Development Patterns and the Recreation Value of Amenities

Public open spaces around and within urban areas have been increasingly developed due to greater population pressures. My paper investigates if land around public open spaces is likely to get developed faster since households are attracted to the recreation value as well as the environmental amenities of the public open space. There has been inadequate attention in the literature to the influence of the different sources of value of open space on housing prices. While views of open space are certainly an important source of value to households, public open space is also valued because households enjoy recreation at the open space. Adopting the monocentric city model, simulations examine how the different sources of value of public open space influence the developed area, rent gradient and the development density of an urban area. The monocentric city model has residents competing for housing around a single central business district (CBD) while developers choose the density of development from the expected prices of the homes at that location in the city. Simulations of the closed city model result in equilibrium rent gradients for land and the housing, a utility level, and a city boundary. By referencing the monocentric city model with two-dimensional coordinates, Wu and Plantinga (2003) are able to more spatially explicitly examine the influence of amenities on the equilibrium state of the city. Amenities are shown to generate leap-frog development, influence the developed area of the city, the population density, rent gradients and location of different income groups. Although different shapes and areas of amenities are examined in their paper, there is no investigation of the proper proximity of these amenities to each other. Several small amenities dispersed far apart from each other in the city may result in less total amount of developed land than if there is only a single large amenity. Another reason that the proximity of amenities to each other matters is that the net benefits from recreation are influenced by the spatial arrangement of the amenities. Consumer´s surplus from recreation trips to the amenity is the net benefit of the amenity, with the price of a recreation trip including the travel cost to the amenity. The travel costs from recreation at amenities depend on how widely dispersed the amenities are in the city. While several amenities located widely throughout a city lower the travel costs of recreation, the city tends to diffuse more too resulting in a larger developed area. On the other hand, a single centrally located amenity contracts the city resulting in a smaller developed area although the travel costs of recreation rise slightly. Simulations from the model collect information on the aggregate amount of recreation trips, recreational net benefits, and the developed area. More localized benefits of amenities like nice views and cleaner air have a stronger influence on housing prices and development densities than the less localized benefits of amenities like recreation. If the travel costs for recreation are low, then only the localized benefits of amenities influence housing prices and development densities. However, if the demand for recreation and the travel costs to reach the amenity is high, the benefits of recreation have the potential to influence the housing prices and development densities in that area of the city. There are several potential solutions to the problem of recreation benefits of the amenities leading to the unwanted development of natural or agricultural land. The simplest solution is to regulate that no recreation take place at the amenity. Of course, the nice views and cleaner air may still draw development outward, and the enforcement of no recreation is necessary. Rather than prohibit recreation, raising user fees at recreation sites is a way to generate revenue for the city while simultaneously restraining sprawl. If the cost of travel to a recreation site is high, development is more likely near the site since households want the benefit of a trip without the high cost of travel to the site. If roads to the recreation site are improved to reduce the cost of travel, households will prefer to locate close to the central business district rather than the recreation site to reduce the cost of their daily commutes.Public Economics,

Identifying Individual Discount Rates and Valuing Public Open Space with Stated Preference Models

An individual's rate of time preference is an important consideration for individuals deciding whether to support a public good since the benefits of a public good often come in the future. Our study finds individual discount rates from a contingent valuation method (CVM) question where the time frame of the payment schedule is varied across surveys. We find discount rates similar to the rates found in the recent revealed preference and experimental literature of around 30%. Our CVM question addresses the preservation of additional open space adjacent to a large regional park at the urban fringe of Portland, Oregon.Resource /Energy Economics and Policy, H43, Q51, Q15,

Simulation study on the fleet performance of shared autonomous bicycles

Rethinking cities is now more imperative than ever, as society faces global challenges such as population growth and climate change. The design of cities can not be abstracted from the design of its mobility system, and, therefore, efficient solutions must be found to transport people and goods throughout the city in an ecological way. An autonomous bicycle-sharing system would combine the most relevant benefits of vehicle sharing, electrification, autonomy, and micro-mobility, increasing the efficiency and convenience of bicycle-sharing systems and incentivizing more people to bike and enjoy their cities in an environmentally friendly way. Due to the uniqueness and radical novelty of introducing autonomous driving technology into bicycle-sharing systems and the inherent complexity of these systems, there is a need to quantify the potential impact of autonomy on fleet performance and user experience. This paper presents an ad-hoc agent-based simulator that provides an in-depth understanding of the fleet behavior of autonomous bicycle-sharing systems in realistic scenarios, including a rebalancing system based on demand prediction. In addition, this work describes the impact of different parameters on system efficiency and service quality and quantifies the extent to which an autonomous system would outperform current bicycle-sharing schemes. The obtained results show that with a fleet size three and a half times smaller than a station-based system and eight times smaller than a dockless system, an autonomous system can provide overall improved performance and user experience even with no rebalancing. These findings indicate that the remarkable efficiency of an autonomous bicycle-sharing system could compensate for the additional cost of autonomous bicycles