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Public transport, noise complaints, and housing: Evidence from sentiment analysis in Singapore

Author

Listed:
  • Yi Fan
  • Ho Pin Teo
  • Wayne X. Wan
Abstract
This paper investigates the effect of a new bus route on noise complaints of residents and the influence of noise on housing price. 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 tools to conduct sentiment analysis. To address the endogeneity concern regarding the bus route, we use a hypothetical least cost path as an instrument for the existing bus route. We find that living closer to the bus route for every 100 m 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 m). 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 offsets 17.8% of the benefit from convenience, which sheds light on the importance of noise insulation in transit‐oriented developments.

Suggested Citation

  • Yi Fan & Ho Pin Teo & Wayne X. Wan, 2021. "Public transport, noise complaints, and housing: Evidence from sentiment analysis in Singapore," Journal of Regional Science, Wiley Blackwell, vol. 61(3), pages 570-596, June.
    • Handle: RePEc:bla:jregsc:v:61:y:2021:i:3:p:570-596
    DOI: 10.1111/jors.12524
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    Cited by:

    1. Wayne Xinwei Wan & Thies Lindenthal, 2023. "Testing machine learning systems in real estate," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(3), pages 754-778, May.
    2. Diao, Mi & Li, Qiang & Sing, Tien Foo & Zhan, Changwei, 2023. "Disamenities of living close to transit tracks: Evidence from Singapore's MRT system," Regional Science and Urban Economics, Elsevier, vol. 100(C).

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