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Manchester Grand Hyatt, Regatta C
Hosted By:
American Real Estate and Urban Economics Association
and the influence of noise on housing prices. To overcome the challenge of mapping noise data with
subjective emotion, we use a novel data source—text-based noise complaint records from residents
in a town in Singapore—and apply natural language processing (NLP) tools to conduct sentiment
analysis. To address the endogeneity concern regarding the bus route, we use the hypothetical least-cost path as an instrument for the existing bus route. We find that living closer to the bus route for
every 100 meters increases noise complaints by around 10 percentage points, and the effect is more
severe on medium floor levels (5th- 8th floors) and near bus stops (within 100 meters). We further
link noise with housing price and discover a price reduction of 3% with a 1-scale-point increase
in noise complaints. This implies that bus noise osets 18.8% of the benefit from convenience,
which sheds light on the importance of noise insulation policy and design.
equilibrium simulation model of a monocentric city with multiple transport modes. Households optimally choose a commuting mode to work: walking, taking public transit, driving, carpooling, taking Uber, or taking Uber to the nearby transit station to take public transit. The simulation results show that the adoption of Uber reduces traffic congestion, prevents urban sprawl, and lowers energy consumption and carbon emissions. Its effects on the public transit usage depend on the quality of the existing transit system. It complements public transit usage under a high quality transit system while serves as a substitute under a low quality system. In addition, public transit expansion has little effects on traffic congestion and the environment regardless of the entry of Uber. Finally, the regulation imposed on Uber reduces its usage and makes it less effective at complementing public transit and improving the environment.
Transportation
Paper Session
Saturday, Jan. 4, 2020 2:30 PM - 4:30 PM (PDT)
- Chair: Edward Coulson, University of California-Irvine
Public Transport, Noise Complaints, and Housing: Evidence from Sentiment Analysis in Singapore
Abstract
This paper investigates the effect of a new bus route on subjective noise complaints of residentsand the influence of noise on housing prices. To overcome the challenge of mapping noise data with
subjective emotion, we use a novel data source—text-based noise complaint records from residents
in a town in Singapore—and apply natural language processing (NLP) tools to conduct sentiment
analysis. To address the endogeneity concern regarding the bus route, we use the hypothetical least-cost path as an instrument for the existing bus route. We find that living closer to the bus route for
every 100 meters increases noise complaints by around 10 percentage points, and the effect is more
severe on medium floor levels (5th- 8th floors) and near bus stops (within 100 meters). We further
link noise with housing price and discover a price reduction of 3% with a 1-scale-point increase
in noise complaints. This implies that bus noise osets 18.8% of the benefit from convenience,
which sheds light on the importance of noise insulation policy and design.
Competition and Quality Gains: New Evidence from the High-Speed Rails and Airlines
Abstract
This study examines the causal relationship between competition and service quality using the introduction of high-speed rail (HSR) as a clean source of exogenous variation in competition faced by intercity transportation providers. Utilizing a unique dataset containing the details of all flights departing from Beijing to 113 domestic destinations in China since January 2009, we employ a difference-in-differences approach to study the effects of high-speed rail entry on airlines’ service quality (on-time performance) and to identify the channels through which competition stimulates quality. We document two main findings. First, the entry of high-speed rail creates competition for the airline industry and reduces flight delays of the affected flights. Second, the reductions in departure delay, which airlines control mostly, and taxi-in time, which destination airport control, are identified as the sources of the increase in on-time performance.The Long Run Effects of Uber on Public Transit, Congestion, Sprawl, and the Environment
Abstract
Little is known about the long run effects of the widely adopted ride hailing transportation services such as Uber on our cities. This paper examines the long run general equilibrium effects of this new type of transportation service on public transit usage, traffic congestion, urban sprawl, and the environment using a spatial generalequilibrium simulation model of a monocentric city with multiple transport modes. Households optimally choose a commuting mode to work: walking, taking public transit, driving, carpooling, taking Uber, or taking Uber to the nearby transit station to take public transit. The simulation results show that the adoption of Uber reduces traffic congestion, prevents urban sprawl, and lowers energy consumption and carbon emissions. Its effects on the public transit usage depend on the quality of the existing transit system. It complements public transit usage under a high quality transit system while serves as a substitute under a low quality system. In addition, public transit expansion has little effects on traffic congestion and the environment regardless of the entry of Uber. Finally, the regulation imposed on Uber reduces its usage and makes it less effective at complementing public transit and improving the environment.
Discussant(s)
Janet Kohlhase
,
University of Houston
Jeffrey Cohen
,
University of Connecticut
Jan Brueckner
,
University of California-Irvine
Jeffrey Lin
,
Federal Reserve Bank of Philadelphia
JEL Classifications
- R4 - Transportation Economics
- O1 - Economic Development