Likewise, growing cities may face decreasing benefits from congestible public goods. In either case, there are two policy actions: limit access (ration) or expand output (higher revenues per person required). We report the results of a series of experiments designed to investigate the effect of alternative rationing rules on the propensity for individuals to support increases in taxes to overcome congestion externalities or decreases in the tax base.

The Double Bind of Asymmetric Information in Over-the-Counter Markets

In over-the-counter markets with heterogeneous asset qualities and individual valuations, private information about both of these value components amplifies the adverse selection problem attributable only to privately known asset quality. Specifically, when gains from trade are low, asymmetric information creates a double bind: either the market breaks down due to a classic lemons problem or low-quality assets are traded excessively, generating a congestion externality. A market designer may improve efficiency without incurring losses by acquiring all assets, issuing asset-backed securities of publicly known quality and capturing at least a part of the surplus from the future trades of these securities.

Self-Fulfilling Signal of an Endogenous State in Network Congestion Games

We consider the problem of coordination via signaling in network congestion games to improve social welfare deteriorated by incomplete information about traffic flow. Traditional studies on signaling, which focus on exogenous factors of congestion and ignore congestion externalities, fail to discuss the oscillations of traffic flow. To address this gap, we formulate a problem of designing a coordination signal on endogenous information about traffic flow and introduce a it self-fulfilling characteristic of a signal that guarantees an outcome flow consistent with the signal itself without causing the unwanted oscillation. An instance of the self-fulfilling signal is shown in the case of a Gaussian signal distribution. In addition, we show simple numerical examples. The results reveal how a self-fulfilling signal suppresses the oscillation and simultaneously improves social welfare through improved network efficiency.

Professional Sporting Events and Traffic: Evidence from US Cities

Sporting events concentrate people at specific locations on game day. No empirical evidence currently exists linking sporting events to local traffic conditions. We analyze urban mobility data from 25 US metropolitan areas with MLB teams over the period 1990 to 2014 to assess the relationship between local traffic and Major League Baseball (MLB) games. Instrumental variable regression results indicate MLB attendance causes increases in local vehicle-miles traveled. At the sample average attendance of 2.8 million, average daily vehicle-miles traveled increases by about 6.9% in cities with MLB teams. Traffic congestion increases by 2%, suggesting that MLB games generate congestion externalities.

The external cruising costs of parking

Existing work emphasizes the importance of traffic congestion externalities, but typically ignores cruising-for-parking externalities. We estimate the marginal external cruising costs of parking—that is, the time costs that an additional parked car imposes on drivers by inducing them to cruise for parking—which is one of the main components of cruising-for-parking externalities. The level of cruising is identified by examining to what extent the car inflow rate into a parking location falls with parking occupancy level. For a commercial street in Istanbul, we demonstrate that a marginal car parking for an hour induces 3.6 other cars to cruise for parking. This translates into an external cruising cost that is in the same order of magnitude with the external traffic congestion cost created by the trip.

Teleworking and Congestion: A Dynamic Bottleneck Analysis

We analyze the welfare effects of part-day teleworking on road traffic congestion in the context of Vickrey's dynamic bottleneck model. Endogenous decisions to become equipped with a teleworking-enabling technology change the scheduling of arrival times at work for equipped drivers and, due to congestion externalities, affects travel costs of all drivers. We show that even costless teleworking might be marginally welfare reducing, after reaching the optimal penetration level, as an equipped driver imposes a higher travel externality on other equipped drivers than unequipped drivers do. We study various possible market configurations for the supply of the technology, and find that private monopolistic supply of the technology might yield a higher social welfare than perfectly competitive supply.

The correlation of externalities in marginal cost pricing: lessons learned from a real-world case study

Negative externalities cause inefficiencies in the allocation of capacities and resources in a transport system. Marginal social cost pricing allows to correct for these inefficiencies in a simulation environment and to derive real-world policy recommendations. In this context, it has been shown for analytical models considering more than one externality, that the correlation between the externalities needs to be taken into account. Typically, in order to avoid overpricing, this is performed by introducing correction factors which capture the correlation effect. However, the correlation structure between, say, emission and congestion externalities changes for every congested facility over time of day. This makes it close to impossible to calculate the factors analytically for large-scale systems. Hence, this paper presents a simulation-based approach to calculate and internalize the correct dynamic price levels for both externalities simultaneously. For a real-world case study, it is shown that the iterative calculation of prices based on cost estimates from the literature allows to identify the amplitude of the correlation between the two externalities under consideration: for the urban travelers of the case study, emission toll levels—without pricing congestion—turn out to be 4.0% too high in peak hours and 2.8% too high in off-peak hours. In contrary, congestion toll levels—without pricing emissions—are overestimated by 3.0% in peak hours and by 7.2% in off-peak hours. With a joint pricing policy of both externalities, the paper shows that the approach is capable to determine the amplitude of the necessary correction factors for large-scale systems. It also provides the corrected average toll levels per vehicle kilometer for peak and off-peak hours for the case study under consideration: again, for urban travelers, the correct price level for emission and congestion externalities amounts approximately to 38 $${EUR}ct/\rm {km}$$ in peak hours and to 30 $${EUR}ct/\rm {km}$$ in off-peak hours. These toll levels can be used to derive real-world pricing schemes. Finally, the economic assessment indicators for the joint pricing policy provided in the paper allow to compare other policies to this benchmark state of the transport system.

The Tragedy of the Last Mile: Congestion Externalities in Broadband Networks

We flexibly estimate demand for residential broadband accounting for congestion externalities that arise among consumers due to limited network capacity, as well as dynamics arising from nonlinear pricing. Our high frequency data permits insight into temporal patterns in usage across the day that are impacted by network congestion, and how usage responds to efforts to mitigate congestion. To estimate demand, we build a dynamic model of consumer choice and rely on variation in the timing of network upgrades and nonlinear pricing to identify the model. Using the model estimates, we calculate the welfare changes associated with different economic and technological solutions for reducing congestion, including peak-use pricing, throttling connectivity speeds, and local-cache technologies.

Autonomous cars and dynamic bottleneck congestion: The effects on capacity, value of time and preference heterogeneity

‘Autonomous cars’ are cars that can drive themselves without human control. Autonomous cars can safely drive closer together than cars driven by humans, thereby possibly increasing road capacity. By allowing drivers to perform other activities in the vehicle, they may reduce the value of travel time losses (VOT). We investigate the effects of autonomous cars using a dynamic equilibrium model of congestion that captures three main elements: the resulting increase in capacity, the decrease in the VOT for those who acquire one and the implications of the resulting changes in the heterogeneity of VOTs. We do so for three market organizations: private monopoly, perfect competition and public supply. Even though an increased share of autonomous cars raises average capacity, it may hurt existing autonomous car users as those who switch to an autonomous car will impose increased congestion externalities due to their altered departure time behaviour. Depending on which effect dominates, switching to an autonomous vehicle may impose a net negative or positive externality. Often public supply leads to 100% autonomous cars, but it may be optimal to have a mix of car types, especially when there is a net negative externality. With a positive (negative) externality, perfect competition leads to an undersupply (oversupply) of autonomous cars, and a public supplier needs to subsidise (tax) autonomous cars to maximise welfare. A monopolist supplier ignores the capacity effect and adds a mark-up to its price.

Optimal policies in cities with congestion and agglomeration externalities: Congestion tolls, labor subsidies, and place-based strategies

This paper develops a spatial general equilibrium model that accommodates both congestion and agglomeration externalities, while firms’ and households’ land-use decisions are endogenous across continuous space. Focusing on the interaction between externalities and land use patterns, we examine the efficiencies of first-best policies and second-best pricing and place-based strategies using numerical simulations. A first-best policy must combine both Pigouvian congestion tolling (PCT) and Pigouvian labor subsidies (PLS) instruments, or design an optimal toll (or subsidy) internalizing agglomeration externalities (or congestion externalities). We also examine second-best pricing policies if only one instrument is adopted. Congestion pricing policies alone (e.g., a partial PCT or a flat-rate toll) can improve social welfare only in heavy-congestion cities, and their welfare gains may be insignificant (e.g., below 10% of the welfare improvement achieved by first-best policies). In contrast, second-best labor subsidy policies alone are a more effective alternative to first-best policies. As to place-based policies, the firm cluster zoning (FCZ) regulation is more efficient than the urban growth boundary (UGB) policy. UGBs only have small effects on the agglomeration economy but could worsen land market distortions via residential rent-escalation effects. These findings suggest that it is important to internalize business land use decisions and relax monocentricity assumptions, in order to appreciate the interplay of both urban externalities, since spatial adaptations to policy interventions can distort system efficiencies.

Tradable location tax credit scheme for balancing traffic congestion and environmental externalities

ABSTRACTThis article proposes a novel urban system equilibrium model for design of a tradable location tax credit scheme to balance traffic congestion and environmental externalities. In the proposed model, the interaction between the location tax credit scheme and households' residential location choices is explicitly considered. It is assumed that the authority initially allocates the credits to all households in a uniform way, and the households pay a certain amount of credits for housing consumptions, relying on the traffic congestion and environmental externalities that they cause. The credits are traded among households through a free market, and the tax revenue due to credit trading is considered as a part of household's income to be redistributed through household's income budget constraint. For a given credit scheme, households' residential location choices and housing market structure in terms of housing prices and space can be endogenously determined by the urban system equilibrium and the price per unit of credit is governed by the credit market equilibrium. A social welfare maximization model is presented to determine the total amount of credits issued. The results show that implementation of the tradable location tax credit scheme can rationalize the urban residential density and promote the efficiency of the urban system in terms of social welfare.

Profit maximization by a private toll road with cars and trucks

This paper examines the profit maximizing behavior of a private firm which operates a toll road competing against a free alternative in presence of cars and trucks. Trucks differ from cars in value of time (VOT), congestion externality, pavement damage, and link travel time function. We find that the firm takes either a car-strategy or a truck-strategy for profit maximization. For a traffic mix with relatively large car volume and small truck volume, the car-strategy results in no trucks using the toll road, while the truck-strategy results in all trucks using the toll road. We derive the equilibrium flow pattern under any combination of car-toll and truck-toll, based on which we identify a profit-maximizing frontier and a strategy-switching frontier in the car-toll and truck-toll two-dimensional space. By geometrically comparing the two frontiers, we establish general conditions under which each strategy will be taken, which suggest that the truck-to-car VOT ratio, the total traffic demand, and the difference in travel distance between the two roads are critical in shaping the firm's strategy.

Tolling the Freeway: Congestion Pricing and the Economics of Managing Traffic

will manually Highway congestion increases the cost of travel in most urban areas of the United States. Policy makers have tried to reduce congestion by building more highways and mass transit. This approach is expensive and has generally failed to put a significant dent in congestion. Long commute times cost the United States an estimated $121 billion in 2012. This paper examines the economics of highway congestion pricing. Its goal is to make clear to policy makers how a variable congestion toll can reduce congestion and improve the operation of urban highway systems. Failure to charge a toll in order to use a highway can lead to congestion at certain times of the day. Additional drivers entering the freeway at some point slow traffic, which imposes an externality or cost on other highway users. The result is an inefficient use of the highway and too much infrastructure investment. The congestion externality can be corrected by a congestion toll that varies with the level of traffic. There are concerns that gasoline and congestion taxes are regressive. Many factors, such as the proximity of residential communities to jobs, can influence this outcome. Also, the use to which the tax revenues are put determines the degree a tax is regressive or progressive. The evidence is mixed with respect to congestion tolls. In order to better understand how congestion pricing might be implemented in the United States, cases where variable highway pricing systems have been used are analyzed. The evidence indicates congestion tolls reduce congestion and increase driving speeds. These cases provide examples of how congestion pricing might be implemented in the United States. To encourage and facilitate the adoption of congestion pricing in the United States, congestion tolls should be made legal on all interstate highways. They could stand alone or be part of a vehicle-miles-traveled tax. While both types of taxes provide revenues and influence traffic, the congestion toll has a bigger impact on improving highway efficiency as it directly addresses peak congestion. Advances in technology have lowered the transaction costs of collecting tolls, eliminating a barrier to adoption. Experience with congestion tolling improves the public perception and willingness to accept highway tolls. One tactic that has been successful is to follow a pricing experiment with a referendum on whether the system should be made permanent. The private sector’s role in building and managing roads can be increased to improve highways in the United States. The private sector offers a source of capital to expand the highway system. An advantage of private ownership is that it creates incentives for efficient management.

The time limit on copyright: an unlikely tragedy of the intellectual commons

With their “tragedy of the commons” paradigm for intellectual property, Landes and Posner argue that the most important benefit of intellectual property rights is not that they generate incentives to create new works, but that they ensure the efficient exploitation of existing intellectual works. This alternative economic case for IP notably relies on the argument that allowing the copyright on certain massively popular works to expire could lead to their overexploitation, generating negative externalities similar to congestion externalities. This article will assess in detail the plausibility of this effect, by reviewing its most plausible interpretations: a boredom effect, a “blurring” or “tarnishment” effect, a snob effect, or a decrease in product diversity. I will argue that while Landes and Posner’s argument is ultimately inconclusive and unverified by the current state of empirical research, it also raises greater challenges than has usually been thought. Moreover, taking their argument seriously can also contribute to a better understanding of the purposes and limits of an intellectual property regime.

Parking Taxes as a Second Best Congestion Pricing Mechanism

Growing vehicle use and congestion externalities have led many to consider alternative congestion pricing mechanisms, as road pricing often has high infrastructural costs and faces public opposition. This paper explores the role of parking taxation in reducing congestion by considering a natural experiment created by the progressive January 1, 2012 Chicago parking tax increase. Exploiting differences in vehicle use across income groups, it is estimated that the approximately $2 a day parking tax increase led to a 4-6 percent reduction in total vehicle trips in high-income areas, with the largest response seen on roads more heavily used by commuters. Also found are corresponding increases in use of public transit and a 3. 1 percent aggregate reduction in vehicle trips. It is concluded that parking taxes can help mitigate congestion externalities, although they are no more than about half as effective as more efficient congestion tolls.

Does public transit reduce car travel externalities? Quasi-natural experiments' evidence from transit strikes

One of the unanswered questions in the field of urban economics is to which extent subsidies to public transit are justified. We examine one of the main benefits of public transit, a reduction in car congestion externalities, the so-called congestion relief benefit, using quasi-natural experimental data on citywide public transit strikes for Rotterdam, a city with mild congestion levels. On weekdays, a strike induces travel times to increase only marginally on the highway ring road (0.017min/km) but substantially on inner city roads (0.224min/km). During rush hour, the strike effect is much more pronounced. The congestion relief benefit of public transit is substantial, equivalent to about 80% of the public transit subsidy. We demonstrate that during weekends, travel time does not change noticeably due to strikes. Furthermore, we show that public transit strikes induce similar increases in number of cyclists as number of car travelers suggesting that bicycling-promoting policies to reduce car congestion externalities might be attractive in combination with first-best congestion pricing.

E-commerce and traffic congestion: An economic and policy analysis

E-commerce, due to its ability to re-direct consumers from physical stores to online, can potentially alleviate traffic congestion. In this paper, we set up a theoretic model to analyze interactions between a firm’s distribution strategy and traffic congestion. In an unregulated economy, we first characterize the private firm’s optimal strategy concerning e-commerce under the influence of traffic congestion. We then examine a centralized economy where the firm is publicly owned and derive the distribution strategy that maximizes social welfare. Comparing the two cases, we show that the private firm’s incentives may deviate from the socially optimal decisions, which leads to inefficiency. We identify two effects, i.e., monopoly effect and congestion externality effect, which drive the private firm to deviate from the social optimum. Based on our analysis, we propose a differentiated tolls/rebates policy to achieve maximum social welfare. Under such a policy, the firm will not only adopt the socially optimal distribution strategy but offer the socially optimal quantities.

Bottleneck congestion: Differentiating the coarse charge

The traditional bottleneck model for road congestion promotes the implementation of a triangular, and time varying, charge as the optimal solution for the road congestion externality. However, cognitive and technological barriers put a practical limit to the degree of differentiation real world implementations can handle. The traditional approach to accommodate for this concern has been a step toll, with the single step coarse charge as its simplest case.In this paper we study how efficiency of the coarse charge can be improved by differentiating its level and timing across groups of travellers. We use the traditional bottleneck model to analyse how the coarse charge can be differentiated over two groups of travellers assuming inelastic peak-hour demand.The results of our analysis indicate that differentiating the coarse charge across two groups of travellers considerably improves its efficiency without increasing cognitive effort and decision making costs for the individual traveller. A numeric illustration reveals a welfare gain of 69% of the first-best charge, up from 53% for the generic coarse charge. This increase is similar to what is obtained by moving from the coarse charge to a generic two step toll. Once different groups have been defined, one could in fact achieve the same gains by temporal separation of drivers, for example by use of licence plate numbers.The presented charging regime has a considerable degree of flexibility with respect to the share of travellers to attribute to each scheme, which further adds to its merits in practical applicability.